Page 1 of 244 Project Number: 318023 Project acronym

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Project Number: 318023

Project acronym: SmartC2Net

Project title: Smart Control of Energy Distribution Grids over Heterogeneous

Communication Networks

Contract type: Collaborative project (STREP)

Deliverable number: D1.1 - version 2

Deliverable title: SmartC2Net Use Cases, Preliminary Architecture and Business

Drivers

Work package: WP1 -Use Cases and Architecture

Due date of deliverable: M22 – September 2014

Actual submission date: 30/09/2014

Start date of project: 01/12/2012

Duration: 36 months

Editor(s): Giovanna Dondossola, Roberta Terruggia (RSE)

Authors: Giovanna Dondossola (RSE), Roberta Terruggia (RSE)

S. Bessler (FTW), J. Grønbæk (FTW), P. Zwickl (FTW), R. Løvenstein

Olsen (AAU), F. Iov (AAU), Ch. Haegerling (TUDO), F. Kurtz (TUDO), D.

Iacono (RT), A. Bovenzi (RT), S. Marzorati (VO), A. Carrapatoso

(EFACEC)

Contributing partners: FTW Forschungszentrum Telekommunikation Wien (FTW), Aalborg

University (AAU), Technische Universität Dortmund / Communications

Networks Institute (TUDO), ResilTech S.R.L. (RT), Ricerca Sul Sistema

Energetico (RSE), Vodafone Omnitel N.V. (VO), Efacec Engenharia e

Sistemas SA (EFACEC)

Dissemination Level of this Deliverable: PU

Public PU

Restricted to other programme participants (including the Commission Services) PP

Restricted to a group specified by the consortium (including the Commission Services) RE

Confidential, only for members of the consortium (including the Commission Services) C0

This project has received funding from the European Union’s Seventh Framework Programme for

research, technological development and demonstration under grant agreement no 318023. Further

information is available at www.SmartC2Net.eu.

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Introductory note:

Following the first review meeting and the comments received, changes within the updated version 2

have been made in the following sections (notwithstanding the correction of a few minor details in

other places):

Section Executive Summary

Section 1 Introduction: from SmartC2Net UC to the overall architecture

Section 2 The Use Cases and their key elements (Intro)

Section 5 UC ICT requirements & success KPI (All subsections)

Section 11 Annex C - Table of Requirements (All subsections)

Section 12 Annex D - Table of KPIs (All subsections)

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Executive Summary

The SmartC2Net project addresses different control scenarios related to the evolution of the

distribution grids. In order to provide a good coverage of the control applications characterizing the

evolution of European smart grids in the next future, the following four use cases are analyzed in

detail:

• Voltage Control in Medium Voltage Grids

• External Generation Site

• Automated Meter Reading and Customer Energy Management Systems

• Electrical Vehicle Charging in Low Voltage Grids.

Starting from the analysis of these use cases a preliminary global high level architecture is derived at

the aim of highlighting the interactions among the respective control components and ICT networks.

An economic analysis of the use case scenarios is performed for getting the specific business drivers

and business requirements of the envisaged smart grid evolution.

Most outcome from the UC analysis and the overall architecture have provided inputs to the

monitoring, communication, control, evaluation and test bed activities undertaken by the other

project work packages.

The requirements and the Key Performance Indicators (KPIs), initially determined from the use case

analysis, will be used along the whole project running for the evaluation of the SmartC2Net

achievements.

This second version of the deliverable addresses the comments coming from the first review in

Brussels.

First of all the motivations for the four use case selection are better highlighted in the introduction

and in the Use Case chapter (Chapter 2).

The Requirements and KPIs definition and analysis have been improved with the quantitative values

and the mapping with related WPs. The aim is to point out which of the Requirements and KPIs are

addressed by the project developments and how they are evaluated.

As a means to highlight the more relevant elements for the project developments, the priority field

of the requirement template is used and a reduced number of requirements and KPIs has been

focused. This work is reflected in Chapter 11 Annex C and Chapter 12 Annex D, that now provide the

list of enhanced requirements and KPIs presented in a more readable way, and in their enriched

analysis reported in Chapter 5.

Given its relevance to the SmartC2Net exploitation plan, the business analysis have been elaborated

further in deliverable D7.2 where the business drivers and benefits have been linked to the use case

KPIs from SmartC2Net.

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Table of Contents

List of Figures ........................................................................................................................................... 7

List of Tables .......................................................................................................................................... 10

Glossary ................................................................................................................................................. 11

1 Introduction: from SmartC2Net UC to the overall architecture ................................................... 13

2 The Use Cases and their key elements .......................................................................................... 15

2.1 Voltage Control in Medium Voltage Grid ............................................... 16

2.2 External Generation Site ........................................................................ 17

2.3 Automated Meter Reading (AMR) and Customer Energy Management

Systems (CEMS) 19

2.4 Electrical Vehicle Charging in Low Voltage Grids ................................... 21

3 The business drivers ...................................................................................................................... 24

3.1 Business Drivers ..................................................................................... 24

3.1.1 Telco Sector ............................................................................................ 24

3.1.2 Categories .............................................................................................. 27

3.1.3 Use cases ................................................................................................ 32

3.2 Business Requirements .......................................................................... 38

3.2.1 Telco and energy sector interplay .......................................................... 39

3.2.2 Template ................................................................................................ 39

3.2.3 Use cases ................................................................................................ 43

4 UC details ....................................................................................................................................... 49

4.1 Voltage Control in Medium Voltage Grid ............................................... 49

4.1.1 Objective ................................................................................................ 49

4.1.2 Architecture and Sequence Diagrams .................................................... 51

4.1.3 Fault/threat analysis/scenarios .............................................................. 53

4.2 External generation site ......................................................................... 56

4.2.1 Objective ................................................................................................ 56

4.2.2 Control of assets .................................................................................... 59

4.2.3 Network adaptive data transport (AN/WAN) ........................................ 59


4.3 Automated Meter Reading (AMR) and Customer Energy Management

Systems (CEMS) 63

4.3.1 Objective ................................................................................................ 63



4.4 Electrical Vehicle Charging in Low Voltage Grids ................................... 70

4.4.1 Objective ................................................................................................ 70



5 UC ICT requirements & success KPI ............................................................................................... 78

5.1 Requirement Template .......................................................................... 78

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5.2 Requirements ......................................................................................... 80

5.3 KPIs Template ......................................................................................... 84

5.4 Key Performance Indicators (KPIs) ......................................................... 85

6 Preliminary overall architecture .................................................................................................... 88

6.1 Global architecture ................................................................................ 89

6.1.1 Layered architecture .............................................................................. 89

6.1.2 Distribution of functions ........................................................................ 90

6.2 Use Case mapping .................................................................................. 91

7 Conclusions and Outlook ............................................................................................................... 95

8 Bibliography ................................................................................................................................... 96

9 Annex A - Value Networks ............................................................................................................. 98

9.1 Electrical Grid Value Network ................................................................ 98

9.1.1 Entities ................................................................................................. 100

9.1.2 Main Value Flows ................................................................................. 101

9.2 SmartC2Net Value Network ................................................................. 102

9.2.1 Entities (Revised) .................................................................................. 104

9.2.2 Main Value Flows (Revised) ................................................................. 107

10 Annex B - UC templates ....................................................................... 109

10.1 USE CASE NAME: Medium Voltage Control ......................................... 109

10.1.1 Description of the Use Case ................................................................. 109

10.1.2 Diagrams of Use Case ........................................................................... 112

10.1.3 Technical Details .................................................................................. 120

10.1.4 Step by Step Analysis of Use Case ........................................................ 125

10.1.5 Information Exchanged ........................................................................ 133

10.1.6 Common Terms and Definitions .......................................................... 134

10.2 USE CASE NAME: Electrical Vehicle Charging in Low Voltage Grids .... 135







10.3 USE CASE NAME: External generation site .......................................... 160







10.4 USE CASE NAME: Automated Meter Reading (AMR) and Customer

Energy Management Systems (CEMS) ............................................................................................ 178



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11 Annex C - Table of Requirements ......................................................... 217

11.1 Requirements for Medium Voltage Control Use Case ......................... 217

11.2 Requirements for EV Charging Use Case ............................................. 223

11.3 Requirements for External Generation Use Case ................................ 226

11.4 Requirements for AMR and CEMS Use Case ........................................ 231

12 Annex D - Table of KPIs ........................................................................ 237

12.1 Key Performance Indicators for Medium Voltage Control Use Case ... 237

12.2 Key Performance Indicators for EV charging Use Case ........................ 240

12.3 Key Performance Indicators for External Generation Use Case .......... 242

12.4 Key Performance Indicators for AMR and CEMS Use Case .................. 243

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List of Figures

Figure 1 Overview of Medium Voltage Control Use Case ..................................................................... 16

Figure 2 Overview of External Generation Site Use Case ..................................................................... 18

Figure 3: Advanced Smart Meter Reading and Customer Energy Management System Scenario ....... 20

Figure 4 Overview of the EV Use Case .................................................................................................. 23

Figure 5 M2M device connections, energy and utility sector, worldwide, 2011–2021 [ANME12] ...... 25

Figure 6 – A categorisation of generic business drivers ........................................................................ 28

Figure 7 – A categorisation of business requirements .......................................................................... 39

Figure 8 - The Medium Voltage Control Function ................................................................................. 50

Figure 9 The UC Architecture ................................................................................................................ 51

Figure 10 Voltage Control – Communications ...................................................................................... 52

Figure 11 Medium Voltage Control Sequence Diagram ....................................................................... 53

Figure 12 Possible attack scenarios to the Voltage Control function ................................................... 54

Figure 13 Estimated RES Power per Substation (2020) ......................................................................... 55

Figure 14: Overview of external generation site use case .................................................................... 57

Figure 15: Overview of use cases – and fault/error cases. ................................................................... 58

Figure 16 Components distributed in the external grid operation case ............................................... 60

Figure 17 Functionalities in the external grid operation case ............................................................... 61

Figure 18 Overview of the sequence diagram for normal operation mode, capturing Control of Assets

and Data Transport. The specific fault/error cases can be seen in Annex B. ....................................... 62

Figure 19 Physical components of the use case and their locations in the Smart Grid setup .............. 64

Figure 20 Detailed use case clustering structure .................................................................................. 65

Figure 21 Mis-use diagrams for the considered CEMS functionalities.................................................. 67

Figure 22: Mis-sequence diagram for the MIM attack .......................................................................... 69

Figure 23 Networks of the EV use case ................................................................................................. 72

Figure 24 Overview of the interactions between components ............................................................ 73

Figure 37 Requirements: Project WP mapping ..................................................................................... 80

Figure 38 Requirements: WP2, WP3 and WP4 mapping Figure 39 Requirements: WP5 and WP6

mapping ................................................................................................................................................. 81

Figure 25 Requirements: Use Case ........................................................................................................ 81

Figure 26 Requirements: Category ........................................................................................................ 82

Figure 27 Requirements: Level .............................................................................................................. 82

Figure 28 Requirements: Priority .......................................................................................................... 82

Figure 29 MVC UC Requirements: Category Figure 30 MVC UC Requirements: Level ........... 83

Figure 31 EV UC Requirements: Category Figure 32 EV UC Requirements: Level ........... 83

Figure 33 EGS UC Requirements: Category Figure 34 EGS UC Requirements: Level .......... 83

Figure 35 CEMS AMR UC Requirements: Category Figure 36 CEMS AMR UC Requirements: Level . 84

Figure 40 KPIs: Project WP mapping ..................................................................................................... 85

Figure 41 WP2, WP3 and WP4 mapping Figure 42 WP5 and WP6 mapping.......... 86

Figure 43 KPIs: Use Case ........................................................................................................................ 86

Figure 44 KPIs: Scope ............................................................................................................................ 87

Figure 45 KPIs: Category ........................................................................................................................ 87

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Figure 46 MVC UC KPIs: Category Figure 47 MVC UC KPIs: Scope ...................... 87

Figure 48 EV UC KPIs: Scope Figure 49 EV UC KPIs: Category ..................... 88

Figure 50 EGS UC KPIs: Scope Figure 51 EGS UC KPIs: Category ............. 88

Figure 52 CEMS AMR UC KPIs: Scope Figure 53 CEMS AMR UC KPIs: Category ... 88

Figure 54 Overview of the SG architecture ........................................................................................... 90

Figure 55 Overview of Use Cases mapping ........................................................................................... 92

Figure 56 Detailed view of Use Cases mapping..................................................................................... 93

Figure 57: “Classical” Electrical Grid Value Network ............................................................................. 99

Figure 58 – SmartC2Net Value Network (with special consideration of chosen use cases) ............... 103

Figure 59 - Voltage Control ................................................................................................................. 113

Figure 60 - Voltage Control - Actors Interactions ................................................................................ 113

Figure 61 - Voltage Control - Use Case Diagram ................................................................................. 114

Figure 62 - Voltage Control - Use Case Diagram - attack scenarios .................................................... 114

Figure 63 - Voltage Control – Mapping on SGAM ............................................................................... 115

Figure 64 - Voltage Control - Overview of involved communications ................................................ 115

Figure 65 – Voltage Control – Communications .................................................................................. 116

Figure 66 – Voltage Control - Component Layer ................................................................................. 116

Figure 67 - Generation Forecast .......................................................................................................... 117

Figure 68 - Generation Forecast - Sequence Diagram ........................................................................ 117

Figure 69 – Voltage Control - Sequence Diagram ............................................................................... 118

Figure 70 - Voltage Control - DoS Attack to DER ................................................................................. 118

Figure 71 - Voltage Control - DoS Attack to MVGC ............................................................................. 119

Figure 72 - Voltage Control - Fake DER Set point ................................................................................ 119

Figure 73 - Voltage Control - Fake DER Set point (Man in the Middle) ............................................... 120

Figure 74 - Voltage Control - Fake TSO signal ..................................................................................... 120

Figure 75 Use case components and Networking Connectivity Options ............................................ 139

Figure 76 - Use Case Diagram for EV charging scenario ...................................................................... 140

Figure 77 - Message Sequence Diagram for EV charging scenario ..................................................... 141

Figure 78 - Use Case Diagram for energy and power management scenario ..................................... 142

Figure 79 - Message Sequence Diagram for energy and power management scenario .................... 143

Figure 80 - Use Case Diagram for Energy Market scenario ................................................................. 144

Figure 81 - Message Sequence Diagram for Energy Market Scenario ................................................ 145

Figure 82 - SGAM Function Layer ........................................................................................................ 146

Figure 83 – AS3 Metering information interrupted ............................................................................ 146

Figure 84 – AS2 LVGC-CSO connection interrupted ............................................................................ 147

Figure 85: Diagram of the Interactions described in section 4.1 ........................................................ 148

Figure 86 Overview of Use Case .......................................................................................................... 162

Figure 87 Overview of use cases ......................................................................................................... 164

Figure 88 Set of physical components and their locations in the smart grid setup ............................ 165

Figure 89 Different communication means used for the various components to interact with each

other .................................................................................................................................................... 166

Figure 90 Different functionalities used in the system in order to be able to execute the use cases

over the network on the different physical components ................................................................... 167

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Figure 91: Advanced Smart Meter Reading and Customer Energy Management System Scenario ... 186

Figure 92: Physical components of the use case and their locations in the Smart Grid setup ........... 187

Figure 93: Detailed use case clustering structure ............................................................................... 188

Figure 94: MM.01 Obtain meter reading on demand (refer to [4]) .................................................... 189

Figure 95: Sequence diagram MM.01.01 - Obtain remote meter reading on demand (refer to [4]) . 189

Figure 96: Sequence diagram MM.01.02 - Obtain walk-by meter reading on demand (refer to [4]) 190

Figure 97: MM.02 Obtain scheduled meter reading (refer to [5]) ...................................................... 190

Figure 98: Sequence diagram MM.02.01 - Obtain scheduled meter reading (refer to [5]) ................ 190

Figure 99: Sequence diagram MM.02.02 - Configure reading schedule (refer to [5]) ........................ 191

Figure 100: MM.03 Set tariff parameters (refer to [6]) ...................................................................... 191

Figure 101: Sequence diagram MM.03.01 - Set tariff parameter in the smart meter (refer to [6]) ... 191

Figure 102: Sequence diagram MM.03.02 - Set tariff parameter in the LNAP/NNAP(refer to [6]) .... 192

Figure 103: CI.01. customer information provision (refer to [8]) ....................................................... 192

Figure 104: Sequence diagram CI.01.01 - Send information to meter display (refer to [8]) .............. 193

Figure 105: Sequence diagram CI.01.02 - Send information to simple external consumer display (refer

to [8]) ................................................................................................................................................... 193

Figure 106: Sequence diagram CI.01.03 -– Smart Meter publishes information on simple external

consumer display (refer to [8]) ............................................................................................................ 193

Figure 107: ES.02 - Manage supply quality (refer to [7]) .................................................................... 194

Figure 108: Sequence diagram ES.02.01 - Configure power quality parameters to be monitored (ref.

[7]) ....................................................................................................................................................... 194

Figure 109: Sequence diagram ES.02.02 - Smart meter sends information on power quality to display

(refer to [7]) ......................................................................................................................................... 194

Figure 110: DG.01.01 - Direct load / generation demand – appliance has end-decision about its load

adjustment (refer to [14]) ................................................................................................................... 195

Figure 111: DG.01.02 - Direct load / generation demand - appliance has no control over its own load

adjustment (refer to [14]) ................................................................................................................... 196

Figure 112: Sequence diagram DG.03.01 - Information regarding power consumption / generation of

individual appliances (refer to [16]) .................................................................................................... 196

Figure 113: Sequence diagram DG.03.02 - Information regarding total power consumption (refer to

[16]) ..................................................................................................................................................... 197

Figure 114: Sequence diagram DG.03.03 - Price & environmental information (refer to [16]) ......... 197

Figure 115: Sequence diagram DG.03.04 - Warning signals based individual appliances consumption

(refer to [16]) ....................................................................................................................................... 197

Figure 116: External Actors (refer to [1]) ............................................................................................ 198

Figure 117:Mis-use diagrams for the considered CEMS functionalities ............................................. 208

Figure 118 Mis-sequence diagram for the MIM attack ....................................................................... 210

Figure 119: Mis-sequence diagram for the Masquerade attack ......................................................... 212

Figure 120 Mis-sequence diagram for the DoS attack ........................................................................ 213

Figure 121: Mis-sequence diagram for the Disclosure of message attack.......................................... 214

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List of Tables

Table 1 Overview of the CEN-CENELEC-ETSI AMR / CEMS sequence diagrams of Annex B - UC

templates............................................................................................................................................... 66

Table 2: Overview of the mis- sequence diagrams of Annex B - UC templates .................................... 70

Table 3 Requirements Template Description ........................................................................................ 79

Table 4 KPIs Template Description ........................................................................................................ 84

Table 5 Requirements for Medium Voltage Control Use Case ........................................................... 223

Table 6 Requirements for EV Charging Use Case ................................................................................ 226

Table 7 Requirements for External Generation Use Case ................................................................... 231

Table 8 Requirements of the AMR / CEMS Use Case .......................................................................... 236

Table 9 Key Performance Indicators for Medium Voltage Control Use Case ..................................... 240

Table 10 Key Performance Indicators for EV charging Use Case ........................................................ 241

Table 11 Key Performance Indicators for External Generation Use Case ........................................... 242

Table 12 Key Performance Indicators of the AMR / CEMS Use Case .................................................. 244

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Glossary

Acronym Definition

AC Air Conditioning Unit

AMI Advanced Monitoring Infrastructure

AMR Automated Meter Reading

AVR Automatic Voltage Regulator

CAM Control Area Manager

CEMS Customer Energy Management System

CHP Combined Heat and Power

CI Customer Information

CLS Controllable Load System

CPE Customer Premises Equipment

CS Charging Spot

CSO Charging Station Operator

CSP Connectivity Service Provider

DER Distributed Energy Resource

DG Distributed Generation

DMS Distribution Management System

DNO Distribution Network Operator

DoS Denial of Service

DSM Demand Side Management

DSO Distribution System Operator

EMG Energy Management Gateway

ESP Energy Service Provider

EV Electric Vehicle

FLIR Fault Location, Isolation and Restoration

GIS Geographic Information System

HAN Home Area Network

HES Head End System

HV High Voltage

IP Internet Protocol

KPI Key Performance Indicator

LAN Local Area Network

LNAP Local Network Access Point

LV Low Voltage

LVGC Low Voltage Grid Controller

M2M Machine-to-Machine

MDA Metering Data Aggregator

MDMS Meter Data Management System

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MIM Man In the Middle

MO Meter Operator

MPLS Multiprotocol Label Switching

MV Medium Voltage

MVGC Medium Voltage Grid Controller

MVNO Mobile Virtual Network Operator

NAN Neighbourhood Area Network

NNAP Neighbourhood Network Access Point

OLTC On Load Tap Changer

OMS Outage Management System

P Active power

PEV Plug-in Electric Vehicle

PG Power Grid

Q Reactive power

RES Renewable Energy Sources

SAS Substation Automation System

SGAM Smart Grid Architecture Model

SM Smart Metering

SSM Supply Side Management

TSO Transmission System Operator

UC Use Case

UI User Interface

V Voltage

VC Voltage Control

VPP Virtual Power Plant

WAN Wide Area Network

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1 Introduction: from SmartC2Net UC to the overall architecture

The expected growth in Distributed Generation (DG) will significantly affect the operation and the

control of today’s distribution systems. Being confronted with short time power variations of DGs,

the assurance of a reliable service (grid stability, avoidance of energy losses) and the quality of the

power may become costly. In this light, Smart Grids may provide an answer towards a more active

and efficient electrical network.

The SmartC2Net project addresses different control scenarios related to the evolution of the

European distribution grids. In particular this deliverable addresses the WP1 activity consisting in the

description of selected use cases with the identification of the requirements and details needed by

the others WPs. A first sketch of the overall architecture is presented and the specific economical

business driver derived.

Decision criteria for the selection of the use-cases are the following:

(1) architectural coverage of the smart grid domains and control layers;

(2) coverage of the time horizon from use-cases that are about to be implemented until future

smart grid control scenarios with deployment in 5-10 years;

(3) relevance/contribution to efficient LV/MV grid operation;

(4) challenges of the use-cases with respect to communication load, communication network

performance and control robustness.

Following the guidelines on the harmonized specification of smart grid use cases provided by the

committee Sustainable Processes of the Smart Grid Coordination Group by CEN/CENELEC/ETSI [UCC],

the following four use cases are analyzed:

Voltage Control in Medium Voltage Grids

External Generation Site

Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS).

Electrical Vehicle Charging in Low Voltage Grids.

Addressing different actors and control layers of the distribution grid, these use-cases provide a good

coverage of the applications characterizing the evolution of European smart grid in the next future:

from the medium voltage grids of the “Voltage Control in Medium Voltage Grid” use case, towards

the low voltage grids and customers involved in “Automated Meter Reading (AMR) and Customer

Energy Management Systems (CEMS)” use case. Some use cases, as Voltage Control in Medium

Voltage Grids and Automated Meter Reading (AMR) and Customer Energy Management Systems

(CEMS) deepen the ICT aspects starting from UC descriptions taken from CEN/CENELEC/ETSI

Coordination Groups on Smart Grid and Smart Meter, respectively. Others, as Electrical Vehicle

Charging in Low Voltage Grids and External Generation Site, are fully new control cases. In all cases

the goal of the analysis is to provide detailed views of the information, communication and

component layers of their control architectures.

Starting from the analysis of these use cases a preliminary global high level architecture is derived at

the aim of highlighting the interactions among the respective control components and ICT networks.

As planned in the project Annex I [DoW] in the next phase of the Task 1.2 this preliminary

architecture will be updated and integrated with the results obtained from the monitoring (WP2),

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communication (WP3) and control (WP4) architecture developments, and a more detailed version of

the SmartC2Net overall architecture will be provided in D1.2.

An economic analysis of the use case scenarios is performed for getting the specific business drivers

and business requirements of the envisaged smart grid evolution. More updated analysis of business

drivers and business requirements will be presented in Deliverable D.7.2.

The requirements and the Key Performance Indicator (KPI) for the evaluation of the SmartC2Net

achievements are determined from the use case analysis and they are studied under several

perspective in order to identify the most important ones. The mapping with the different

SmartC2Net WPs allows understanding how the project results will be addressed and evaluated.

In order to increase the readability of the document, the deliverable is organized into core chapters

presenting the basic methods and most relevant aspects, and a set of annexes providing further

details.

The core part is structured into seven chapters, as follows: chapter 2 introduces the key elements of

the four use cases, then chapter 3 presents the business drivers and the business requirements

related to the use cases. More details regarding the use cases are described in chapter 4 where the

fault/threat scenarios are introduced, and an extended requirement and KPI analysis is presented in

chapter 5. Chapter 6 presents a first high level sketch of the SmartC2Net architecture. Finally,

chapter 7 concludes the deliverable.

Annex A presents the SmartC2Net Value Network used for the analysis of the business drivers; Annex

B includes the full templates of the four UCs by adopting the standard template proposed by IEC TC8

AHG 4 [IEC TC8], Annexes C and D include the refined UC requirements and KPIs lists, respectively.

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2 The Use Cases and their key elements

This Chapter introduces a general vision of the four Use Cases that will be described with more

details in Chapter 4. Following the guidelines on the harmonized specification of smart grid use cases

provided by the committee Sustainable Processes of the Smart Grid Coordination Group by

CEN/CENELEC/ETSI [UCC], the following four use cases are analyzed:

Voltage Control in Medium Voltage Grid


Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS)

Electrical Vehicle Charging in Low Voltage Grids.

The selected Use Cases provide a good coverage of the applications characterizing the evolution of

European smart grid in the next future and address the major actors and control layers of the power

grid.

In particular the Voltage Control in Medium Voltage Grids use case addresses a key functionality in

the operation of DER connecting grids, and considers the ICT aspects and related cyber security

challenges. The connection of DERs to medium voltage grids can perturb the status of the whole

power grid: the non-deterministic behavior of DERs should be managed using ICT components in

order to avoid effects on the contracted terms of the DSO (Distribution System Operator) with the

TSO (Transmission System Operator) and on the quality of service of the neighbor grids.

The external generation site resembles a small town with some local industry, covering both low

voltage and medium voltage quality control. The scenario setup is a quite typical setup in many

places in Europe and therefore has a significant relevance.

The Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS) describes

two basic functionalities for enabling future distribution grids for load balancing and integration of

decentralized and distributed (renewable) energy resources. Different European utilities are moving

on the introduction of these functionalities on their grids. According to the European Mandate

M/441, a monthly billing for the customer and a roll-out of smart meters in 80% of all European

households until 2020 is targeted, which requires cost-efficient, modular concepts for the

comprehensive deployment of smart metering devices enabling a variety of flexibility management

scenarios. New customer programs to make the home power consumptions more “intelligent” are

emerging.

A specific flexibility management use case is represented by the Electrical Vehicle Charging in Low

Voltage Grids. In order to reach the European 2020 climate and energy package, in particular the 20%

reduction of CO2, new energy strategies are evaluated. The transition from fuel-powered cars to

Electrical Vehicles represents a challenging goal that need to be addressed by the power utilities in

order to avoid problems on the electrical grid due to the recharging operation and to make this

transition attractive for customers.

The functionalities addressed by the selected use cases represent interesting and relevant aspects for

the External Advisory Board members composed by DSO from different countries. The discussion and

the iteration performed during the first meeting and continuing in the next ones allow obtaining an

aligned vision with the real needs of the utilities for the future European distribution grids.

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The focus of the analysis is given to the ICT aspects and to the communication needs of the control

scenarios. Both normal and abnormal behaviors are addressed by each Use Case, describing the

effect of malicious attacks or accidental faults. The interactions among the Use Cases, participating to

the control of the whole grid system, are shown in Chapter 6.

2.1 Voltage Control in Medium Voltage Grid

The primary aim of this use case is to address the communication needs of a Voltage Control function

for medium voltage grids connecting Distributed Energy Resources (DERs). The actions derived from

the Voltage Control function are considered with the specific aim of defining an ICT architecture

suitable for the security analysis. The Medium Voltage Control is a didactic case for illustrating the

need of cyber security in smart grid applications, first because its behaviour influences both the

system operation and economy, secondly for the high level of inter-networking of its ICT

architecture. The evaluation of attack processes to the Voltage Control function is aimed at

identifying security controls to counter act those attacks having the capability of compromising the

voltage profile [DGPT12].

The connection of DERs to medium voltage grids can influence the status of the whole power grid:

the behaviour of DERs can affects the capacity of the DSO (Distribution System Operator) to comply

with the contracted terms with the TSO (Transmission System Operator) and directly the quality of

service of their neighbour grids.

The main functionality of the medium voltage control function is to monitor the active distribution

grid status from field measurements and to compute optimized set points for DERs, flexible loads and

power equipment deployed in HV/MV substations.

Figure 1 Overview of Medium Voltage Control Use Case

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The optimization function is performed by a Medium Voltage Controller of a HV/MV substation

control network. In order to pursue the previously defined objective, the Controller calculates in a

coordinated manner the optimal states of the controllable devices across the substation area.

The control strategy requires information originating externally to the DSO domain. From the

operation stand point, the optimization function has to receive voltage regulation requests by the

TSO whenever a transmission grid contingency needs to apply preventive measure to voltage

collapse. Load and generation forecasts are used to optimize the operation of distributed devices,

while the economic optimization is based on market prices and DER operation costs.

A first major design assumption underlying the use case ICT architecture (see Chapter 6) is that

communications from the DMS (Distribution Management System) application in the DSO centre

provide to the Controller the information related to DER features, changes in the grid topology,

requests by TSO, load/generation forecasts and market data. This design choice preserves the

integrity of the distribution grid operation by limiting the communication channels at the substation

level and concentrating the communications with those external actors at the DSO centre level.

The control loop is triggered by critical events (e.g. under/over voltage event, TSO request, grid

topology change). In absence of criticalities, the VC function is executed on a periodic base (e.g.

every 15 minutes) for optimization purposes. The total response time of its closed control loop, from

the start of the elaboration to the end of the set point actuation, depends on actuation time

constants of OLTC and DER power electronics.

The architectural layout deployed for implementing the VC function depends on the responsibilities

attributed to the use case roles and on country-based regulations. According to the architectural

layout in Figure 1, the data supply chain of the VC function depends on several communication links

enabling remote accesses from systems outside the perimeter of the DSO operation. The DMS

application in the DSO centre has permanent links (the green WAN in Figure 1) with four actors (TSO,

Aggregator, Generation Forecaster and Load Forecast); the Controller in the DSO substation has

permanent communication links (the red WAN in Figure 1) with third party DERs, possibly deploying

heterogeneous communication technologies available in different geographical areas;

communications between DMS and substation automation and control systems pass through the

DSO SCADA links (the blue WAN), possibly based on telco services. By focusing on the core of the VC

scheme, it results evident that the correct elaboration of the optimal set points depends on the

provision of correct operation and economic data from the above communication channels. A

malicious attack to one of the above communication links may cause either the loss of input data

(generation forecasts, economic data from the Aggregator, TSO requests, topological changes), or

the introduction of faked input values or output set points. The effects of such communication

attacks may lead the control function either to diverge from optimum set points or, even worst, to

produce inadequate set points with cascading effects on connected generators. The global impact of

cyber attacks to the Voltage Control functions on the supplied power depends on the grid size, the

amount of distributed generation, the control network topology on the top of the power grid

structure and the extension of the attack.

2.2 External Generation Site

With the anticipated increase in small decentralized energy resources from primary wind and

photovoltaic (PV), the low voltage (LV) grids are exposed to new load scenarios than originally

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designed for. Further, new high consumer demands from Electrical Vehicle (EV) mobility and heat

pumps challenge existing LV grid infrastructures additionally. As a result, there is an increased

interest in technologies to improve the LV grid operation. These mainly entail: local energy storage,

active control of energy fed in electrical grid, flexible demand control (entailing both end-user

managed demand response and autonomic demand control) for house-holds and EVs. This use case

covers the automation and control techniques required for future LV grids and enables the DSO to

utilize the flexibility of the LV grid assets. All this happens over an imperfect communication network

which poses challenges to the operation of the grid. Therefore, the objective of this use case is to

demonstrate the feasibility of controlling flexible, distributed loads and renewable energy resources

in LV grids over an imperfect communication network. Flexibility of LV grids for upper hierarchical

control levels is also investigated.

Primary Substation

Automation&Control

MVGC

ProsumerLarge DER Large DER

HV Grid

HV

MV

MV

LV

Prosumer

Consumer

Interm. DER

Consumer

MicroDER

SME

Farm

SME

EnergyStorage

…

MV

LV

...

...

...

...

MV

LV

Use Case 2.3

Prosumer

Retailers

DMS

TSO

ForecastProviders

Markets

AggregatorsMV/LV

WAN

AN

Technical Flexibility

&Performance

Commercial Feasibility

& Flexibility

AN Provider(s)

AN Provider(s)

WAN Provider(s)

Secondary Substation

Automation&Control


Automation&Control

Secondary SubstationAutomation & Control

LVGC

Figure 2 Overview of External Generation Site Use Case

The reference scenario for this use case consists of a MV and LV grid shown in Figure 2, contains: 1)

fixed and shift-able energy consumption from households, small enterprises and EVs, 2) production

from PVs and wind turbines, 3) Energy storage. Hierarchical controller architecture is utilized, where

a distribution management system (DMS) is at the upper most level. This provides commands to the

MV grid controller, which sends commands to the LV grid controllers as well as flexible generation

and consumption in the MV grid. Finally, the LV grid controller sends commands to flexible assets in

the LV grid. The LV grids are connected to the MV grid via a controllable transformer station with an

online tap changer (OLTC).

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It is considered that all components in the architecture are connected with a communication

network providing monitoring data from and control of the individual components. The LV grid

implements its own control mechanisms which are responsible for: a) maintaining an acceptable

voltage profile, security and safety, b) balancing available power resources (energy storage and

generation) with the (flexible) demand, and c) handling the interactions between a) and b). The

control infrastructure is managed by one or more dedicated LV grid controllers which provide

functionality to support the sub-use cases introduced in the following sections. This Use Case is

considering only faults and performance degradation within the public communication network, and

the system’s overall ability to perform normal grid operation even during network faults and

performance degradation.

With the introduction of significant decentralized energy production from wind and photovoltaic

plants in the LV grid along with energy storage as illustrated in Figure 2, new problems arise. In this

setting the low voltage grid control should preferably be able to: 1) control the voltage profile along

the low voltage feeders, 2) optimize MV grid losses; 3) optimize energy cost; 4) aggregate the

flexibility of LV and MV assets that can be used as an input to the MV control and distribution

management system (DMS). The grid operation should in this matter be resilient to faults and

performance degradation in the public communication lines between the low voltage grid controller

and the assets in the electrical grid with special focus on the low voltage side, hereby limiting the

effect of changing network conditions on the electrical grid performance. This means that the use

case also includes mechanisms for adapting the communication to events in the network that

challenge the communication and the quality of the data exchanged between the controlled and

controlling entities.

Under these settings, two focus points are defined as to show the above characteristics:

- Technical flexibility and performance: Resilience of control towards faults and congestions in

communication networks.

- Commercial feasibility and flexibility: Aggregation of generation and demand (abstraction of

models).

2.3 Automated Meter Reading (AMR) and Customer Energy Management Systems

(CEMS)

This use case describes two basic functionalities for enabling future distribution grids for load

balancing and integration of decentralized and distributed (renewable) energy resources (Figure 3).

Therefore, Automated Meter Reading (AMR) is an enabling technology, which is capable of

generating precise multi-sector metering data and aggregate them on local grid operator side for

large-area and in-house analysis of current energy consumptions as well as grid load conditions.

Additionally, current efforts in the context of the Internet of Things aim to connect more devices in

the household to create a more intelligent home area network (HAN), including components of

customer energy management systems (CEMS) like distributed energy resources (DER) and storages,

demand side management, private electric vehicle charging and user interaction. In the context of

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AMR, this adds an additional way of home building automation by combining the energy

consumption of accordant components with the current status of the energy grid to improve its

stability by shifting loads balanced with the neighborhood area network.

Shiftable

loads

In house applications

Communication

hub

Local CHP

Photovoltaic

Household

appliance

Air

conditioning

units

Decentralized

power production

Smart

Metering

Smart

Metering

EMG

User

interface

Home area network with AMR / CEMS

CommunicationPower

ControlMetering

Energy grid

Communication network

Neighbourhood area

network

Control

Data aggregator

Power predictor

Cellular

networkCellular

network

Fixed

network

To MV grid

Cellular

network

Fixed or cellular

network

Ag

gre

ga

ted

me

teri

ng

da

taWind turbines

Figure 3: Advanced Smart Meter Reading and Customer Energy Management System Scenario

AMR is often referred as the key application for enabling a Smart Grid. Basically, AMR represent

different approaches for automatically collecting energy consumption data from electric, gas, water

and heating metering devices and transmitting these data to the meter reading operator for billing

and accounting. This information enables the energy utilities for an accurate meter reading and a

detailed forecast of the predicted energy consumption. Since several years AMR systems are already

deployed mainly for industrial and commercial customers, based upon an integrative approach by

combing the actual metering components and a WAN interface for remote meter reading. Due to the

European Mandate M/441, a monthly billing for the customer and a roll-out of Smart Meters in 80%

of all European households until 2020 is targeted, which requires cost-efficient, modular concepts for

the comprehensive deployment of Smart Metering devices considering a variety of application

scenarios. Due to different technology life cycles for energy components and ICT components a

modular system is targeted in most of the approaches. Usually a Metering HAN Gateway collects and

stores metering data from several metering devices, like electricity, gas, water and heating meters

connected by short range radio, e.g. ZigBee or Wireless M-Bus. The collected data is bundled and

securely transmitted to the meter reading operator by different access technologies, based on

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wireless, wired or PLC technologies. Moreover, a local feedback system gives the prosumer

transparent insight into his current energy consumption. In conjunction with available tariff

information, motivation for reducing overall power consumption can be achieved.

Additionally to the basic functionality of the AMR deployment, a more balanced usage of volatile

renewable energy sources (RES) and shift-able and controllable load system (CLS) in the distribution

grids is achievable by an active integration of the components on the customer side. In this context,

several customer energy management systems (CEMS) are presented, like locally managed and self-

sustaining Micro Grids, virtual power plants and centralized load coordination like DSM or DER based

on dynamic energy prices. All approaches focus on the bidirectional integration of DER and

prosumers (producers and consumers) from both power and communication engineering's point of

view. This includes volatile RES such as wind farms and photovoltaic systems, as well as energy-aware

households, which are enabled by AMR to get a detailed forecast of the energy demand and

additional transparency in energy consumption on the customer side. Moreover, based on CLS and

DG through Combined Heat and Power (CHP) generation, micro-turbines and intelligent photovoltaic

(PV) panels, the ability to balance load peaks and valleys is given. These approaches require, because

of the distributed installations and small shift-able load potential, an aggregation of multiple DER.

Through concepts such as VPP, microgrids and energy hubs, different components are combined

using various networking concepts into a logical, partly independent group (e.g. isolated networks).

At this point, the seamless integration, reliable and near real-time connectivity within the households

by an Energy Management Gateway (EMG) and a CEMS, which is required for DER and DSM at the

customers side, are key capabilities of reliable power distribution grids.

All in-house components assume to be connected via a CEMS, which can be realized by a dedicated

wired or wireless home automation system (e.g. narrowband PLC, broadband PLC, BUS systems,

ZigBee, W-MBus, etc.) or a shared medium provided by the customers in-house networks (e.g.

wireless LAN, broadband PLC, etc.). At least one access technology (at least cellular networks), but

potentially more communication means, depending on the existing possibilities, e.g. power line, 3G

or fiber (if already installed in the household) and operators, may differ between households. Faults,

of different varieties, that might occur in context of this Use Case are addressed by Chapter 4.3 of

this deliverable.

2.4 Electrical Vehicle Charging in Low Voltage Grids

This use case describes the charging of electrical vehicles in a low voltage grid considering both public

as well as private charging (Figure 4). The overall objectives of the use case are to provide EV

charging service by:

• Satisfying the charging demands of arriving EVs in such a way that the charging load is distributed

according to the resource capacities in time and space (geographical routing for public charging).

• Enabling electrical vehicle to charge flexibly, a feature that can be used by the local DSO to manage

power quality control in the LV grid along with decentralized PV production as well as other loads

(e.g. households), and by the EV aggregator to handle on the energy market.

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• Providing a system architecture that enables interoperation between new actors such as charging

station operator, the EV routing service provider, the EV aggregator, and existing actors such as DSOs

and energy market.

• Enabling the DSOs to monitor the state of low voltage grid under EV load conditions.

The EV charging scenarios described in this document cover the pre-charging scenario (not in detail)

and the smart charging scenario (similar to CG-CG/M490 document, scenario WGSP-1300). The pre-

charging interactions occur before arrival at the charging spot. The interaction of the EV with the

Charging Station Operator (CSO) (mediated by a routing service) leads to a reservation and the

allocation of a charging spot (CS), as well as the communication of desired charging demand, arrival

time, leave time, etc. from the EV to the CSO. The CSO can already create a plan. Also without the

pre-charge phase, the smart charging scenario is possible: the EV arrives at a free CS and requests

the CSO to charge, while providing following data: arrival time (now), estimated departure time,

minimum required amount of energy, maximum required amount of energy (to fill the battery),

preferred charging speed (sub-scenario PS2). The CSO creates a schedule, based on up-to-date

information: a) from the DSO about the charging capacity at that certain grid bus (available power),

b) energy bought optimally on the market, following the offered (flexible) demand.

The use case also considers how the DSO can supervise the Low Voltage grid to observe potential

power quality issues. The tool for the DSO to ensure power quality is a low voltage grid controller at

the secondary sub-station providing the available power limitations and flexibility demands to the

charging services. The low voltage grid controller utilizes the flexibility in conjunction with local

power resources (battery and production) to actively control power quality.

A regional EV aggregator (or energy supplier) interacts with the market (retail and spot) and buys the

EV charging energy according to the demand predicted by the charging stations. This demand is

expressed specifying also the flexibility of the consumption, for which the charging station is

rewarded. The aggregated requested EV demand cannot exceed the LV grid capacity (expressed by

the available power).

Specific for SmartC2Net are the following communication failure sub-scenarios: in the first the

communication channel from DSO to CSO for updating the available power is interrupted, implying a

reduction of the charging duration or the intensity of all current operations, and in latter the

metering data flow used for estimating the available power from the consumption and generation

forecasts is disrupted. Due to this uncertainty, the calculated available power could be reduced for

safe operation.

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Charging Spot

Charging station

Operator(Controller)

Charging stationRouting

Meter

LVGrid Controller

EVAggregator

LVNetwork

internet

Control

MeterAggregation

Market

MeterNetwork

MVGridController

Load

prediction

Available

power

Network

Sell

Flexibilitybuy energy

reservations

availability

buy energy

query & reserve

plugin/ leave

BatteryPV

Inverter

Meter Meter

control

Figure 4 Overview of the EV Use Case

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3 The business drivers

Drawing the attention towards economic and business drivers motivating a transition towards smart

grids, the present Section will investigate drivers facilitating the decision towards investments over

classical grids, and will further highlight business requirements providing useful feedback to the

technical realization, e.g. in respect to mitigating complexity or security threat disbenefits.

Originating from a value network representation (representing inter-firm business relationships) of

classical grids, the new value streams (in terms of monetary, resource, or other value exchanges) of

smart grids may substantially be different. Thus, creating a sufficient understanding of the business

change from “classical” electrical grids to smarter grids is necessary in order to examine business

advantages, i.e. drivers, arguing for the required transition. The necessity for investigating business

requirements may in addition be argued twofold: on the one hand the full exploitation of business

drivers may deserve the satisfaction of certain technical conditions (i.e. hygiene factors). On the

other hand, opposed to benefits of smart grids (business drivers), there may also arise costs (OPEX

and CAPEX) to be mitigated in order to render an attractive business environment.

The remainder of this section is structured as follows: Building on a common Value Network basis for

“classical” electrical grids and smart grids annexed in Section 9 (including entity (actor role) and

important value stream descriptions), business drivers are formed in Section 3.1. These business

drivers analyses will be conducted on a use case basis following a template proposal.

Correspondingly in Section 3.1.3.4 business requirements are collected and described from a

business driver point of view.

3.1 Business Drivers

This section aims at providing an analysis template for business drivers being applied to each of the

scenarios. We will first introduce a series of relevant business driver categories, which will be

instantiated for individual use cases.

3.1.1 Telco Sector

Before defining an appropriate template for the analysis of business drivers, we briefly discuss the

telco sector role in the smart grid context in order to capture business motivators in the energy

sector. The telco sector is of special interest for this investigation, as it complements the classical

energy sector roles in new smart grid business models and has not yet settled. The outcome will later

on be considered in the definition and application of the template.

There are several definitions of smart grid, but regardless of these definitions, the main characteristic

of the smart grids is the introduction and application of communications and information technology

in power grids. This will lead also to an increased usage of communication services, provided by Telco

operator, to cover the needs of the utility companies. Suitable communication technologies provided

by telco can be wireless or wireline, the first one mainly used in neighbourhood area network for

smart meter communication infrastructure because of easier and less expensive deployment, while

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the backhaul network to connect the smart meter head-end and the data aggregation points can

either be wireless or wired. Hereafter, we will focus on scenarios where connectivity is provided by

cellular technologies through M2M services because, although this technology introduces some

drawbacks, w.r.t. other wireless technologies it appears to provides the best answer in terms of

technical characteristics (coverage range, latency and reliability) at the lower cost and ease of

deployment [EEE12ZZ]. Regarding wired network and its adoption opportunities for smart grid, while

it has and will continue to have a place in utility market applications, several reports [NTS12 and

INT12] indicate a shift towards wireless technologies mainly driven by costs, difficult installations and

copper theft.

These scenarios foresee that the number of M2M device connections in the energy/utility sector will

grow from 22.1 million worldwide in 2011 to 1.3 billion in 2021. The CAGR (Compound Annual

Growth Rate) will be 50% during the 11-year period. Smart metering will be one of the fastest-

growing segments of the M2M ecosystem in terms of device connections during the next 8 years

[ANME12].

Figure 5 M2M device connections, energy and utility sector, worldwide, 2011–2021 [ANME12]

According to [ANME12], the growth in the sector is spurred by energy/utility companies’ need to:

respond to regulatory and legislative changes

access more granular demand- and supply-side data in near real time

constrain capital and operating costs

increase service offerings.

Limiting analysis to smart metering, [ANME12] list the following factors driving the adoption of M2M

based services within the energy/utility sector:

Reducing operating costs and increasing margins. Operators in the energy sector, including energy producers and distributors, are looking at ways to reduce costs. M2M devices help

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these businesses to improve processes such as meter reading, supply management and fraud prevention. As an example, better near-real-time management of electricity supplies can significantly reduce the cost of total energy production.

Providing accurate and timely data. M2M solutions are a way to remove human intervention from collecting data and making decisions, which will reduce costs [ANME12] and will help enterprises make better decisions more quickly by providing employees access to relevant business data in real time or near real time.

New revenue streams or product differentiation. M2M solutions allow energy companies to offer new services to consumers and other businesses. These new services might result in additional revenue streams or increased differentiation for manufacturers. Examples include home energy management, and residential and commercial security/surveillance solutions.

Renewed interest in connectivity due to Regulatory action and need to constrain costs. Building new-generation facilities is extremely complex and often politically difficult. Connectivity embedded in smart meters, homes and businesses helps the energy/utility sector minimise the need to build new-generation facilities and maximise customer satisfaction.

On the other hand the complexity of the M2M supply chain can inhibit the adoption of M2M

solutions in the energy sector. With M2M implementations frequently custom-designed, the overall

return on investment (RoI) of the solution is generally lower than that of other IT solutions.

Moreover government policy and regulation could have a deep impact on M2M adoption in energy

sector, depending on the commitment shown by governments and regulatory bodies for keeping

utility prices affordable, matching supply and demand, and encouraging energy conservation.

Connectivity represents almost 90% of M2M for CSP (role details see Section 9) revenue in the current market, but most of reports indicate that within three years M2M connectivity revenues will continue to grow, but new revenue streams will increase their importance for a sustainable profitability [INFO12]:

Connectivity (Communications services, associated communications hardware)

Professional services (Consulting, integration, software development)

Service level management (Security, demand response, performance management)

Business intelligence (Decision support, reports and alerts, analytics)

The same shift will apply also to business models and role that CSPs will play:

Today most CSPs function as M2M data wholesalers,

only one in every 10 CSPs actively runs revenue-sharing models with partners.

Fewer than one in 10 routinely offers service-level or application-based pricing for M2M. M2M stakeholders can agree that table stakes for market success are end-to-end service management and flexible billing for varied M2M applications and traffic profiles. Beyond these two priorities, however, for smart grids scenarios security and securing data delivery according to end customers’ service-level requirements is another priority to ensure. Conflicts Besides, the market data anticipating the raise of the M2M market and the interleaving of telco and energy sectors, the particular roles have not been settled. Energy companies may cooperate with

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telcos as “friends”/”partners” or may on the other hand exclude them from the smart grid business [ADL12], i.e., competitors. Generally, different entities may have different visions, expectations, and driving interests in the

raise of smart grids [ScTa12]. Communication services may in practice be provided by telcos, but also

by DSOs themselves. Fearing the disadvantages of being locked in by one or more telcos (high or

rising prices, know-how transfer [ADL12]), the classical top-down energy sector approach with full

control over the whole value chain may be preferred by DSOs. However, cost advantages through

synergies (“joint customer base and sales channels”, shared investment costs, etc. [ADL12]) for both

DSOs and telcos thus could not be utilized. [ADL12] recommends that energy providers carefully

consider their strategic positioning with respect to cooperation and competition alternatives for

communication services. Besides that, even telcos could become a competitor in the energy sector,

which may assist the finding of a cooperative equilibrium at the end.

Thus, we argue that conflicting business drivers may only be resolved at mutually beneficial

configurations, i.e. a stable equilibrium. We suggest designing scenarios facilitating high control for

DSOs, high cost synergies for DSOs and telcos, and adequate business involvement of dedicated

CSPs. This could for example be realized on top of full-Mobile Virtual Network Operator (MVNO)1

agreements between a trusted CSP and a DSO, which provides the following flexibilities to DSOs:

Possibility to replace telco provider by a competitor (some contractual limitations), if service or price

levels do not meet expectations

Complementation with own telco equipment possible (i.e., control over critical elements could be established)

Dedicated resources could be assigned to DSOs, which could substantially increase the control over the communication network (if technically enabled)

Besides synergies with the CSP, own investments could be made up by selling remaining resources to external customers, i.e., entering the “classical” telco business as MVNO

Besides that scenario, also regulatory measures could enforce a more direct cooperation, e.g. by

increasing the cost pressure on DSOs and CSPs, thus requiring the consideration of more synergies in

smart grids investment and operation.

3.1.2 Categories

Each listed category represents a specific area of concern that can be extended individually. These

categories extend the considerations of [EPRI10] and are presented here with a short description

listing high-level examples of more specific concerns. Not all categories may apply to each scenario.

1 http://www.nereoconsulting.com/pdf/SmartGridandMVNOs.pdf

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Figure 6 – A categorisation of generic business drivers

As illustrated in Figure 6, two main categories interrelating with most others are cost reductions and

revenue growth. The details are provided in the tables below.

Category Description & Means of Realization

(Here we describe by which means the area of concern can be addressed)

Costs Reductions Cooperation & Incentives: Improved cooperation with customers and suppliers

(business partners) is a significant source of cost reduction. In particular,

incentives for adequate supply/demand patterns may be used in order to

eliminate inefficiencies or even lead to customers/suppliers looking for

alternative business partners.

Entities: DSOs cooperating with energy generators and consumers on

adequate generation & demand levels; Retailers need to be incentivized to

reserve sufficient energy in advance; better integration of heavy users such as

charging stations in the grid stability picture

Increased Reliability: Improving reliability of service may bring a variety of

benefits also affecting cost levels. In the operative business, the compensation

payments (e.g. to business customers/partners) or even loss of customers may

be avoided. Cost advantages may be yielded by reductions of maintenance

costs (e.g. energy loss reduction primarily on MV level). In addition, further

aspects of product satisfaction or product attribute satisfaction like

convenience and quality may also affect customer satisfaction figures.

Entities: DSOs, CAMs (role details see Section 9), and also energy consumers

Wholesale energy trading efficiency: By an increased understanding of arising

supply and demand levels, utilisations can be attempted at the wholesale

market. In particular, unnecessary options deals may be avoided (or

downsized) or replaced by very dedicate futures purchases. This may on the

one hand save option fees and may on the other hand increase the supplies on

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the market.

Entities: Esp. CAMs and DSOs (more efficient trading due to better metering

information and thus forecasting)

Resource usage efficiency: The usage efficiency of invested resources, esp. by

smart control of renewable energy generation/use, may be improved. Thus,

fewer resources are used and less energy needs to be wasted.

Entities: Regulatory (may enforce efficient usage), energy generators

(reduced costs due to fewer raw material inputs), DSOs and CAMs (higher

stability due to reduced danger of shortages), energy consumer (“greener”

energy provisioned)

Claim management: Reduction of claims means a reduction of costs. Claims

could be a perceptually unreasonably/surprisingly highly energy bill (being

provided only on a e.g. yearly basis) or product dissatisfaction (i.e., outages).

Both types of claims may be targeted by smart grids where consumption

figures could be shared more regularly and outages (in increasingly more

difficult environments) are aimed at being further reduced in probability. This

factor also interrelates with customer satisfaction & loyalty, as well as with risk

management subcategories.

Please take note that the introduction of new technologies such as smart

meters may also require some claim handling in the transition phase. Thus,

ease of use for end customers is important – see business requirements.

Entities: Retailers and DSOs

Revenue Growth New Sources of Revenue: Newly designed information services may provide

added value to the customers leading to new sources of revenue. On the other

hand, the improved understanding may enable the provisioning of further

flexibility services, i.e., bearing risks of others etc. Finally, new/occasional

service offers could be provided, which could help utilizing fallow energy

resources, e.g., AC in public transport being automatically switched on

whenever there is no supply scarcity. (Please also take note that the utilization

of improved knowledge about customers and their consumption behaviour

may represent very valuable information e.g. for the advertisement industry)

Entities: Com. Service Providers (M2M services), DSOs/Retailers (dynamic

pricing), EV Charging Station Operators (satisfaction of more customer

requests), DERs (more DERs can be integrated in the grid), Vendors (new

equipment sold for metering or communication services)

Differentiation of existing services: Service differentiation, e.g. dynamic pricing

of energy at different times, may also allow energy providers to more

efficiently charge dynamically arising peaks. This may on the one hand

stimulate cooperation with business partners, and on the other hand generate

additional revenues beyond acting on the wholesale markets.

Entities: Retailers but also DSOs (and transitively CAMs)

Customer basis growth (existing resources): Due to a better forecasting of

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demand, as well as the shaping of actual demand and supply, supply levels may

be further exhausted by increasing the demand (new customers), trading of

resources (options, futures), etc.

Entities: Retailers and DSOs

The other categories are listed subsequently:


Risk Management

Efficiency

Risks are generally a considerable threat for business prospects. In smart grids,

this in particular complies with the risk management of energy and ICT

resources. At all the time it has to be ensured that sufficient supply matching

the demand is present.

Hedging: risk of investment (too low demand) hedged against put options or

risk of too low supplies hedged by call options on the wholesale market.

Reduction: Risks may be reduced e.g. by an improved understanding of

demand and supply patterns.

Sharing / Insurance: One may insure against energy (demand/supply)

fluctuations, e.g., by buying insurances. Insurances may cover monetary losses

or more realistically the bearing of the risk of ad-hoc energy demands, i.e.,

options or futures. A better understanding of available risks may lead to a

proper dimensioning insurances / risk sharing mechanisms. Risks may also be

shared among entities besides hedging mechanisms discussed above.

Entities: Mainly CAM, but also retailers and DSOs will have more

responsibilities regarding balancing the grid

Marketing &

Societal Benefits

The shift towards smart grids may be used for emphasizing the ecological

responsibility of firms (e.g. more renewables can be integrated). Especially in

the relationship with end customers, this may be a very important factor for

motivating such investments.

Smarter energy grids may provide better statistics allowing fine-granular

supply and demand analysis, customer inspection/relationship etc. This may be

seen as platform for doing business intelligence (knowing the customer base

for adjusting advertisements, product offers, etc.) as well as for the generation

of figures being used for PR purposes (e.g., consumption figures, saved energy,

reliability, etc.)

The reduction of greenhouse emissions, i.e. CO2, also poses benefits to the

society, i.e., lowered negative externalities (also see [EPRI10]). Thus, beyond

the direct business utilization, the society profits (also see regulation).

Entities: Retailers and DSOs, society

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Infrastructure

Efficiency

Delaying investments: the better understanding and proper utilisation of

existing infrastructure may allow the delaying of investments in future

upgrades. This may substantially affect the incurred costs, and may thus be

among the central drivers.

Infrastructure efficiency highly depends on the peculiarities of geographical

areas. Frequently most connection requests of renewable generation resources

come from rural areas where the grid hosting capacity and the communication

service availability are lower. On the other hands, the connection of flexible

loads (medium size prosumers and EV charging) is more relevant in urban areas

characterised by more reliable and oversized grid capacity.

(High precision) quality & energy demand/supply statistics: Improved

durability and quality statistics of deployed components may provide even

better selection of future devices

Entities: Mainly DSOs

Customer

Satisfaction &

Loyalty

Loyalty may be increased on two main axes, i.e., whitewashing customer

service, price or quality (reliability or information services), and obligations

(lock-in effects, long-term contracts). Endogenous whitewashing may occur

when intensified relationships with retailers or DSOs may automatically be

blandished by customers. Exogenously, whitewashing may be triggered by

dedicated advertisements & communication with the customers based on high

precision figures.

The customer satisfaction may be subject to economic aspects (is the price too

high? does the pricing scheme fit the needs?), self-control aspects

(consumption metering interrelated with current price), ecological aspects

(saving energy, green energy), (perceived) reliability, new information services

(where can I charge my car?), and trust (in energy grids, services etc.). By

allowing a more transparent communication with the customer a broad

majority of these factors could be addressed. The additionally provided new

capabilities enabling (dynamic) pricing and increasing reliability may further

contribute to suitable customer satisfaction levels.

Beyond that, customers may also profit from lower electricity prices, if smart

grids enable the more cost efficient integration of renewables.

Entities: Mainly retailers, consumers

Regulation &

Legislation

Smart grid investments and operation may be enforced and regulated by

official bodies or laws. Entities may in particular face the regulatory

enforcement of accommodation for broader scale renewable rollouts paired

with a required maintenance of adequate stability and power quality in the

grid. Thus, the retention of the current business model may require certain

technological and/or business process adaption to changing legal frameworks.

Entities: DSOs, CAMs and partially retailers and larger consumer/resellers like

EV CSOs, society (lowered greenhouse emissions).

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Together with further factors like Risk Management Efficiency and Infrastructure Efficiency the cost

related factors represent an economic dimension comparable to [EPRI10]. Additionally, the Marketing

& Societal Benefits extend the understanding of “Environmental” benefits as captured in [EPRI10].

Customer Satisfaction & Loyalty covers and extends “Reliability” advantages linked to smart grids. On

the other hand, “Security & Safety” aspects are interpreted as business requirements (see later), as

the raising complexity of smart grids require proper countermeasures itself on this axis.

3.1.3 Use cases

Based on the above-presented template, each SmartC2Net use case is analysed on a fine-granular

level. By picking relevant categories from the template, specific business drivers will be discussed,

e.g. smart grids may facilitate charging of more cars a day (revenue opportunity). On the other hand,

less relevant categories for specific use cases are completely omitted in the analysis. We will

additionally address conflicting business driver and related business conflicts per use case, e.g., DAC1

introduces a Business Driver conflict of the AMR/CEMS use case.

All use cases share the following high-level business drivers:

Risk Management Efficiency:

Due to improved metering, risk management can be further professionalized by receiving

better load forecasts, which lead to improved contractual agreements, i.e., insurances or risk

hedging agreements. These factors are typically immediately revenue-effective.

Marketing Benefits:

Improved argumentation towards society to better accommodation for renewables in the

grid, and thus probably raising share of “green” sources of energy

On a high-level, [EPRI10] suggests the following general and rather energy-sector-centric benefits per

actor group:

Energy sector: Reduced operation and maintenance costs, deferred capital costs, etc.

Consumer: Reduction of electricity costs and disbenefits from power interruptions (or

“power quality events”)2.

Society: Reduction of negative externalities

These generic drivers are subsequently extended by use-case specific details.

3.1.3.1 Voltage Control in MV grids

Business Driver Instantiation Conflicts

Costs

Reductions

The Voltage Control use case is mainly driven by cost considerations:

Improved cooperation between DSO and DER owners is a

significant source of DSO cost reduction

DVC1

2 These advantages may be seen in direct comparison to cases of extensive renwable rollouts without

smart grid assistance

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Minimised technical energy losses

Improving reliability, voltage stability and power quality of the

power supply service may bring cost cost benefits

Decreased outages means reduction in maintenance and claim

management costs

Optimised voltage profile reduces OLTC and DER costs of

operation

Ability to integrate more DERs may reduce pressure to act on

wholesale markets and thus may reduce costs

SmartC2Net may help DSOs to comply to the contracted terms

with TSOs and thus may be reduce costs inferred due to grid

instabilities (reliability issues) and/or charges (due to TSOs

having to act on the wholesale markets) – see risk

management

Entities: Mainly TSO, DSO cooperating with DER owners (generation

plants and medium size prosumers) on adequate generation &

demand levels

Revenue

Growth

The connection of DERs may enable the satisfaction of higher demand

levels, thus leading to potential electrification of new services. Thus,

this extending the grid business through higher demand levels. It also

requires extended communication services.

Entities: DSOs, CSPs

Risk

Management

Efficiency

Related to cost motivations, also risk management becomes of

interest:

Risks of over/under voltages may be reduced by relying on a

more precise grid monitoring, actors’ communications and

optimized set points

Specific focus on cyber security as a means of increasing the

efficiency of the cyber-physical risk management

Entities: TSO, DSOs, DER owners

(also see general drivers above)

Marketing (see general drivers above)

Infrastructure

Efficiency

The connection of DERs will allow to optimise the DSO infrastructure

efficiency in those geographical areas where grid overcapacity is

available – thus helping to delay investments in infrastructure upgrade

through more efficient usage.

Entities: DSOs

Customer

Satisfaction &

Loyalty

The increased acceptance rate of connection requests of DER to the

grid increases the customer satisfaction level, i.e. prosumer acceptance

Entities: DER owners (prosumers)

Regulation &

Legislation

DER connections to the grid have to guarantee compliance with

country-specific regulations reflecting the adopted business model and

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the grid code. DSO and DER owners need to meet revised regulations

requiring a shift to smarter grids, e.g. according to the new regulation

it is necessary that all active customers are endowed with a

communication system allowing the (real time) data exchange with the

DSO. This will allow the DSO to implement optimization logics and to

send all customers the signals implementing the actions (e.g.

disconnection) needed to guarantee the security of the whole power

system.

Entities: DSOs, DER owners, Regulators

DVC1: DSO operation constraints may decrease DER owners’ revenue.

3.1.3.2 EV Charging

The EV use case in particular targets the advancements over EV charging realisation on top of

classical grids. Explicitly, telecommunications, and as an effect of that, the solutions required in

SmartC2Net, are a result of the distributed character of the EV charging sub-system. Creating

decentralized decision support both at the LV grid, and at the charging station level has the following

advantages:


Costs

Reductions

No alarms are issued and power line enhancement costs are

deferred.

Grid operators may profit from overload avoidance in the LV

grid (due to charging station congestion) and in turn deferred

grid enhancements costs

Better estimates of demand due to smarter reservations may

lead to more efficient wholesale trading (lower overcapacity

and fewer intra-day trades, as well as improved risk

management)

Smaller dimensioning of charging stations may potentially also

result from load distribution optimizations

Entities: EV CS operators, DSOs, and CAMs (EV users may also profit

from lower prices)

DEV1

DEV3

Revenue

Growth

Due to optimized scheduling, the installed power and the

dynamic calculated available power is maximally utilized

On a high level, new revenue opportunities could be exploited

by e.g. renters/operators of parking lots or store operators that

may further provide charging opportunities in order to

differentiate over competitors or even directly increase their

revenues.

DEV1

DEV2

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Each charging station may also profit from an optimized

utilization of their charging capabilities by an improved

steering of customers to available resources (parking lots and

energy).

Due to the flexibility of the demand and of energy price

information, charging station operators can increase profits or

increase competitiveness by lowering their service prices

towards the customer

New information services may be realized on top of a more

capable smart grid platform

Entities: EV CS operators, InfSPs (e.g., E-Mobility Service Operator),

DSOs/retailers (selling all available energy), Com. Network Providers

(M2M services e.g. for charging stations and grid or connectivity in

cars)

Risk

Management

Efficiency

(see general drivers above)

Marketing In addition, the SmartC2Net grid may enable the broader role out of

EV charging stations and a broader coverage of charging demands due

to optimized balancing the grid. Thus, besides investment cost

reductions, CO2 reduction due to the transition from fuel-powered

cars may provide positive incentives.

Entities: Society, regulators, energy consumers, but also DSOs and

retailers may profit


Infrastructure

Efficiency

----------

Customer

Satisfaction &

Loyalty

Transparency by offering to broker between customers and

any supplier of charging services which best satisfies the

requirements of users (near to destination, price, availability of

resources, charging speed, energy mix, discount (loyalty

programs) (communications needed).

New information services such as the reservation of charging

resources before or during the trip (communication is needed)

while at the same time reserving a parking lot

No waiting times due optimal steering of customer flows

Decentralized operation of charging stations makes them less

vulnerable to single point failures of a central charging service,

i.e., higher reliability

Thus, positively attributing to the perceived convenience/quality and

reliability of using the EV charging service. The increased satisfaction

may also help to blandish price figures.

DEV2

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Entities: Mainly EV CS operators, DSOs and retailers (transitively also

EV users / energy consumers)

Regulation &

Legislation

Government incentives seem to expedite the broader usage of EV,

which thus drives the necessity for finding solutions to charge more

cars. Thus, by upgrades to smarter grids proactively regulatory or

legislator intervention may be avoided.

Entities: DSOs and CAMs

DEV3

DEV1: Customers may want to participate in cost reduction prospects, which may mitigate revenue

prospects through new services and more EV charging

DEV2: Customers may be reluctant to switch to other CSs without a monetary incentive or clearly

communicated benefits, otherwise customer satisfaction may not increase or may even be lowered.

DEV3: The political impetus for pushing EVs may entail the requirement for investing in smart grids

or antedating investments in smart grids, which may not be aligned to the plans of the energy sector

entities (in terms of costs etc.).

3.1.3.3 External Generation Site


Costs

Reductions

Reduction of claim management by avoidance of disconnection

of customers, and increased penetration of renewable energy

sources by maintained voltage profile on LV feeders

Minimize losses in MV grids while increasing the penetration of

renewable energy sources e.g. wind and PV in MV and LV grids

(we also kindly refer to Section 4.2).

Increase wholesale trading efficiency

Increase resource usage efficiency

Increase reliability of MV/LV grids

Entities: DSOs, Retailers, Consumers, Prosumers,

micro/intermediate/large DER, Network Owners/Providers

Revenue

Growth

New Sources of Revenue for prosumers,

micro/intermediate/large DER by providing ancillary services3

Service differentiations of existing/new services

New connectivity for smart grid actors provided by CSPs, e.g.,

by utilizing the network for providing tailored M2M services

and/or QoS-differentiated services

Entities: DSOs, Retailers, Consumers, Prosumers,

micro/intermediate/large DER, Network Owners/Providers

Risk

Management


3 Paid services on top of energy generation such as voltage control or reactive power support, which

form a new type of business (business model) due to decommssing of large power plants. Thus, such services may gain in importance.

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Efficiency

Marketing Capability to integrate more renewables in MV/LV grids – in

particular the case of renewable energy sources i.e. wind and

PV, is studied in this use case.

Entities: retailers and DSOs, prosumers


Infrastructure

Efficiency

Reduce the need for grid reinforcement by better utilization of

existing grid

Entities: DSOs

Customer

Satisfaction &

Loyalty

Increase loyalty and satisfaction of end-users by increased

reliable power supply with renewable energy resources

Entities: Consumers, Prosumers, micro/intermediate/large DER

Regulation &

Legislation

New regulation and legislation for prosumers and their

interaction with the grid

Requirements regarding the interfacing between prosumers

and the system

Entities: Consumers, Prosumers, micro/intermediate/large DER

3.1.3.4 AMR/CEMS


Costs

Reductions

Enhance grid status information exchange below substations, which may raise the reliability of the grid, and thus may reduce costs

Peak shaving → Shift of demand at times where energy is available (reliability and thus cost effective; reduction in wholesale trading; reduction of required investment costs, etc.)

Minimize non-technical energy losses (illegal, unbilled energy consumption; also see paragraph on revenue)

Entities: Mainly DSO

Revenue

Growth

Minimize non-technical energy losses (illegal, unbilled energy consumption) → new fees are received

Com. Service Providers may profit from selling connectivity services for AMR/CEMS, while relying on infrastructure required for CPE connectivity, i.e., connectivity service bundles providing a new source of revenue with potentially limited investments required.

Entities: Mainly DSO and Com. Network Providers

DAC1

Risk

Management

Efficiency


Marketing (see general drivers above)

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Infrastructure

Efficiency

Demand-response may delay infrastructure investments (e.g.

cables)

Customer

Satisfaction &

Loyalty

More frequent / more transparent feedback on consumption

and prices

Supporting customers in order to save energy and/or costs

Feedback mechanisms and home integration may blandish

price disadvantages

Yearly metering models may lead to imbalances of

consumption period and assigned prices, e.g., lower than

expected consumption in winter but higher in summer, as well

as to compensation payments at the end of the year (metering

and payment intervals may not be aligned), which can be

eliminated/mitigated with AMR/CEMS (customer interest &

satisfaction due to transparency and self-control capabilities). Entities: Mainly DSO and retailer may profit from increased

satisfaction (besides customers)

DAC2

Regulation &

Legislation

Regulators may enforce the deployment of smart meters, as practice in

Germany for example, and may also enforce load-dependent tariffing

schemes in order to promote energy saving behaviours of customers.

DAC1: Customer incentives may conflict with CSP’s revenue prospects, and thus need a proper alignment. DAC2: Customer satisfaction increase through improved consumption figures may not compensate required investments in smart grids and especially smart meters. Thus, this may have to be financed by other smart grid actors, probably DSOs. The discussed use case-specific business drivers are viewed as the motivators for the investigation of subsequent technical solution. Later on these drivers may serve as crosschecking or validation tool for evaluating how the architectural realization, i.e., the SmartC2Net solutions, support the realization of listed business drivers. This analysis has also illustrated the requirement for differentiating in particular smart grid services to be considered, as their driving forces may differ in their characteristic.

3.2 Business Requirements

Building on the description of business drivers, the present section investigates business

requirements – potentially providing implications on technical requirements – originating from a

business context. Thus, this section correspondingly provides use-case specific investigations on

technical properties that may be required to satisfy business needs. Such needs are caused by

business drivers for smart grids, or are dedicated to mitigate negative side effects (such as high

investment or operation costs of smart grids).

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3.2.1 Telco and energy sector interplay

A central requirement for the transition towards smart grids is the proper alignment of telco and

energy sector business objectives. Thus, this will be briefly discussed in this subsection and finally

provide implications on the business requirements template.

While DSOs may want to keep outmost control over their distribution network (including

communication services), CSPs are looking for a business case and may be able to utilize cost

synergies through the reuse of existing infrastructure. Thus, a fruitful cooperation implies the

following business requirements (also see dedicated business drivers section), which may, amongst

other technical solutions, be targeted by smart MVNO agreements:

Straightforward replicability of CSPs

DSOs’ possibility to deploy own communication infrastructure at critical locations

Cost efficient integration of DSO communication infrastructure with CSP infrastructure

Quality assurance, e.g., dedicated resources, access control, prioritization or other smart QoS

techniques

Efficient reuse of existing resources (e.g., MPLS rather than leased lines/own spectrum;

dynamic adaption to energy sector)

3.2.2 Template

The applicable categories for factors triggering business requirements specification are summarized

in Figure 7.

Figure 7 – A categorisation of business requirements

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Information Sharing

(Frequency, data sets

& access,

communication links)

Information Sharing: Requirements of communication links towards external

or internal business partners and/or between internal systems/departments.

Not only the frequency of data exchange is of high relevance, but also the

amount of data being required to be exchanged. Generally, we assume that

only the minimal set of data will be shared with business partners in order to

assure a proper functioning of the smart grid. Different data exchange and

access rules may apply to smart grid entities and (external) Information

Service Providers. Specifically of interest is the exchange between DSOs and

CSPs regarding current/expected performance and capabilities of the

network as well as the information dissemination of the grid status.

Another special case refers to the integration of Information Service

Providers building added value on top of smart grid interfaces. Information

services here refer to internally or externally provided added value services

(partially) utilizing information gathered or circulated in smart grids.

Data access: While the access of data needs to be restricted mainly

for security reasons (see dedicated category), the defined level of

data utilization may be subject to different degrees of market

openness: in order to allow the access of third party actors –

facilitating competition on information services – segmentation of

exchanged data would be useful (different information sets being

shared with different entities on different levels of aggregation)

Trust relationship: There must be a trust relationship between

partners accessing the data, data providers, and customers (trusting

in the proper handling of their data). Unreliable partners need to be

removed, and the data access design should limit the required trust

level as much as possible.

Entities: All actors, esp. Information Service Providers, E-Mobility Service

Operators, Com. Service Providers, and DSOs.

Investment

Efficiency

Investments in smart grids (and individual systems or components) should be

kept as low as technical feasible. Thus, cost efficiency is required in order to

manage a successful transition towards smarter grids.

Entities: Esp. DSOs but also Com. Service Providers (w.r.t. revenue

prospects)

Efficiency of

Interaction

Market or system interactions or price adjustments may be subject to

different timescales. Thus, economic requirements for maximum timescales

or granularities may exist (in respect to dynamic pricing).

System/Market Interactions: The granularity of interactions between

systems or market places may be subject to service/use case requirements or

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customer demands, which may substantially influence the practical

realization of use cases.

Entities: Retailer (on wholesale market), CAM (on wholesale market and

with retailer), and esp. DSO (with generators, consumers, and CAM w.r.t

metering information exchange)

Possibility of (dynamic) pricing / service differentiation: The requirement of

allowing (dynamic) pricing (or comparable differentiation of existing services)

of particular resources

Entities: DSO (in cooperation with retailers)

Flexibility of

Deployment (e.g.

plug & play)

Limited effort: The transition to smart grids should be accompanied

by limited deployment or behavioural adaption efforts

Plug & Play: The reduction of deployment complexity in terms of

required know-how is of high importance, i.e., a "plug & play"

paradigm in lieu of required individual adaptions. Also the

complexity for customers should be limited towards the transition to

smart grids in order to keep claim management efforts minimal. New

features/technical capabilities should thus optimally be self-

explanatory.

Entities: DSOs & Com. Service Providers (limited CAPEX for smart

grid investments), Information Service Providers (easy access to

data), EV Charging Station operator (w.r.t integration in smart

grids)

Environmentally

Sustainability

Energy-aware components, e.g., having the capabilities of shutdowns under

low loads, are required in order to mitigate cost increases as well as in order

to support the ecological argumentation of smart grid role outs towards

customers or the society in general.

Entities: all, but esp. DSO & Com. Service Providers

Improved Metering A key element for gathering information in smart grids is metering (on the

customer side as well as in the grid). Thus, metering information provides a

fundamental basis for business considerations or utilizations of gathered

data.

Control/Validation of business/legal agreements: A more precise validation

of business or legal agreements may be enabled

Entities: CAM, DSO and retailer

Basis for Forecasting: Currently present or historic demand / supply patterns

may be useful for forecasting subsequent deviations (especially regarding

seasonal, daytime, etc. effects)

Entities: CAM and DSO

Localization (of faults): Metering information may provide a good basis for

localizing events like faults, stressed components, deviating demand/supply

patterns etc.

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Entities: DSO

Basis for Statistics: Gathered information may be utilized for business needs.

In particular, business intelligence (classification of customers, customized

offers, etc.) and PR/Marketing (communicable figures etc.) considerations

may play a big role.

Entities: Retailer (and DSO?)

Basis for Shaping: The metering information will be useful for providing a

basis for shaping demand and supply (demand-response) via automatisms

(i.e., consumer devices adapting their energy consummation),

feedback/suggestions (e.g., alternative charging station suggestions or high

load indications), pricing, etc.

Entities: Mainly DSO

Incentivizing

Customers

Customer demands regarding the usage of service, e.g., localization of

available charging stations, have to be met in order to successfully realize

SmartC2Net use cases. These factors may be assisted by technical or

monetary incentivization of customers.

Entities: Esp. DSOs

Operational

Efficiency

Originating from key business driver, the maintenance as cost factor is a very

import prerequisite towards the transition to smart grid systems. On the one

hand, smart grids should only add limited maintenance effort to existing

grids. On the other hand, smart grids should contribute to lower

maintenance costs of classical grid components, e.g., due to faster recovery.

Reliability (outages):

o Durability of components (years): The durability of individual

components is in important factor for reducing outages, but

also reducing overall maintenance costs.

o Redundancy & Fault Tolerance: The failure of one

component should be of limited/minor effect to the overall

grid. This may be targeted by suitable degrees of redundancy

or component failure tolerance

o Quality of Network/System: Besides durability constraints,

communication network quality (or quality of other systems)

may decrease the required maintenance effort in terms of

human intervention.

o Alerts:

Component failure: Automatic and precise (e.g., in

terms of localization) notifications about component

failures should be provided

Component overload: Automatic and precise

notifications about highly stressed components may

be provided

Self-healing: Recoverable failures (e.g., software) of

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components/control system/etc. may be assisted by automatic self-

healing processes. This may essential reduce the human effort in

maintenance

Time to recover: Outages or limited service usages may be very

costly. The time to recover from failures is thus critical.

Entities: DSOs and Com. Service Providers

Information Security Confidentiality: The business information gathered or circulated in

the smart grid has to be regarded as confidential to external and/or

competing actors. Competitive information needs to be protected

throughout the smart grid.

Privacy: The customer information collected or circulated in the

smart grid has to be protected. In particular, careful handling of

information exchange with other entities is required: there should be

the capability to blur unavoidable data exchange (e.g., due to

technical or legal reasons), i.e., elimination of identities, meaningful

aggregation of information, segmentation of information sets etc.

Avoidable data exchanges (besides judicial or social restrictions)

should serve a business interest of the information contributing

party.

Information Integrity and Availability: The requirements to be able

to trust on information gathered through metering and/or

exchanged with partners or other systems, or circulated in the own

network.

Entities: All (as all are using communication services)

3.2.3 Use cases

By picking relevant categories form the above-presented template each use case is specifically and

fine-granularly addressed. Thus, the present section will provide qualitative and use-case specific

feedback towards the analysis of requirements. Additionally, we will again investigate business

conflicts associated to stated business requirements of each use case, e.g. RAC1 introduces a

Business Requirement-related conflict for the AMR/CEMS use case.

Please, note that all use cases of course immanently require cost efficiency for a successful

realization, e.g., typically combination of connectivity services for end customers (Internet access)

may be aligned to the realization of smart grids to keep costs low and/or strengthen revenue figures.

We may also state the following high-level business requirements being shared by all use cases:

Efficiency of Interaction:

Higher dynamicity of interaction, information exchange and trading:

o Grid resource trading in seconds

o Supply-demand balancing in milliseconds -> thus balancing reserves like batteries

required more intensively

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o Pricing updates in milliseconds in order to provide meaningful behavioural adaption

incentives (mechanisms avoiding oscillations in the system may be required)

More fine-granular interaction and cooperation

More fine-granular control over the distribution grid

o Incentives / compensation mechanisms (w.r.t. contracts and information exchange)

for balanced / unbalanced energy demand & supply by retailers

More systematic integration of DER supply-levels, retailer energy sales, customer behaviour

and actors balancing the grid, i.e., DSO, CAM, TSO.

Improved Metering:

More fine-granular metering capabilities

o Providing means for require fewer flexibility & reserves

o Better forecasting of demand and supply levels in order to make reservations earlier

(at a cheaper point in time)

3.2.3.1 Voltage Control in MV grids

Business

Requirements

Instantiation Conflicts

Information

Sharing

Communication links between DSO and TSO, Aggregators, InfSP, CSP,

and between DSO systems and networks (e.g. metering, SCADA and ICT

infrastructures)

Investment

Efficiency

-------------------

Efficiency of

Interaction

(see generic business requirement above)

Flexibility of

Deployment

Flexibility in implementing new DER connections is required. The role

of standards is particularly relevant

Evniron.

Sustainability

Environmental sustainability is relevant in view of energy source plans

and global economic strategies

Improved

Metering

Improved metering capabilities provide more accurate generation and

load forecasts (also see generic business requirement above)

Incentivizing

Customers

Favourable contractual conditions (e.g., electricity costs) through a

more efficient integration of DERs or tax deductions for installation

costs may support the transition towards smart grids.

Operational

Efficiency

The voltage control is tightly coupled with efficiency of operation of the

grid and its components, i.e. advanced voltage control is required

Information

Security

Availability and integrity of grid monitoring and voltage control

information flows is essential

3.2.3.2 EV Charging

Business Instantiation Conflicts

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Requirements

Information

Sharing

Information Sharing: On a high level competitive data needs to be

protected from competitors, which includes occupancy rates. On the

other hand, the privacy of end customers needs to be protected.

All involved entities inherently require communication services

for their coordination.

Direct and convenient interaction between end customers and

CSOs is required in order to find suitable charging stations in

the proximity of most customers. Thus, E-Mobility Service

Operators (or comparable information services) require access

to reliable forecasts whether a CS will be able to meet the

energy demands of a requesting EV in a certain timeframe.

However, the charging station should not directly exploit load

levels allowing a long-term monitoring of financial success.

Thus, we for example envision the following process chain

avoiding iterative requests for data collection purposes:

Car request (energy demand, area, price constraints) → E-

Mobility Service Operator one-by-one contacts CSs → positive

reply means automatic and compulsory reservation of the

energy slot (i.e., no-show fee seems to be required)

Moreover, due to the sharing of customer demand levels the

role of an Aggregated EV Charging Infrastructure Management

cannot be played by direct competitors and may only be

shared with trusted partners. We, thus, suggest linking this role

with energy aggregators or creating an Aggregated EV Charging

Infrastructure Management instance for each CS chain.

CSOs require an on request communication link towards DSOs

and their energy retailers to make sure that sufficient energy

can be distributed in order to satisfy present EV requests.

Whenever minimum loads are guaranteed to users, the DSOs

need to immediately update the information being

communicated to other (requesting) consumers. As there may

still be a certain fluctuations of individual demands, it is

advised that CS request a minimum energy level plus an

epsilon as risk hedging factor for the satisfaction of own

customers’ interests.

In order to allow pre-planning of both the distribution grid load

levels and the CS utilization, customer requirements should be

characterized by minimal and maximal energy charges

requested

User data – especially personal data, consumption pattern, reservation

details, and payment information – should only be exposed to a limited

REV1

REV2

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number of entities or optimally be handled anonymously (optimally up

to a single actor like the CSO or an InfSP). Thus, user data is only

forwarded to entities absolutely requiring this information and may in

the optimal case be anonymised.

Investment

Efficiency

----------

Efficiency of

Interaction

The charging is currently a slow process with duration between 30

minutes and 3-4 hours. A time accuracy in the schedule in the range of

minutes is therefore sufficient. Therefore the charging capacity

planning will have a granularity in the range of e.g., 5-15 minutes.

Charging stations require the latest price signals (wholesale markets,

aggregators) and available power profiles (calculated by the LV grid

controller; DSO interface) in order to optimize the utilization of

charging slots. In addition, an interaction between the charging station

(CSO) and the aggregator, for reserving/purchasing the energy is

required (also see generic business requirement above).

Flexibility of

Deployment

----------

Environ.

Sustainability

----------

Improved

Metering

Related to higher efficiency of interaction, frequent updates of

metering information again in the granularity of 15 minutes are an

essential prerequisite for the effective steering of customers and

efficient reservation of resources (also see generic business

requirement above).

Incentivizing

Customers

Requests consisting of a minimum and maximum (full battery) amount

of energy have to be considered in order to align energy demand and

price expectations to available resources and wholesale trading prices

in the energy supply. While due to congestions, fluctuating grid

conditions, the maximum request may not be satisfiable, the minimum

charge request should be met in any case.

Operational

Efficiency

----------

Information

Security

Secure handling of customer reservations (avoidance of manipulation,

and privacy) and wholesale market interactions is essential.

REV1

REV1: Required information sharing may conflict with the protection of user information and

anonymisation especially w.r.t. to the optimal steering of customers.

REV2: Customers may not be aware of their needs, especially hours before the usage. This may be an

immanent EV charging problem, but especially relates to the problem of reservation and pre-

planning. Thus, certain flexibilities for increased or reduced energy charging may have to be found,

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e.g., by proper integration with information services allowing an updating of plans within certain

bounds.

3.2.3.3 External Generation Site

Business

Requirements


Information

Sharing

DSOs will collect and process all data from end-users. Specific data will

be provided to relevant actors using different comm. networks. There

will be a need for a legal framework regarding the access and usage of

data.

Entities: All actors, esp. Information Service Providers, E-Mobility

Service Operators, Com. Network Providers, and DSOs.

REG1

Investment

Efficiency

Software platform allowing efficient deployment and interaction over

communication infrastructure with actors.

Efficiency of

Interaction

Adaptation of communication to fit current network condition without

changing interface for DSO or other entities accessing data from end-

users (also see generic business requirement above).

Flexibility of

Deployment

Plug&Play will require demanding connection requirements and

standardization for both grid and networks.

Environ.

Sustainability

Reduction of power losses due to a more careful handling and control

of assets

Improved

Metering

New metering functionalities will be required

o faster update rates for exchanged data

o possibility for delay estimation (network level)

(also see generic business requirement above)

Incentivizing

Customers

Potential of providing detailed information of energy

consumption/production to individuals, which may allow end users to

for example become aware of own consumption.

REG1

Operational

Efficiency

----------

Information

Security

----------

REG1: Access and usage of data may be strong concern for customers, whether end users or

enterprise customers.

3.2.3.4 AMR/CEMS

Business

Requirements


Information

Sharing

Information sharing between the customer energy management

domain and the service domain (DSO, Supplier, 3rd Party) is essential

business requirement and may additional technical infrastructure (at

RAC1

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gateway) and may require careful additional regulation

Investment

Efficiency

----------

Efficiency of

Interaction

(see generic business requirement above)

Flexibility of

Deployment

No decline of comfort or reliability of supply for customers (they need

not care about underlying infrastructure), i.e., influence to end users’

usage habits (manual) may be kept as minimal as possible or may be

assisted be compensatory measures such as monetary incentives or

supporting systems/automatisms (it has to be ensured that

automatisms cannot be used to the disadvantage of customers).

Consumption figures (visual indications) should be easy

understandable for end users and required human intervention should

be kept.

Evniron.

Sustainability

----------

Improved

Metering

(also see generic business requirement above)

Incentivizing

Customers

Access to CPE may require incentives for the customers, e.g., by

receiving cheaper or even free Internet access etc. (provided by telcos

or grid operators themselves), in order to create a mutual interest of all

actors.

RAC2

Operational

Efficiency

----------

Information

Security

Especially protection of energy consumer data is essential, i.e., privacy,

in order avoid legal or societal blockage.

RAC1

RAC1: More precise information of customer demand patterns is very valuable information esp. for

DSOs, which may thus be reserved towards actions protecting customer information. Anonymisation

and privacy protecting architectures may be supportive for aligning conflicting interests.

RAC2: CSPs may require to be subsidized for providing such offers, which may not be in line with

other smart grid actors’ intention.

Despite the broad conformity across use cases, a wide range of flavors is represented by the chosen

use cases. Thus, the identified use case-specific business requirements and drivers will serve as basis

for cross-validation dimensions during the formulation of the architecture and evaluation phases in

later stages of the development.

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4 UC details

In Chapter 2 an overview of the four Use Cases is presented. In this chapter a more deep description

is provided in order to highlight the ICT aspects. The communication components and the relevant

networks are hereby reported and the specific anomalous scenarios addressed by each Use Case

identified. In particular we distinguish the accidental faults from the intentional malicious attacks.

The type and the characteristics of the abnormal scenarios depend on the specific information flows

and architectures addressed.

4.1 Voltage Control in Medium Voltage Grid

4.1.1 Objective

The introduction of Distributed Energy Resources (DERs) can influence the status of the power grid.

The behaviour of DERs can affects the capacity of the DSO to comply with the contracted terms with

the TSO and directly the quality of service of their neighbour grids. DSO has to face with units whose

behaviour is both unknown and uncontrollable and investments on conventional reactive power

control devices in substations may become ineffective. Automatic voltage regulations limited to the

OLTC (On Load Tap Changer) of the substation transformers, as usually operated in passive grids, may

be not sufficient to meet the supply requirements established by the norm EN 50160. This difficulty

to meet the contracted terms and the quality of service standards not only could be transferred into

charges to the DSO, but also affects the TSO operation because the scheduled voltages at grid nodes

could not be observed and voltage stability problems cannot be managed properly.

In order to maintain stable voltages in the distribution grid the Voltage Control function is

introduced. This main goal can be extended in order to achieve other important objectives as supply

ancillary services, minimize the cost and the KWh consumption, provide reactive power support for

distribution buses, reduce energy losses and provide compatible combinations of the above

objectives. The specific aim of this UC is to define a ICT architecture for the Voltage Control function

suitable for the security analysis. The main functionality of the medium voltage control function is to

monitor the active distribution grid status from field measurements and to compute optimized set

points for MV DERs, flexible loads and power equipment deployed in HV/MV substations.

The voltage profile optimization is reached by controlling reactive and active power injection by

distributed generators, flexible loads and energy storages, and setting On Load Tap Changers (OLTC),

voltage regulators and switched capacitor banks. Costs of control actions and load/generation

forecasts in the area have to be taken into account to select the appropriate control strategy

[UC200].

Figure 8 schematizes the Voltage Control Function with the inputs and the computation of a Voltage

profile in order to send set points to customer and utility devices.

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Third party MV DER Distributor’s device

Voltage Profile

Grid Topology

Fieldmeasurem

ent

Marketprices

ResourceOperation

costs

TSOsignals

LoadForecast

Voltage Control

Function

GenerationForecast

Figure 8 - The Medium Voltage Control Function

Voltage profile and power flows in active distribution grids are changing dynamically, mainly because

of the stochastic production of renewable sources. The power injected by distributed generators can

overload feeder segments or lead the voltage beyond the limits in some parts of the grid. In order to

guarantee the correct voltage value at each customer site, the voltage profile of the distribution grid

is continuously monitored and optimized using the available grid flexibilities.

The optimization function can be implemented in a delocalized site for the selected area. Considering

the hierarchical architecture of the electric grids, a controlled area is a Medium Voltage (MV) section

of the grid, typically underlying a primary (HV/MV) substation and having points of common coupling

with distribution buses or the upper level grid. In this UC, the optimization function is performed by

the Medium Voltage Grid Controller of HV/MV substations.

At the border of the control zone the function can manage the area as a technical Virtual Power Plant

(VPP) and the main voltage optimization criteria can be extended to supply ancillary services to the

upper level grid, contributing to the stability of the electric power system. The function then

improves the spatial reactive power balance as well as the voltage quality in electric distribution

systems and also the spatial balance of the active power.

In a generic case, the optimization process takes into account combinations of technical/economical

objectives and constraints, including requirements on power exchanges at points of common

coupling with the higher-level grid. The optimization algorithm is not detailed in this generic use case

and it is assumed to be performed by an ICT component within the substation control network. Only

the actions derived from the optimization function are considered in view of their communication

needs.

As part of the coordinated optimization within the substation, suitable devices for control actions are

selected. Depending on the particular grid controlled area where the voltage control is applied and

on the optimization objectives, some generation/load units can be controlled either directly by the

DSO Controller or via the Flexibility Operator (in the following referred with the term Aggregator).

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After any change of an equipment state, either due to a substation request or to a local automatic

action, the substation is notified about the new state or operating point, including the information

on available regulation ranges.

The application includes the controllable power equipment, distributed generators variables and

issue corresponding signals to these variables in the closed-loop control sequences.

If during the execution of the optimal solution, the topology of the grid changes, then the application

is interrupted and the solution is re-optimized. If during the execution some operations are

unsuccessful, then the solution is re-optimized without involving the malfunctioning devices. If some

of the controllable devices are unavailable for the remote control, then the solution does not involve

these devices but takes into account their reaction to changes in operating conditions.

4.1.2 Architecture and Sequence Diagrams

In order to analyze the communication aspects of this use case, we need to highlight the main

interaction between the elements involved. The main control and communication components are

presented in Figure 9.

TSO Control Network

DSO/DMS

TSO/EMS

Generation Forecast

IEC

60870-5

-104

MVGC

IEC 61850

Load Forecast

IEC 60870-6

(ICCP)

IEC 61968-100

IEC

61850

IEC 60870-5-104

IEC 60870-5-104

IEC 60870-6 (ICCP)

IEC 61968-100

IEC 61850-8-1 (MMS)

Aggregator

IEC 61850-8-1

(MMS, IP GOOSE)

IEC 60870-6 (ICCP)

IEC 61968-100

DSO Control Network

OLTCCapacitor Bank

Substation Automation System

DER

Flexible Load

DSO Enterprise Network

Figure 9 The UC Architecture

The Medium Voltage Control Use case involves communications through components inside the DSO

area, but also exchange of information with systems outside the DSO domain.

The TSO Control Center interacts through the TSO Control Network and the DSO Control Network

with the DMS through a permanent link in order to be able to send, if necessary, the signal that

triggers the execution of the voltage control function.

In order to compute an optimized voltage profile the algorithm needs different input data provided

by different actors. The DMS forwards the information from these components to the Medium

Voltage Grid Controller. In this way the control center – primary substation communications are

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reduced. The Aggregator provides the load and generation program and the ancillary cost to DMS via

the DSO Enterprise Network.

Also the Load and Generation forecast interact with the DMS through the DSO Enterprise Network.

The DMS sends /receives information to/from the Medium Voltage Grid Controller through the DSO

Control Network.

The Medium Voltage Grid Controller is connected through the Substation Automation System with

the Capacitor Bank and with the OLTC in the substation LAN. DERs and Flexible loads communicate

with the Medium Voltage Grid Controller via the DER /Flexible loads Control Network, possibly

deploying heterogeneous communication technologies available in different geographical areas.

In particular it is possible to identify the following different networks as depicted in Figure 10 :

NW1: Wired LAN local to substation, distinguishing different network segments that

corresponds to separate control layers, e.g. station, bay and process layers

NW2: Wireless/wired WAN that may use commercial cellular or private wireless technology.

This network connects the substation with the DER sites

NW3: Private wired WAN. This network connects the DSO Operation Center with the

Substation. It may be based on dedicated communication services via wired WAN

NW4: Wired LAN local to DSO Operation Center, distinguishing different network segments

that corresponds to separate operation layers, e.g. DMS and MDMS

NW5: Wired WAN. This network connects the TSO Center with the DSO Operation Center. It

may be based on dedicated communication services via wired WAN

NW6: Public IP. This network connects the Aggregator with the DSO Enterprise Center

NW7: Wired WAN. This network connects the DSO Operation Center with the DSO Enterprise

Center. Most probably it will be based on dedicated communication services via wired WAN.

TSO Center

Aggregator Site

DER SiteDSO/Customer

DSO Operation Center

DSO Substation

FieldSubstation

AutomationSystem

DMS

Flexible load siteDSO/Customer

DSO Enterprise CenterEnterpriseSystems

NW6

NW5

NW7

NW3

NW2

NW4

NW1 MVGC

Figure 10 Voltage Control – Communications

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Figure 11 Medium Voltage Control Sequence Diagram

The sequence diagram in Figure 11 shows the exchange of messages between the actors. The DMS

collects information from the Generation Forecast, Load Forecast and Aggregator and forwards them

to the Medium Voltage Grid Controllers. The TSO can send signals to the DMS that dispatches them

to the Medium Voltage Grid Controller. The distributed energy resources, flexible loads and

distributor’s devices (OLTCs, Capacitor banks) provide measurements to the Medium Voltage Grid

Controller.

Once obtained all the required information the Medium Voltage Grid Controller, if necessary due to

the estimation of the state of the grid or for optimization purpose, computes the set points. These

values are sent to the field devices in order to stabilize the voltage.

4.1.3 Fault/threat analysis/scenarios

In the analysis of the attack scenarios different networks can be taken in consideration, in this Use

Case the Medium Voltage Control function is taken as central element and the related

communication networks are addressed. In particular the input and output data flows are

considered.

The two main areas of data exchange are the DSO Control Network (connecting the DMS with the

Medium Voltage Grid Controller) and the DER Control Network (connecting the Medium Voltage Grid

Controller with the DERs).

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After the identification of the critical networks that will be addressed, we focus our attention on the

possible effects that the attack can cause to the control function. In general the attack scenarios can

affect the following security properties [IEC 62351]:

Confidentiality: preventing the unauthorized access to information

Integrity: preventing the unauthorized modification or theft of information

Availability: preventing the denial of service and ensuring authorized access to information.

In the Voltage Control Use Case integrity and availability represent the most relevant security legs.

The availability is threatened by the possible loss of data or commands, while the introduction of

possible fake data or the execution of possible fake commands can have effect on the integrity of the

control function.

For each UC network, we can initially consider two macro categories of attack effects: loss of good

messages (effects on availability) or introduction of fake messages (effects on integrity). Moreover it

is possible to identify two types of traffic: periodic and asynchronous. Combining this information the

schema of possible attacks depicted in Figure 12 can be completed where three dimensions can be

observed: type of traffic (Periodic or Asynchronous), network addressed (DSO Control network or

DER Control network) and the security propriety effected (Integrity or Availability).

Availability

Integrity

Periodic traffic

I: Costs, Generations

Forecast, Load Forecast

Measurements (field)

O:Measurements, states (to DMS)

I: Measurements P,Q,V

DSO Control Network

Asynchronous traffic

I: TSO signal, TopologyO: Setpoint

O: Setpoint P,Q,V

DER Control Network

Figure 12 Possible attack scenarios to the Voltage Control function

In order to reduce the analysis space, a selection criteria based on the evaluation of effect criticality

has to be applied to all the possible attack combinations in Figure 12, resulting in the following attack

cases:

DoS Attacks to DER (gateways). The traffic between DER and Voltage Controller is perturbed

and some DER measurements are not able to reach the Voltage Controller.

DoS Attacks to Substation (gateways). The traffic between the Voltage Controller and the

DMS is perturbed; some DER and SCADA measurements are not able to reach the DMS any

more.

Fake DER setpoints. Either an (additional) fake setpoint is sent to DER, or a legal setpoint is

intercepted and modified with wrong set point values

Fake TSO signals. A fake TSO signal is sent to the Voltage Controller.

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A (flooding-based) DoS attack performed against DER or Substation gateway may perturb the

periodic traffic. The percentage of lost messages could allow to evaluate the possible effects on the

voltage control. On the other hand the sending of a fake message performed in order to implement a

fake setpoint or a fake signal, or to alter an existing message may cause instability or DER

detachment. The observed effect of the fake setpoints sent to DER is an enabling factor for the

intrusion detection.

In section 10.1.4.2 of the template (see Annex B - UC templates) some anomalous scenarios of the

Voltage Control function are analyzed with focus on the effect of the attack scenarios introduced

above.

The global impact of such cyber attacks to the Voltage Control functions on the supplied power

depends on the grid size and the amount of distributed generation, both these factors varying on a

geographical base.

By focusing on the Italian target of integrating an amount of renewable energy of about 40 GW

within 2020 [Petroni12], the distribution grid development plan will require the building of about

10% new HV/MV substations. The analysis of the attack impact on the supplied power depends on

the control network topology on the top of the power grid structure. By applying an extreme case

approach, the impact value associated to future smart grids endowed with the Voltage Control

function depends on the extension of the attack effect. For example, an attack to the DER network

could cause the disconnection of all the generators connected to the MV feeders of a given

substation (that means more than 100MW in the extreme case of the Center 25 in the Figure 13).

From the same impact analysis it results that an attack to the substation networks could be able to

disconnect one or several substations (e.g. less than 1 GW), while a control centre attack, causing the

disconnection of all the substations in a given control centre, could count 6 GW of unsupplied power.

Figure 13 Estimated RES Power per Substation (2020)

By mapping such impact values on the power scales identified by the SGIS working group [SG-CG/IS

12], it results that the impact of those cyber attacks to the communications of the Voltage Control

functions may be associated, respectively, to the Medium, High and Critical impact levels.

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4.2 External generation site

The Use Case is focusing on demonstrating the feasibility of controlling flexible loads and renewable

energy resources in LV grids over an imperfect communication network. The flexibility provided by LV

grids for upper hierarchical control levels is also investigated. The case is potentially disconnected

from the external MV grid, therefore the external generation site. In the following we elaborate this

use case.

4.2.1 Objective













Under these settings, different sets of actors will interact for the two focus points:




models).

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Primary Substation

Automation&Control

MVGC


HV Grid

HV

MV

MV

LV

Prosumer

Consumer

Interm. DER

Consumer

MicroDER

SME

Farm

SME

EnergyStorage

…

MV

LV

...

...

...

...

MV

LV

Use Case 2.3

Prosumer

Retailers

DMS

TSO

ForecastProviders

Markets

AggregatorsMV/LV

WAN

AN


&Performance


& Flexibility

AN Provider(s)

AN Provider(s)

WAN Provider(s)


Automation&Control


Automation&Control


LVGC

Figure 14: Overview of external generation site use case

Figure 14 also shows the proposed communication network structure imposed on the power grid.

The use case includes control of LV grid components, such as households, farms, PV’s, local wind

turbines, etc. as well as MV grid components such as larger refrigerator systems, wind farms etc. To

achieve this communication is needed to ensure proper transport of measurement and control

signals to assure proper control of the assets in the grid. Thus, the electrical grid includes both LV as

well as MV grid. The communication network is split into three categories: 1) the access network

(shown in orange) connects all actors in the low voltage grid; 2) the dedicated wide area network

(shown in blue) which is a high performance dedicated network for grid control; 3) the wide area

network (shown in red) connects the rest of the middle voltage actors.

The definitions for distributed energy resources used for this Use Case are defined in the table

below. These definitions take into account the voltage and current at the connection point as well as

the power rating of the device.

DER Definition Voltage Ratings

[kV]

Current Ratings

[A]

Installed

Capacity

[kW]

DER Type

Micro DER < 1 <16 < 5 DER at Household level e.g.

micro CHP, PV system, wind

turbine, energy storage,

Intermediate DER < 1 > 16 5 < …< 500 DER connected to low

voltage feeders. Examples:

standalone systems e.g. PV

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panels and heat pumps,

single wind turbine, battery

storage, charging spot for

EVs, etc

Large DER > 1 > 16 > 500 DER connected to medium

voltage grids. Examples:

wind or PV power plants,

Combined Heat and Power

plants, Supermarkets with

refrigeration systems and

charging stations for EVs,

etc.

Market(s)

Data Transport(WAN)

Data Transport(AN)

Control of assets

Retailer

DSO

TSO

ForecastProvider(s)

AggregatorTechnical (MV/LV)

Medium Voltage Grid Controller

Low Voltage Grid Controller

Prosumer

Consumer

Micro DER

WAN Provider(s)

Network

performance

change

Network

congestion

Lost network

connectivity

Network

performance

change

Intermediate DER

Large DER

DMS

AN Provider(s)

ProsumerNetwork

congestion

Lost

Network

connectivity

Figure 15: Overview of use cases – and fault/error cases.

The diagram in Figure 15 illustrates the use cases found in the external generation case. The key

functionality is to keep the grid operational in both technical and commercial sense as already

mentioned which is the key focus of Control of Assets use case. To ensure this, data and signals need

to be transported between the different actors which is the focus of Data Transport in both Access

and Wide Area Networks. The main issue with the data transport is that the network used for this

purpose, is not perfect and adds stochastic delays (potentially leads to loss of connectivity) as well as

packet loss to the transport. These undesirable effects are caused by various reasons in the networks

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and lead to different undesirable behaviors causing potential troubles for the control of the system

and therefore affect the Control of Assets case. Therefore it is important to enable the system to

overcome different situations in the communication network. In order to do so, the system must first

be able to detect faults and detect when it is safe to return to normal operational mode. To support

these use cases, there is a range of network activity necessary, first the monitoring of the

communication network is required to keep track of what is going on in the communication network;

second scalable management of data access mechanisms is a necessity to overcome the potential

number of sources and the geographical spread. To support the data access, data quality estimation

is also done. By this estimation process, data collected can be attached quality attribute that are

useful for efficient data access management. This may require reconfiguration of the network or

completely using a different communication network infrastructure. Finally, registration of

communicating entities is needed for the system to be aware of what is interacting with what.

4.2.2 Control of assets

The normal operation defines three sub cases that will be considered in the use case:

Energy balance – where the operation of MV grids is targeted. LV grids are considered aggregated and the LVGC is offering flexibility to the MVGC. Thus the MVCG is primarly controlling the assets such as Large DER, prosumers and LV grid via the LVGC to keep the energy balance. The primary actor involved here is the WAN Provider

MV operation – where the focus is to control the voltage profile as well as to optimize losses and energy costs on MV grids using active and reactive power capabilities offered by Large DER, MV prosumers and the secondary substations on MV side. The primary actor involved here is the WAN Provider

LV control - where the focus is to control the voltage profile on LV grids using reactive power capabilities offered by Micro and Intermediate DER, flexible consumption and production at household or small and medium enterprises. The primary actor involved here is the AN Provider(s)

These subcases may involve only some of the actors while other are neglected as mentioned above.

A detailed description of these scenarios is given in 10 Annex B - UC templates

4.2.3 Network adaptive data transport (AN/WAN)

The data transport covers the communication required to execute normal operations as described in

previous sub section, and generally covers data and signaling between entity A and entity B, and is a

part of the normal operation situation as shown in Figure 18. The use cases for the AN and WAN

focus on adapting the network layer to overcome different performance issues in the network that

affect the operation of the Control of Assets. For the network part, three fault/error cases are

thereafter considered (detailed views on these can be found in Annex B - UC templates):

Network Performance Changed - This scenario deals with time varying performance in the network, and the adaptation of access methods to provide reliable data exchange between entities communicating. This scenario is relevant for both WAN and AN.

Network Congestion - This scenario deals with more severe network conditions, i.e. congestions in the network, and the adaptation of access methods to provide reliable data exchange between entities communicating. This scenario is relevant for both WAN and AN.

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Lost Network Connectivity - This scenario addresses the case where devices loose

connectivity at the network layer. The case assumes a certain notion of connectivity, e.g. as

in TCP. This scenario is relevant for AN only.


In the following a brief overview of the architecture and functionality of the use case diagram is

provided in component and functional layers as described in [UCC]. This approach describes the

relation between components and functions in terms of electrical grid components (x-axis) and zones

of operation (y-axis) which is helpful also to understand the need for communication between the

various components and functions. Following this, a high level message sequence diagram connects

these components and functions in time.

Component Layer

TSO

AN NetworkProvider(s)

MV grid control

RetailerForecast Provider

TechnicalAggregation (LV)

LV grid control

Large DER

DMS

TechnicalAggregation

(MV)

WAN NetworkProvider(s)

Markets

Prosumer Micro DER ConsumerIntermediat

e DERProsumer

Smart Meter

Smart Meter

Smart Meter

Smart Meter

MV Grid Components

LV Grid Components

Station

Distribution DER Customer PremisesTransmission

Field

Process

Operation

Enterprise

MarketWAN Channel(s)

Private Channel(s)

AN Channel(s)

Figure 16 Components distributed in the external grid operation case

This figure illustrates what components are foreseen to be used in order to effectively execute the

use case Control of Assets shown in Figure 15, and although it appears quite wide, the focus in deed

is to balance the energy in the system which requires both MV and LV operations as well as

interaction with the external world related to the market and TSO. The setup in the scenario requires

several different types of DERs for proper energy balancing, with specific focus on the LV side

considering the technical and commercial aggregation as main points of operation. For completeness

to describe and understand the full operation of the grid, MV and some functionality from the LV/MV

and MV/HV is also needed as well as the parts related to commercial operation, e.g. retailers and

market interfaces. Communication will be focused to the Access Network and to some extend also

the Wide Area Network, which poses challenges due to a continously changing condition and

enviornment. Different traffic patterns, link conditions etc. will change the properties of the network

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over time, which needs to be handles. This will be addressed in the Data Transport use cases, and

the challenges as described in the sub cases.

TSO


MV grid control



LV grid control

Large DER

DMS


(MV)


Markets


e DERProsumer

Smart Meter

Smart Meter

Smart Meter

Smart Meter

MV Grid Components

LV Grid Components

Station


Field

Process

Operation

Enterprise

Market Market prices

Weather

information

Commercial

aggregation

HV grid management,

GIS system data,

planning tools,

visualisation

MV/LV grid

management, GIS

system data, planning

tools,

visualisation

Technical aggregation

Grid resynch., fault detection and

isolation, demand side mngt and

response, curtailment, ancillery services

Protection and monitoring

Warnings and alarms for

grid failure

Actuation Actuation Actuation

Protection and metering

Functional Layer

Figure 17 Functionalities in the external grid operation case

The functionalities shown in Figure 17 enable the envisioned operation of the Control of Assets use

case. The subsequent message sequence diagram shows an overview of the most important

operation, using the components and functionalities from Figure 16 and Figure 17. The remaining use

cases are found in the annex. At the lowest part, actuation functionality is used to efficiently

distribute actuation messages to the individual assets in the system. Protection metering and

monitoring functionality is running on top of the actuation for efficient and scalable data collection,

and event observation. On the DER side, this also includes some control functionality. On the MV and

LV side there is grid control functionality for the different voltage levels, and for the DER side

technical aggregation that allows the demand-response and production management. Further on

top, functionality for interaction between HV/MV and MV/LV is done, as well as the commercial

aspects are taken into account via functionalities allowing commercial aggregation, market (price)

interaction and interaction with forecast providers, e.g. on the weather situation. Again here,

communication is critical for these functions to perform properly. The impact of the solutions of the

network adaptation found in the Data Transport use cases to changing network conditions; will be

evaluated by the performance of the functions.

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TSOAN NetworkProvider(s)

MV grid controlRetailer

Forecast ProviderTechnical

Aggregation (LV)

LV grid control

Individual setpoints (MV)

Individual setpoints

Large DERMicro DER/

Intermediate DER/Prosumer

Consumer

Measurements

Aggregated flexibility (LV)

Measurements

Aggregated set point

AggregatedFlexibility (LV)

DMS

Weather information

Setpoint

Aggregated flexibility (MV)

Aggregated Setpoint (MV)

Measurements

Measurements

Measurements

NetworkStatus/

performance



TechnicalAggregation (MV)

AggregatedFlexibility (MV)

Measurements


Markets

Price signal

Aggregated setpoint (MV)

NetworkStatus/

performance

Individual

setpoints (MV)




Measurements


Weather information

Bids

Accepted bids

Setpoints

Measurements

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance Figure 18 Overview of the sequence diagram for normal operation mode, capturing Control of Assets and

Data Transport. The specific fault/error cases can be seen in Annex B.

Figure 18 shows the message exchange in normal operation. Starting from the lowest level (right in

the figure), consumers and DERs send measurements to the LV grid controller and receive setpoints

from the LV grid controller. The measurements from LV assets are aggregated before they are sent to

the MV grid controller. Similarly, the LV grid control receives an aggregated setpoint from the MV

grid controller that must be dispatched to the individual LV assets. The MV grid controller

communicates with Large DERs and LV grid controllers to exchange aggregated flexibility,

measurements, and setpoints. Additionally, the MV grid controller sends the aggregated flexibility to

the DMS, which generates setpoints based on the available flexibility, weather information, and

market conditions.

Basically, the operation mode interacts with the different actors as needed, and in particular, the

commercial part interacts also with the market entities to obtain set points for the grid operation.

These steps are continuously repeated with specific time intervals. It is important to realize that the

network use cases are run in the background and effectively evaluates the performance of the

interactions between the entities shown in Figure 18. That is, the overall functionality of the network

is to ensure that the signals shown in Figure 18 are effectively mediated to the different entities

involved. When faults/errors/performance degradation in the network occurs, the smartC2Net

platform shall adapt the strategies such that the overall operation does not necessarily degrades, or

at least to an acceptable level.

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4.3 Automated Meter Reading (AMR) and Customer Energy Management Systems

(CEMS)

This paragraph provides details on the Automated Meter Reading (AMR) and Customer Energy

Management System (CEMS) Use Case.

4.3.1 Objective

The following goals cover the objectives of the user as well as of the operator.

Automated Meter Reading:

Collection of energy consumption data from electric, gas, water and heating metering devices

Transmission of aggregated data from the households to the energy utilities/meter reading operators for billing and accounting

Provide (local) feedback system to the customers in order to provide transparent insight on the current energy consumption and enabling indirect demand side management

Aggregate information of energy consumption in order to balance the distribution grid by enabling direct demand side management

Customer Energy Management Systems:

Improve distribution grid stability by enabling direct demand side management

Reduce energy costs for consumers by shifting flexible loads to less expensive time slots or improve utilization of local energy resources

Optimize the utilization of energy according to supply contracts or other economic targets, e.g. by shifting flexible loads to less expensive time slots

Provide added-value services to the customers

Provide the flexibility information to the Aggregator by gathering customer premises’ data

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Figure 19 helps to get an understanding of the Automated Meter Reading (AMR) and Customer

Energy Management System (CEMS) Use Case (UC) by showing its logical and physical components

(e.g. the physical Network Access Points, not logical information flows) and their locations in the

Smart Grid Setup.

Simple external

consumer display

Home automation end device

Energy Management Gateway (EMG)

Smart Meter (SM)

Customer Energy Management System (CEMS)

Substation Level Operator LevelAutomated Meter Reading (AMR)

Local Network Access Point

(LNAP)

Flexible Loads

Non-Flexible Loads

Metering Operator

Private Charging Spot

Aggregator

Distribution Network Operator

Energy Service Provider

Metering Data Aggregator

Related to EV Use Case

Related to External GenerationUse Case


Meter Data Management System

Head End System (HES)

Neighborhood Network Access Point (NNAP)

Figure 19 Physical components of the use case and their locations in the Smart Grid setup

The figure depicts how the individual physical components are laid out. The Smart Meters (SM) of

the AMR use case measure the amount of energy, gas and water used in the household. Therefore a

connection between the flexible and non-flexible loads and the Smart Meter is necessary. The SM

interfaces with the Local Network Access Point (LNAP), which provides the WAN connection for

upload of the metering data. It is to be considered that, due to legal restrictions out of privacy

concerns, it is possible that a direct connection between SM and Energy Management Gateway

(EMG) might not exist. An EMG has the ability to controls flexible loads, private parking spots and

home automation devices. The state of these devices, along with current tariff and consumption

information, is made available for the consumer by an external display, which also provides a certain

degree of control over the CEMS. The LNAP has an interface to the Neighborhood Network Access

Point (NNAP) which itself connects to the Head End System (HES) with its subsequent set of devices

and roles. These are the Meter Data Management System (MDMS), Metering Data Aggregator

(MDA), Distribution Network Operator (DSO), Aggregator, Metering Operator and Energy Service

Provider.

Figure 20 delivers a detailed clustering structure of the use case. AMR and CEMS are in the center

and connect to sub use cases with their respective actors.

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DG.01. Direct Load /Generation

management

DG.02. HL-UC Flexibility offerings

DG.03. HL-UC Receiving consumption, price or environmental information for further action by consumer or a local

energy management system

CI.01. Provide Information to

consumer

ES.01. Tamper and Fraud detection

ES.02. Manage supply quality

ES.03. Monitoring

MM.01. Obtain meter reading on demand

MM.02. Obtain scheduled meter

reading

MM.03. Set tariff parameters

Keys

Customerinformation provision AMR Use Cases

<< extends >>

Actor A Actor B Actor C

Demand and Generationflexibility for technical and

commercial operations

Electric Vehicle REF: Use Case Name: Electrical Vehicle

Charging in Low Voltage Grids

Reference to use casedocument

Use Case ClusterUse Case Cluster

Use Case

Actor D

[WGSP Actor B]

[WGSP Actor A]

Collect AMI eventsand status information

<< extends >>

Measurement

Grid related REF: Use Case Name:

External Generation Site and Island Mode

CEMS Use Cases

Figure 20 Detailed use case clustering structure

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The sequence diagrams of the AMR / CEMS use case originate from the CEN-CENELEC-ETSI Smart

Meter Coordination Group and can be found with references in the corresponding use case template

located in the Annex B - UC templates.

Sequence Diagrams Figure Nr. Annex B

CEN Designation

Obtain meter reading on demand 4 MM.01

Obtain remote meter reading on demand 5 MM.01.01

Obtain walk-by meter reading on demand 6 MM.01.02

Obtain scheduled meter reading 7 MM.02

Obtain scheduled meter reading (Sequence Diagram) 8 MM.02.01

Configure reading schedule 9 MM.02.02

Set tariff parameters 10 MM.03

Set tariff parameter in the smart meter 11 MM.03.01

Set tariff parameter in the LNAP/NNAP 12 MM.03.02

Customer information provision 13 Cl.01

Send information to meter display 14 CI.01.01

Send information to simple external consumer display 15 CI.01.02

Smart Meter publishes information on simple external consumer display 16 CI.01.03

Manage supply quality 17 ES.02

Configure power quality parameters to be monitored 18 ES.02.01

Smart meter sends information on power quality to display 19 ES.02.02

Direct load / generation demand – appliance has end-decision about its load adjustment 20 DG.01.01

Direct load / generation demand - appliance has no control over its own load adjustment 21 DG.01.02

Information regarding power consumption / generation of individual appliances 22 DG.03.01

Information regarding total power consumption 23 DG.03.02

Price & environmental information 24 DG.03.03

Warning signals based individual appliances consumption 25 DG.03.04 Table 1 Overview of the CEN-CENELEC-ETSI AMR / CEMS sequence diagrams of Annex B - UC templates

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In this section the possible failures in the CEMS/AMR UC are considered. In particular, the focus is on

security threats that can hamper the CEMS main functionalities since the CEMS may operate in a very

hostile environment. Indeed, the CEMS can be connected to home automation devices and to the

EMG by means of shared network (e.g., the home WiFi, office LAN). The use of already deployed IP

network is extremely appealing since the cost for cabling and network interfaces is rapidly decreasing

[LECH08]. However, IP-based networks, when not well secured, are subject to cyber attacks.

The shift towards such a scenario may expose the communication and the CEMS critical

components, to attacks. For instance, an attacker can be:

a hacker with no intent to cause damage and who is satisfied by the penetration of systems

accessible through the Internet;

a criminal (e.g., disgruntled employee of the Energy Supplier or Energy Service Provider) who

wants to cause financial loss to the customer or to the energy service provider;

a customer with malicious objectives, e.g., to tamper the system with fraud purposes.

The attack can be executed either from the Internet or from a device connected to the HAN which

has been previously tampered, such as a personal computer or the LNAP, and may have special

information or authorizations (e.g., EMG login credentials, remote management of home automation

devices).

All in-house components are assumed to be connected to the CEMS. Among the functionalities of the

CEMS depicted in the use case diagrams (see Figures 20-25), the most critical operations that must

be secured are: i) direct load/generation management (DG.01.01) and ii) communication of power

consumption information (DG.03.01). The considered misuse cases are depicted in Figure 21.

Figure 21 Mis-use diagrams for the considered CEMS functionalities

The alteration or missed delivery of load adjustment commands that can be performed by means of

active attacks, i.e., the attacker tries to alter system resources or affect their operations. This may

compromise the capability of the customer to use the smart appliances or even the execution of

emergency procedures. When the attacker is able to compromise a limited number of CEMS the

impact of the attack is low; however, when the attack is coordinated and several CEMS systems are

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compromised (e.g., more than 100) or when some critical CEMS are violated (e.g., police and fire

departments systems) the impact of the attack can range from moderate to high (e.g., when the

CEMS systems of a very extended area, such as a city, are all compromised in a limited interval of

time). In the following we refer to this misbehaviour as incorrect direct load generation management,

mis-use case DE.01 (see Figure 21). These mis-use cases extend the ones provided by CEN-CENELEC-

ETSI Smart Meter Coordination Group and are fully described in the template located in the Annex B

- UC templates of the deliverable.

The access to power consumption/generation data shall also be secured against non-authorized

accesses. In other words customer power-related data shall be protected against passive attacks, i.e.,

attempts to learn or make us of information from a system without affecting its resources. As a

matter of fact, this is mandatory according to privacy law in some countries of the European

Community, such as Germany. Moreover, sophisticated burglaries could be architected when such

information is not secured. For example, thieves can exploit power consumption data to infer when

persons are not in the buildings and then plan physical penetrations. The impact of such an attack

can be classified as low. In the following we refer to this misbehaviour as disclosure of power

consumption information, DE.02 (see Figure 21).

For the aforementioned motivation, the network security requirements that shall be guaranteed in

CEMS systems are confidentiality, integrity and availability . In particular, for the communication of

direct load/generation management operations (i.e., load and emergency commands) integrity and

availability shall be guaranteed; while confidentiality, integrity and availability shall be assured when

power consumption data are exchanged.

According to the CEMS logical architecture described in Section 1 the most critical components

involved in the aforementioned operations are the EMG and the CEMS. Indeed, these can be

connected to the home WiFi and the likelihood to be exposed to malicious attacks is higher with the

respect to the components that are in dedicated network and when not protected by firewall or

other security mechanisms (e.g., encryption).

Incorrect Direct load and generation management

The considered active attacks that compromise the integrity and/or the availability of EMG/CEMS

and lead to incorrect direct load generation management are:

Man In the Middle (MIM) – an opponent captures messages exchanged between the EMG

and the CEMS. It can partially alter the content of the messages, or the messages are delayed

or reordered to produce an unauthorized effect.

Masquerade – an opponent sends fake messages the EMG pretending to be a different

entity.

Denial of Service (DoS) – the attacker floods anomalous messages to the EMG. It prevents or

inhibits the normal use or management of the communication facilities and/or the

components.

These attacks have been selected since they are usually performed by exploiting the most commonly

computer system and network vulnerabilities (e.g., sensitive data exposure, insecure object

references, broken authentication and session management, security misconfiguration). MIM and

Masquerade attacks can violate both integrity and availability; while, DoS violates only availability.

Tables Scenario D.01.01-D.01.03 and Figure 118-115, which can be located in the AMR / CEMS

template in Annex B - UC templates detail the considered active attack scenarios. It is worth noting

that just one interaction is considered for the mis-use cases DG.01.01 and DG.03.01; in particular, it is

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assumed that the Actor D starts the communication. However, a similar analysis can be applied when

Actor A initiates the communication.

The step by step description of the MIM attack is explained for the sake of clarity. As for other

attacks (i.e., masquerade and DoS) further explanations can be founded in the Annex B.

Figure 22: Mis-sequence diagram for the MIM attack

The MIM attack assumes an adversary can (i) observe messages exchanged, (ii) intercept messages

and (iii) reply messages with altered content (e.g., a load adjustment command sent by the EMG).

The attack takes place when the adversary intercepts the load adjustment command sent by the

EMG. Then, the attacker modifies the message previously intercepted and sends it to the CEMS. The

CEMS is not aware of the adversary modification and takes the load adjustment command as

appropriate and replies to the message. Hence, the attacker intercepts and alters the expected

change message sent by the CEMS (i.e. the reply to the load adjustment command) and finally sends

the altered message to the EMG. In this scenario, it is assumed that the CEMS sends the response

message to the EMG. However, the attacker might also be able to redirect all messages sent by the

CEMS to himself, e.g., by means of DNS tempering.

Disclosure of power consumption information

In this section the focus is on passive attacks that compromise the confidentiality of power

consumption information exchanged between the EMG and the smart appliances. As for the active

attacks that compromise the integrity and availability, similar analyses performed for the mis-use

case DE.01 also apply for the power consumption communication.

The considered passive attacks that compromise confidentiality are:

Release of message content: the opponent tries to eavesdrop transmissions;

Traffic analysis: the opponent observes the pattern of the messages to discover the location

and the identity of the parties involved in the transmissions, and the frequencies and the

length of exchanged messages.

The disclosure of message content scenario is detailed in Table Scenario DE.02.01, which is located in

AMR / CEMS template of the Annex A. When the smart appliance / generator sends information

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regarding consumption to the CEMS, the CEMS aggregates and/or forecasts total consumption and

sends this information to the display and to the EMG. The attacker may intercept the message and if

no cryptography method is used he/she reads the content about power consumption/ generation.

As for the traffic analysis attack the only differences with respect the disclosure of message attack

(depicted in Figure 29 in the AMR / CEMS template) is that we are assuming that the adversary

cannot understand the message. Hence, the opponent needs to intercept several messages in order

to observe the communication pattern and discover relevant information (e.g., location and the

identity of the parties involved in the transmissions).

Mis-sequence Diagrams Figure Nr. Annex B

Man in the middle (MIM) attack Figure 118

Masquerade attack Figure 119

Denial of Service (DoS) attack Figure 120

Disclosure of message attack Figure 121 Table 2: Overview of the mis- sequence diagrams of Annex B - UC templates

4.4 Electrical Vehicle Charging in Low Voltage Grids

EV charging appears in both the Home scenario, where it is coordinated by the Energy Management

Gateway (EMG, see 2.4), and in the public and semi-public scenario below, in which a charging

station coordinates the operation of several charging spots.

4.4.1 Objective

The objectives of the EV charging sub-system, as described by this use-case, are listed below:

Satisfy the charging demands of arriving EVs in such a way that the generated and stored

energy is efficiently used and the grid is not overloaded.

Enable electrical vehicle charging to become a flexible consumption resource that can be

used to balance energy and power resources in the LV grid along with decentralized

production as well as other loads (e.g. households).

Provide a system architecture enabling interoperation between new actors such as charging

station operators (charging aggregator) and their connection to existing actors such as DSOs

and energy providers.

Enable DSOs to monitor state of low voltage grid under EV load conditions


For SmartC2Net it is significant to describe the view of the various ICT network technologies and

operations constraints (Figure 23):

Network 1 – Metering. The metering network is owned by the DSO or a metering infrastructure

operator. It is a network used to collect smart meter data measurements at the last mile. The smart

meter network is usually based on powerline communications, cellular or proprietary wireless

solutions.

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Network 2 – Sub-station network. This network is an internal bus-network in the secondary

substation. It is owned by the DSO and connects equipment in the substation. May be based on

Ethernet.

Network 3 – Public IP Network. The Public IP network represents the open Internet. This is the

easiest platform for third parties to provide their services, such as routing services to EV users, or

weather services. The public IP network can be based on everything from wired xDSL based

technologies to cellular data access.

Network 4 – eCar Communication. This communication is between the charging station and the

electrical vehicle itself. The communication is usually wired and may be running through the charging

cable itself. Information about the state of the car, e.g. state of charge, preferred charging speed,

etc. may be provided through this network.

Network 5 – Private IP Network The private IP network represents a local network infrastructure

utilized by the infrastructure owner to connect local elements. For instance charging spots may be

connected to the charging station through this network. It could be based on PLC or Ethernet.

Network 6 - LV Grid Management Network. The DSO may choose to deploy an own closed

networking architecture used for grid components to communicate. Thus could be to communicate

with inverters, protection devices as well as sensors in the grid.

Network 7 – DSO Network. The DSO network is the network connecting the DSO management and

control systems (e.g. SCADA) towards the secondary sub-station. These networks are usually closed.

They may be based on fibre put out by the DSO as the cables to substations were put in the ground.

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DSO

Local LV Grid

ressources (DER)

Private Charging Station

EVprivch

Public Charging Station

Cloud

NW1: Metering

NW2: Sub-station NW

NW3: Public IP Network

NW4: eCar

CommunicationNW4: eCar

Communication

NW5: Private IP Network

NW6: LV Grid Management Network

Private

Charging

SpotEVpubch

Public

Charging

Spot

NW7: DSO Network

Charging

Station

Controller

Public

Smart

Meter

Photovoltaic

Inverter

Battery

Inverter

Private

Smart

Meter

Energy

Management

Gateway

Metering

Head-end

System

Metering

Aggregation

(NNAP)

Low Voltage

Grid Controller

Meter Data

Management

System

Distribution

Management

System

(SCADA)

Information

Services

Market

(Distribution/Transport)

Charging

Station

Routing &

Reservation

Aggregated

Charging

Infrastructure

Management

Figure 23 Networks of the EV use case

To define how these components are foreseen to interact over the provided networks, the use case

has been divided into three primary scenarios (PS) covering different functions and parts of the

system: 1) a charging scenario, 2) an energy and power management scenario, and 3) a market

scenario.

The overview of the interactions is given in Figure 24:

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DSO

Charging

Station

ControllerLow voltage

grid controller

E-mobility

Service

Operator

Charging

Station

Routing &

Reservation

PS2.10

Charging

spot

PS2.6

PS1.8

PS 1.6, PS 1.9

PS1.6, PS1.9

PS 2.4

PS 2.9

DMS

PV Local

Production

Battery

Storage

PS

2.8

PS

2.7

PS1.

1, P

S1.

3

PS

1.2,

PS

1.5

Aggregator & CSO

PS

3.3

MarketPS3.5

PS

2.5

PS3.4

Meter

Meter Aggregation

PS 1.11

PS1.

11

PS

3.6

Aggregated

Charging

Infrastructure

Management

PS1.3

PS1.4, PS1.7

Figure 24 Overview of the interactions between components

The EV charging scenario PS1.* describes the interactions between the EV owner, charging station

for reservation, plug-in, plug-out.

Scenario PS1

Scenario PS1: EV Charging

Step

No.

Event Name of

Process/

Activity

Description of

Process/Activity

Information

Producer

(Actor)

Information

Receiver

(Actor)

Information Exchanged

PS1.1 Charging

Station

Lookup

Find Charging

Station

Identify charging

station and

provide user

context

(expected stay

duration, needed

charge, …)

EV Owner

+ EV

Charging

Station

Routing

Charging Context.

PS1.2 Availability

Check

Availability

Check and

Response

The Charging

Station

Infrastructure

Mgmt. identifies

charging station

options and

informs EV

Owner.

Charging

Station

Routing

EV Owner Available charging

opportunities.

PS1.3 Reservatio

n

Charging

Station

Routing

receives

reservation

EV user selects

charging station,

arrival time

energy demand.

May get

EV Owner

+ EV

Charging

Station

Controller

Reserve message

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request and

redirects it to

CSO

additional

information such

as routing advice.

PS1.4 Process

Reservatio

n

Reservation

handling at the

charging

station

Update Schedule,

allocate

resources

Charging

Station

Controller

Charging

station

Routing

Schedule update and

resource availability

PS1.5 Reservatio

n

successful

CSO returns

OK

OK response.

Charging station

Routing updates

its CS availability

list

Charging

Station

Controller

EV Owner Reservation

confirmation

PS1.6 Plugin EV Plugin An EV plugs into

the Charging Spot

and provides

additional/updat

ed context

information

EV Charging

Station

Controller/

Gateway

Updated Charging

Context.

PS1.7 Plugin

Handling

Re-planning of

resources

The Charging

Station Controller

(re-)/plans the (if

needed) charging

plan

Charging

Station

Controller

Charging

Station

Routing

Schedule update and

Resource availability

PS1.8 Start/Stop

Charging,

Change

Charging

Speed

Charging

Process

Management

The charging

station controller

starts/stops

charging as well

as manages

charging speed

Charging

Station

Controller

EV Start/Stop commands.

Updated charging

speeds.

PS1.9 Plug-out EV Plugout The EV plugs out

of the Charging

Spot. The

Charging Station

Controller

adapts.

EV Charging

Station

Controller

Plug-out event

PS1.1

0

Periodic Metering Send charging

metering data to

meter

aggregation

system for billing

purposes

Smart

Meter

Meter

aggregatio

n

Meter data

PS

1.11

Periodic Metering Read meters for

state estimation

Meter

Aggregatio

n

LVGC Relevant Meter Data

The PS2.* Scenario relates to the energy balancing and power management at the LV grid level

Scenario PS2

Scenario PS2: Energy Balancing& Power Management

Ste

p

Event Name of

Process/Acti

Description of

Process/Activity

Information

Producer

Information

Receiver

Information

Exchanged

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No. vity (Actor) (Actor)

PS2.0

1

Update

LVGC

operation

Provide

update of

the LVGC

operation

settings

The DMS provides

information to the

LVGC to update high-

level operation

objectives as well as

changes in data

models such as grid

topology information,

newly connected

charging stations etc.

DMS LVGC - Setpoints

- Settings

- Data models

(e.g. grid

topology)

PS2.0

2

Update

LVGC

prediction

informatio

n

Provide

update of

the LVGC

data for

prediction

Information is pushed

(or pulled) from

information services

that are useful in the

LV grid management

operation such as

weather data.

Information

Services

LVGC - Weather

data

- Expected

load profiles

- …

PS2.1 Periodic Load and

Production

Prediction

The LVGC predicts the

expected production

and load a predefined

time into the future

for planning purposes

LVGC LVGC Updated

prediction

profiles

PS2.2 Periodic Metering Current load in

different busses of

the LV grid

Metering

Aggregation

LVGC Load

information

on busses

PS2.3 Periodic Distributed

Generation

Current generated

power in different

busses of the LV grid

Metering

Aggregation

LVGC Generated

information

on busses

PS2.4 Periodic Set Available power

for EV charging to all

charging stations

LVGC Charging

Station

controller

Available

power profile

PS2.5 Periodic Control

Re-planning

The LVGC plans the

local power and

energy resources to

maintain service

quality within

acceptable limits. It

may perform this

planning based on

setpoints from the

MV level.

LVGC LVGC Power and

Energy

control plan in

the LV grid.

PS2.6 Periodic Charging

Load profile

update

CSO updates the

schedule considering

the preferred loads

from aggregator and

the CSO available

power constraints

Charging

Station

Controller

LVGC EV Loads

update

PS2.7 Overvolta

ge/Curren

t

Limit

Production

If overvoltage/

over-current events

occur the LVGC can

choose to limit the

production in critical

periods to maintain

LVGC Photovoltai

c Inverter

Production

Limits

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power quality.

PS2.8 Service

quality

deviations

Change

battery

control

objectives

A local battery in the

grid can be requested

to change its

objectives to

increase/decrease

load to aid in the

operational

parameters

LVGC Battery

Inverter

Setpoints/obj

ectives for

battery

control

PS2.9 Power

quality

deviations

Change

demand

objectives

The LVGC can request

flexibility services

from the Charging

Station Controller to

increase/decrease

load now and in the

future. This involves

hard constraints on

power availability.

LVGC Charging

Station

Controller

Setpoints/obj

ectives for

-charging

demand

flexibility

- Available

power profile

PS2.1

0

Events/Al

arms

Monitoring

events/Alar

ms

A monitoring event or

alarm (depending on

criticality level) is

raised and sent to the

DMS to report about

the current and past

state of the LV grid.

LVGC DMS Event/Alarm

Scenario PS3 adds the view of EV aggregator/Utility

Scenario (see Figure 80 & Figure 81)

Scenario: PS3: Energy Market

Step

No.

Event Name of

Process/Activi

ty

Description of

Process/Activity

Information

Producer

(Actor)

Information

Receiver

(Actor)

Information

Exchanged

PS3.1 Periodic Sell

Production

Local energy sources

(storage and production)

sell energy resources to

an aggregator.

DER/Battery

owner

Aggregator Energy

production

capabilities

PS3.2 Periodic Sell

Aggregated

Production

Local energy resources

across several LV/MV

grids are aggregated

enabling the aggregator

to act on the retail

market

Aggregator Market Aggregated

energy

production

capabilities

PS3.3 Periodic Provide

EV charging

demand

The charging station

forwards an already price

optimized demand curve.

(alternatively, it forwards

the demand plus its

flexibility and the

aggregator performs the

price optimization)

CSO EV

Aggregator

(retailer)

demand +

flexibility

capabilities

PS3.4 Periodic Price signals pricing information is

provided to energy

providers/aggregators.

Market EV

Aggregator

Price signals

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PS3.6 Periodic Price signals The CSO uses the price

information and the

flexibility of the charging

operation to find an

optimal demand curve

EV Aggregator CSO Price

signals

PS3.5 Periodic Price

Optimized

Energy buying

The aggregator buys

updates the energy need

by buying on the intraday

market

EV Aggregator Market Demand


The fault/anomaly scenarios AS1 and AS1 address network interruptions: AS1- the connection

between LVGC and a charging station and AS2 – the connection between meters and LVGC is

interrupted.

Scenario

Scenario (Sub-

scenario)

AS1: EV demand control disrupted

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Information

Producer

Information

Receiver

Information

Exchanged

AS1.1 LVGC CS

connection

lost

Scheduling under

av. power

uncertainty

Enter precautious

mode. Refuse new

requests

CSO Charging

Spots

reduced

charging

duration

Scenario

Scenario (Sub-

scenario)

AS2: Metering data flow disrupted

Step

No.

Event Name of

Process/Activ

ity

Description of

Process/Activit

y

Informati

on

Producer

Information

Receiver


AS2.1 consumption

Metering

samples

missing

Estimate

load under

uncertainity

Conservative

calculation of

available

power

LVGC CS

controller

Reduced Available

power

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5 UC ICT requirements & success KPI

In any system development process the requirements represent the definition of the system

functions and their desired properties. As such the identification of UC requirements has been

considered as mandatory to the further development of the SmartC2Net UC.

In addition to UC requirements a list of Key Performance Indicators (KPI) has also been provided in

this initial phase as supporting the next development and evaluation activities of the SmartC2Net

components.

The requirements and the KPIs are determined from the use case analysis and they are studied under

several perspectives in order to identify those mostly related to the SmartC2Net objectives. Their

mapping with the SmartC2Net WPs allows understanding how the project developments will be

addressed and evaluated.

For the collection of the requirements and KPIs two templates have been used. For sake of simplicity

and readability the revised version of the requirement and KPI tables are collected in Annex C - Table

of Requirements and Annex D - Table of KPIs. In the next sections the respective templates are

presented first, followed by the relevance indications elaborated from the tables.

5.1 Requirement Template

Each requirement is characterized by several fields which both identify and characterize it. The

description of the characterization field is reported in Table 3:

Field Value Description

Requirement ID REQ_<nnn> This field contains a unique identifier of the requirement where <nnn> is a unique sequential number which identifies the requirement

Level This field specifies the logical level where the requirement is allocated. A requirement can be a general one specified for the whole system or a specific one for an individual component

SYS Whole system oriented

UC Use Case oriented

CO Individual component oriented

Priority This field specifies whether the requirement is considered for being created right now, or is a future development or is desirable

N Now: the requirement is taken into serious consideration inside the project

F Future: to be considered at some point in time

W Wish: the requirement is considered desirable but not yet scheduled in the project activities

UC Name This field specifies the reference UC if applicable

Title This field reports a brief description of the requirement

Category This field specifies the category of the requirements. For example if the requirement specifies a functionality or is dictated by standards.

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Functional This category comprises requirements about the functionality of the system/component including technical constraints such as:

voltage ranges

active/reactive power ranges/limits

generation/load coefficients

sample rates

EV schedule time horizon/resolution

generation/load profile time horizon/resolution

Architectural This category comprises architectural requirements

Dependability this category contains requirements about

Availability: readiness for correct service

Reliability: continuity of correct service

Integrity: absence of improper system alterations

Maintainability: Ability to undergo modifications and repairs

Security This category is a composite of the attributes of:

Availability for authorized actions only (access control, authorization, deny of service)

Confidentiality: absence of unauthorized disclosure of information

Integrity: data integrity, non-repudiation

Performance (Quality of Service)

This category comprises some specific performance requirements including the following time constraints: refresh time, response time, actuation time

Interface This category comprises interface requirements.

Communication This category comprises the requirement about the communication infrastructure including the following subcategories:

Communication size: possible measures are: bandwidth, data rate, range (Km), frequency band

Communication performance: possible measures are: delay, overhead

Communication availability: possible measures are sec-min-hour/year

Communication security: possible measures are # lost packets/messages, # discarded packets/messages, # faked messages

Communication cost: possible measures are €/y per connection point

Environment This category comprises requirements about the operational environment in which the system shall work.

Standard/Regulation This category comprises requirements dictated by the standards.

Description The description of the requirement

Table 3 Requirements Template Description

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5.2 Requirement analysis

Requirements represent an essential step in order to understand what the specific necessities of the

different use cases are. These functional and technical properties will drive the developments in the

other WPs. In particular these requirements will be used as inputs for the adaptive monitoring

(WP2), for addressing the adaptive communication (WP3), for the grid control algorithms (WP4), for

the validation of the models in WP5 and for the testbeds developed in WP6. In the requirement

study the mapping between the specific item and the related project WP is presented and some

analysis proposed.

Figure 25 provides an overview of the distribution of the four use case requirements over the

different project WPs.

Figure 25 Requirements: Project WP mapping

WP5 and WP6 (modelling and experimental analysis) are the most represented because the major

part of the requirements offers input for the evaluation work packages. In particular Figure 26

displays the mapping with the Monitoring, Communication and Control WP and Figure 27 shows

as the requirements are subdivided according to the model or testbed analysis.

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Figure 26 Requirements: WP2, WP3 and WP4 mapping Figure 27 Requirements: WP5 and WP6 mapping

These requirements are obtained considering different aspects as functionality, performance

(availability, latency...), maintainability (monitoring), and security (protection, authentication,

authorization …). Detailed lists of requirements tend to be extensive. In this section an analysis of the

requirements annexed in Annex C - Table of Requirements is presented. The whole set of

requirements is composed by a total of 136 items.

The subdivision considering the different use cases is depicted in Figure 28. The Medium Voltage

Control use case includes 46 requirements, the Electric Vehicle in Low voltage use case includes 22

requirements, the External Generation Site use case includes 26 requirements and the AMR/CEMS

use case includes 42 requirements.

Figure 28 Requirements: Use Case

Figure 29 shows the distribution of the requirements considering the different categories: Functional,

Communication, Interface and Security are the most represented as can be inferred by the scope of

SmartC2Net project.

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Figure 29 Requirements: Category

Another index/view that can be considered by the requirement analysis is the Level field, whose

graph is represented in Figure 30. More than half of the total requirements are of system level.

Figure 30 Requirements: Level

The list of requirements comprises a large number of items, it is important to highlight which of them

are more relevant for the project development. In order to obtain this indication it is possible to

analyse the priority field assigned to each requirements. Figure 31 shows the distribution of the

priorities and it is possible to note that the main part is tagged as “N” (now). This means that these

requirements are currently addressed.

Figure 31 Requirements: Priority

In the following pictures (Figure 32 - Figure 39) the graphs corresponding to UC specific

requirements are presented. From a first look, it can be observed that some UC, e.g. the EGS, only

included a subset of the template categories/levels. This means that those requirements have been

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identified as relevant to the SmartC2Net objectives, and it has not to be interpreted as a restriction

of the type of smart grid application that the UC is representing.

Figure 32 MVC UC Requirements: Category Figure 33 MVC UC Requirements: Level

Figure 34 EV UC Requirements: Category Figure 35 EV UC Requirements: Level

Figure 36 EGS UC Requirements: Category Figure 37 EGS UC Requirements: Level

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Figure 38 CEMS AMR UC Requirements: Category Figure 39 CEMS AMR UC Requirements: Level

The UC developments in the next phases of the project will allow refining the current list of UC

requirements in the Annex C.

5.3 KPI Template

As for the requirements, also for the KPIs a template is introduced. In Table 4 the fields involved and

their brief description are provided.


KPI_id KPI_<nnn> This field contains a unique identification number of the KPI where <nnn> is a unique sequential number which identifies the KPI

UC text UC reference

KPI name text Name of the KPI

Description text A brief description

Category

This field specifies the category of the KPI, for example if it is a technical ,or social or economic KPI

Technical_Power KPI related to technical power aspects

Technical_Communication KPI related to technical communication aspects

Social KPI related to social aspects

Economical KPI related to economic aspects

General General KPI

Scope

This field specifies the scope of the KPI, in terms of the main entities involved

Customer Customer oriented

DSO DSO oriented

CSO Charging Station Operator oriented

Aggregator Aggregator oriented

CSP Communication Service Provider oriented

Goal Expectation, objective Table 4 KPIs Template Description

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5.4 Key Performance Indicators (KPIs) analysis

The Key Performance Indicators (KPIs) represent a way to identify the important values to take into

account for the evaluation of the success of a proposed solution. Accordingly, choosing the right KPIs

relies upon a good understanding of what is important for the use case in relation to the SmartC2Net

objectives. The KPIs will be used in the others WPs, in particular in WP2 for the analysis of the

monitoring solutions, in WP3 for the validation of the communication architecture approaches

defined and in WP4 for estimate if the control techniques developed are satisfactory. Also the

assessment framework developed in WP5 and testbed implementation in WP6 take into account the

KPIs in order to evaluate the technologies and algorithms considered in the project.

Figure 40 shows the mapping of the KPI listed in the Annex D with the different project WP: we see as the identified KPIs will be used in order to validate the model and testbed implementation. The main WPs involved are the model related WP (WP5) and the testbed WP (WP6).

Figure 40 KPIs: Project WP mapping

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WP5 and WP6 (model and testbed work packages) implement the solutions developed in WP2, WP3 and WP4. All the KPIs addressed by Monitoring (WP2), Communication (WP3) and Control (WP4) WPs are also addressed by one or both the model (WP5) and testbed (WP6) WPs. For this reason a more interesting analysis is presented in Figure 41 where we see as the Monitoring (WP2), Communication (WP3) and Control (WP4) related KPIs are subdivided and in Figure 42 as these KPIs are evaluated by means of model (WP5) and testbed (WP6) analysis. The ICT related KPIs are relevant for the SmartC2Net project: they are spread over the different WPs. The KPIs important for some aspect of smart grid, but not for the scope of the SmartC2Net project are not addressed by any WP.

Figure 41 WP2, WP3 and WP4 mapping Figure 42 WP5 and WP6 mapping

In the following we focus the KPI analysis considering the four use cases. The KPI complete list is

presented in the Annex D. In the progress of the project they will be refined and those KPIs that will

be common to all UCs will be identified as global or smart grid level KPIs.

Figure 43 KPIs: Use Case

A total of 68 KPIs are identified and Figure 43 plots their distribution per use case.

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Figure 44 KPIs: Scope

If the scope field is selected as the analysis index, in Figure 44 it is possible to notice that the major

part of KPIs is DSO oriented. This is not surprising, as many UC objectives are related to the

optimization from the utility perspective.

Figure 45 KPIs: Category

Another interesting field that can be considered is the category: in Figure 45 it is possible to see as

the main categories are the technical ones. In particular as we can suppose, the power and

communication categories are the most represented.

In the following pictures (Figure 46 - Figure 53) the specific use case graphs are presented showing

the UC specific focus.

Figure 46 MVC UC KPIs: Category Figure 47 MVC UC KPIs: Scope

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Figure 48 EV UC KPIs: Scope Figure 49 EV UC KPIs: Category

Figure 50 EGS UC KPIs: Scope Figure 51 EGS UC KPIs: Category

Figure 52 CEMS AMR UC KPIs: Scope Figure 53 CEMS AMR UC KPIs: Category

6 Preliminary overall architecture

Starting from a bottom-up analysis of the individual use case architectures a preliminary high level

architecture is derived at the aim of highlighting the interactions among the respective control

components and ICT networks. This integrated view allows having a comprehensive picture of the ICT

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aspects addressed by the SmartC2Net project. It is important to have not only the specific use case

view, but also a global outlook in order to understand what are the common aspects and interactions

as well as the parts of architecture that the different use cases share.

This preliminary version of the overall architecture is aimed at defining the logical interfaces of the

different control components. Where alternative architectures might be envisioned for a specific use

case, e.g. for the Home Energy Management UC, we decided to include all the alternatives to cover in

the overall architecture as many case instances as possible.

6.1 Global architecture

One of the main targets of the SmartC2Net project is to demonstrate that it is feasible to have a

robust control of the power grid using and open and heterogeneous communication infrastructure.

In fact, while at the Generation and Transmission areas, the communication infrastructures are

normally private and protected from external access, the Smart Grid extends the areas where the

communication between devices is required to the medium and low voltage areas, which were, till

now, unobserved and uncontrolled. The proposed preliminary architecture aims at satisfying the

requirements of power grid monitoring, communication network monitoring and grid control

associated with the Use Cases and that will be developed in WPs 2, 3 and 4. This architecture may

nevertheless be further tuned during the project evolution.

6.1.1 Layered architecture

The proposed architecture maps the architecture of the Distribution System, by having components

in the different sites that can be found in a typical electrical distribution grid.

Different areas are involved: there are equipment and systems located at the Central Management

Level, at the Primary Substations, at the Secondary Substations and at the Customer Premises.

In particular the Distribution Management System (SCADA/DMS) and the Demand Response System

are placed at the Central Management Level. Since they have a view of the entire power grid and

communication network, their actions may have a global scope.

The Medium Voltage Grid Controller (MVGC) is located at the Primary Substation (HV/MV). Its

actions will have a local scope, interacting with the Primary Substation and with other systems

connected to it, namely DERs (MV) and Secondary Substations.

The Low Voltage Grid Controller (LVGC) is located at the Secondary Substation (MV/LV). Its actions

will also have a local scope, with low voltage devices and systems, connected to the Secondary

Substation, namely Customer Installations and DERs (LV).

At the Customer Premises several equipment and systems are placed: Smart Meter, Customer Energy

Management System, PV inverter, EV Charger, flexible and non-flexible loads.

Other systems outside the Distribution Grid will also be taken into consideration, namely the Energy

Management System, owned by the TSO, Weather Forecast Information, Market Operators, EV

Charging Operators, Telecom Operators Information Systems and third party Aggregators.

Equipment and systems that may exist in the Distribution Grid but that may not be owned by the

DSO, like Distributed Energy Resources (Distributed Generation, Flexible Loads) are also considered.

The following figure shows the different sites, equipment and systems as well as the communication

networks that connect them.

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Figure 54 Overview of the SG architecture

6.1.2 Distribution of functions

The proposed architecture also allows the distribution of functions across several locations and

equipment, allowing the processing of data close to the data sources and data users.

At the Central Systems Level the following functions will be implemented:

Global Grid Monitoring

Global Grid Management

Global Communications Network Monitoring

Global Communications Network Management

Demand Response

At the Primary Substations the following functions will be implemented:

Distribution Grid Monitoring

Distribution Grid Management

Communications Network Monitoring

Communications Network Management

Distributed Energy Resources (DER) control (MV)

At the Secondary Substations the following functions will be implemented:

Distribution Grid Monitoring

Communications Network Monitoring

Demand Response

Load Management

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Distributed Energy Resources (DER) control (LV)

At the Customer Premises the following functions will be implemented:

Load Management

Micro generation Management

EV Charging

Some functions may extend a single location and will be distributed across several sites. The EV

Charging Use Case is an example of such a situation.

6.2 Use Case mapping

The following sections describe how the proposed architecture maps the chosen use cases.

In order to provide a global vision of the infrastructure and not only restricted to the single use case,

the following figures show how the different Use Cases and the different equipment, systems and

communication networks are related.

Figure 55 gives a general view of the Use Cases and the equipment, systems and communication

networks that are going to be involved in each of the Use Cases.

The figure shows for each use case, which sites and which equipment and systems are involved.

External systems are also shown.

It can be seen that the Use Cases are not isolated from each other and more than one Use Case

involves the same sites and the same equipment, systems and communication networks, sharing a

common architecture.

It can be seen in the figure that the Medium Voltage Grid Controller, DER (MV) and Flexible Loads are

involved in the Medium Voltage Control and the External Generation Site Use Cases.

Also the Low Voltage Grid Controller and several equipment and systems located at the Customer

Premises are involved the External Generation Site, Electrical Vehicle Charging and Customer Energy

Management System and Automated Meter Reading Use Cases.

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MVG

DER

WAN

DMS - Distribution Management

System

DSO Center

Primary Substation

WANFlexible

Load

LVGSecondary Substation

AN

Customer

Charging StationCEMS

MVC UC

CEMS & AMR UC EVC UC

External Generation Site UC

External Systems

Information Service

Aggregation Controller

Charging Station &Routing Reservation

Weather forecast

Distribution Market

Legend:DSO: Distribution System OperatorWAN: Wide Area NetworkMVG: Medium Voltage GridDER: Distributed Energy ResourceAN: Access NetworkLVG: Low Voltage GridUC: Use CaseMVC: Medium Voltage ControlCEMS: Customer Energy Management SystemAMR: Automated Meter ReadingEVC: Electrical Vechicle Charging

Figure 55 Overview of Use Cases mapping

Figure 56 provides a detailed view of the system architecture, mapping all the involved equipment

and systems, either directly associated with the distribution grid or external, and also the

communication links that connect them. In particular the Logical Interfaces (LI) are represented.

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Flexible Load Control

Charging Spot

Charging Spot

EV

EV



Local LV grid resources (DER)


Primary Substation

Substation Automation System

Capacitor Bank OLTC

DER(generic)

Flexible Load(generic)

Load Forecast

TSO

GenerationForecast

Weather Forecast

MVC UC

Micro-combinedHeat and power unit (Micro-CHP)

Simple externalConsumer display

Photovoltaics

Smart Meter

AMR

Metering Aggregation(NNAP)

Home automationend device

MV/LV Secondary Substation

HV/MV Primary Substation

Central Management

DER Control

Non flexible load Flexible LoadDER

AN

Customer

Photovoltaic Inverter

Battery Inverter

EVC UC

CEMS & AMR UC


UC

LI1: Internal Communication

LI2: TSO Communication

LI3: Control communication between Control Center and primary and secondary substation

LI4: Metering communication

LI5: Control communication inside LVG

LI6: Local control communication

LI7: Control communication inside MVG

LI8: Communication between External System and SmartC2Net

Metering Head-endSystem (HES)

Charging StationController

PublicSmart Meter

DSO Enterprise Center

TSO: Transmission System OperatorDSO: Distribution System OperatorWAN: Wide Area NetworkMVG: Medium Voltage GridDER: Distributed Energy ResourceAN: Access NetworkLVG: Low Voltage GridUC: Use CaseMVC: Medium Voltage ControlCEMS: Customer Energy Management SystemAMR: Automated Meter ReadingEVC: Electrical Vechicle ChargingOLTC: On Load Tap ChangerNNAP: Neighborhood Network Access Point

MVGC

External Systems

Legend


EMG

PrivateSmart Meter

Charging Station &Routing Reservation

Information Service

LI_DMS_TSO

DMS

Aggregator Controller

Energy Storage

UPS

Wind Turbines/plants

Refrigerator System

Demand/Response ManagementControl

Tariff Management

EV Charging Station


LI_Weather_LoadForecast

LI_DMS_LoadForecast

LI_DMS_DMC

LI_DMS_GenForecast

LI_Weather_GenForecast

LI_GenForecast_MDMS

Automated Meter Data

Management System

LI_GenForecast_GridDB Grid DB Manage

ment

LI_DMS_AggContr

LI_D

MC

_Tar

iffM

gmt

LI_A

C_D

MLI_DM_Info

LI_DMS_HES

LI_MVGC_EnergyStorage

LI_MVGC_Wind

LI_MVGC_UPS

LI_MVGC_DER (generic)

LI_MVGC_FlexLoad

LI_MVGC_EVCS

LI_MVGC_Ref

LI_LVGC_PVInv

LI_LVGC_BatteryInv

LI_LVGC_CSC

LI_P

VIn

v_B

atte

ryIn

v

LI_CSC_CS

LI_PSM_CS

LI_EMG_AMR

LI_EMG_Display

LI_E

MG

_HA

LI_E

MG

_DER

LI_E

MG

_CS

LI_SM_mCHP LI_SM_PV

LI_E

MG

_No

nFl

exLo

ad

LI_E

MG

_Fle

xLo

ad

LI_A

MR

_DER

LI_A

MR

_No

nFl

exLo

ad

LI_A

MR

_Fle

xLo

ad

LI_LVGC_AMR

LI_DMS_MVGC

LI_M

VG

C_S

AS

LI_SAS_CapBank LI_SAS_OLTC

LI_DMS_GridDBDistribution Market

LI_CS_EV

LI_CS_EV

LI_CSC_AggContr LI_EMG_AggContr

LI_HES_AMR

LI_AMR_NNAP

LI_H

ES_N

NA

P

LI_LVGC_NNAP

LI_D

MS_

LVG

C

LI_D

MS_

NN

AP

LI_CSRR_AggContr

LI_HES_SMLI_SM_NNAP

LI_HES_PSM

LI_PSM_NNAP

LI_AMR_Display

LI_M

VG

C_L

VG

C

External Systems

Aggregator Site(can be included with DSO/TSO)

Wind Turbine(s)

LI_SM_WT

Flexible Load

LI_A

MR

_CS

LI_PrSM_CS

Figure 56 Detailed view of Use Cases mapping

In the Medium Voltage Control use case, the SCADA/DMS, located at the Central Systems Level

communicates with the Medium Voltage Grid Controller located at the Primary Substation through

the logical interface LI_DMS_MVGC in Figure 56. To interact with the Primary Substation equipment,

communication between the Medium Voltage Grid Controller and the Substation Automation System

will be required (logical interface LI_MVGC_SAS).

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In order to perform the voltage control, the Medium Voltage Grid Controller needs to receive

measurements from and send setpoints to DER (MV) and Flexible loads. This exchange of data is

performed using the logical interfaces of type LI7.

Communications of the SCADA/DMS with external systems will also be required, namely

communications with the Energy Management System owned by the TSO (logical interface

LI_DMS_TSO), the Weather/Load Forecast Systems and Aggregator (logical interfaces

LI_DMS_GenForecast and LI_DMS_LoadForecast).

In the Electrical Vehicle Charging use case, the SCADA/DMS, located at the Central Systems Level, the

Low Voltage Grid Controller located at the Secondary Substation and the EV Charger, Smart Meter

and Micro-generation located at the Customer Premises will be involved.

Communication with external systems, namely Market Operators, Charging Station Operators and

Routing Reservation systems will be required.

In Public Charging Stations, the Charging Station Controller will also be involved.

n the External Generation Site use case, the SCADA/DMS and the Demand Response System, located

at the Central Systems Level, the Low Voltage Grid Controller located at the Secondary Substation

and the flexible loads and Micro-generation located at the Customer Premises will be involved.

DER (Distributed Generation and Flexible Loads) connected to the Medium Voltage Grid will also be

considered.

In the Automated Meter Reading and Home Energy Management use case, the SCADA/DMS, located

at the Central Systems Level, the Low Voltage Grid Controller located at the Secondary Substation

and the Home Energy Management System and Smart Meter located at the Customer Premises will

be involved.

Other devices like flexible loads, Micro-generation (PV inverters, Micro-CHP), EV chargers, in-Home

Automation devices, Consumer Display, will also be considered. The Aggregator, the Metering Head-

end System and an EV charging spot are also involved in providing the functionality of the

AMR/CEMS UC.

This first sketch of the high level architecture provides a view of each smart grid application

integrated in the global smart grid control, highlighting the main logical component interfaces. This

overall architecture has to be considered as preliminary and will be updated at the end of Year 2

according to the progress of WPs 2-5 and to the lab prototype setup in WP6. Starting from this

preliminary overview architecture the other WPs take inputs for monitoring, control and

communication aspects. Also the development of the System Assessment and the Test Beds need

information obtained from this architecture.

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7 Conclusions and Outlook

This deliverable includes the control scenarios analyzed in SmartC2Net and provides many

information about their ICT architectures. In particular four use cases representative of the Smart

Grid domain are described and critical anomalous scenarios related to faults and threats identified.

From the energy market model the business driver and requirements associated with the use cases

are analysed, allowing to compare the possible technological and architectural options in the use

case over their benefits and their architecture impacts.

A first sketch of the high level architecture is presented with the specific aim of developing a view of

each smart grid application integrated in the global smart grid control, highlighting the main logical

component interfaces. However the overall architecture has to be considered as preliminary at this

project phase and to be updated at the end of Year 2 according to the progress of WPs 2-5 and to the

lab prototype setup in WP6.

The outcome from the UC analysis and the overall architecture have provided inputs to all the other

project WPs, defining the requirements and the architecture border for the development of the

Adaptive Monitoring (WP2),the Adaptive Communication Solution (WP3), the Adaptive Control

(WP4), the System Assessment (WP5) and the Test Beds (WP6) that will focus on the UC

requirements. Some fault and attack scenarios identified by the UC analysis will be modeled in the

System Assessment (WP5) and implemented in the Experimental Prototypes (WP6), where the

impact of the use case integration in the overall architecture on the grid operation will be analyzed

from a technical stand point. In the last phase of the project the output of the economic analysis will

be re-considered in the exploitation task (WP7) to define the business impact of the SmartC2Net

solutions.

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8 Bibliography

[ADL12] Arthur D. Little: Telco and Utility: Friend or Foe?, Energy & Utilities Viewpoint, 2012. Web access: http://www.adlittle.com/downloads/tx_adlreports/ADL_ENRUTL_2012_TelcoUtility_Friend-or-Foe.pdfWeb access: http://www.adlittle.com/downloads/tx_adlreports/ADL_ENRUTL_2012_TelcoUtility_Friend-or-Foe.pdf

[AFSP07] L’Abbate, A., Fulli, G., Starr, F., & Peteves, S. D. (2007). Distributed Power Generation

in Europe: technical issues for further integration. Joint Research Center Institute for Energy. WWW. CaRBoNWaRRooM. CoM2007.

[ANME12] Analysis Mason: Case study: Telenor Connexion’s approach to an M2M smart grid

implementation in the UK; May 2012; Steve Hilton

[BDCN12] C Baldi, G Di Lembo, F Corti, F Nebiacolombo, “Monitoring and Control of Active

Distribution Grid” ”. CIRED 2012 Lisbona (PT), 29-30 May 2012

[DoW] SmartC2Net – Description of Work

[DGPT12] G. Dondossola, F. Garrone, G. Proserpio, C. Tornelli, 2012, “Impact of DER integration on the cyber security of SCADA systems – the Medium Voltage regulation case study”. CIRED 2012 Lisbona (PT), 29-30 May 2012

[EPRI10 ] M. Wakefield: Methodological Approach for Estimating the Benefits and Costs of Smart

Grid Demonstration Projects. Electric Power Research Institute (EPRI), 2010. [FIER11] FierceSmartGrid: Telecom's evolving role in smart grid 2011. Web Access:

http://www.fiercesmartgrid.com/story/telecoms-evolving-role-smart-grid/2011-04-20

http://www.adlittle.com/downloads/tx_adlreports/ADL_ENRUTL_2012_TelcoUtility_Friend-or-Foe.pdf

http://www.adlittle.com/downloads/tx_adlreports/ADL_ENRUTL_2012_TelcoUtility_Friend-or-Foe.pdf

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[FIEX12] Financial Express: M2M device connections in automotive sector to rise to 277m in

2020. 2013. Web access: http://www.thefinancialexpress-bd.com/print.php?ref=MjBfMDNfMDVfMTNfMV84OV8xNjIwOTg

[FSS12] SGCG/M490/B_Smart Grid Report First set of Standards Version 2.0 Nov 16th 2012 [HaSn89] Hakansson, H., Snehota, I.: No Business is an Island: The Network Concept of Business

Strategy. Scandinavian Journal of Management (1989) 187–200

[IEC104] IEC TC57 IEC 60870-5-104 International Standard

[IEC61850] IEC TC57 IEC 61850(-7-420) International Standard

[IEC 62351] IEC TC57 IEC 62351 International Standard

[IEC TC8] Use Case Approach Part 2 - Definition of Use Case Template, Actor list and Requirement List for Energy Systems – NWIP 8/1307/NP 20 June 2012

[INFO12] Informa: M2M Communications - Turn Potential into Profit. 2012. Web Access:

http://www.informatandm.com/wp-content/uploads/2012/04/M2M-Communications.pdf

[INT12] InTech: Wired vs. wireless in utility markets. Web Access http://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentDisplay.cfm&ContentID=89205

[LECH08] D. Lechner, W. Granzer, and W. Kastner. Security for KNXnet/IP. In Konnex Scientific

Conference, November 2008 [NoRa94] Normann, R., Ramirez, R.: Designing Interactive Strategy: From the Value Chain to the

Value Constellation. John Wiley & Sons (1994) [NTS12] National Technical System – Advanced Technologies: Wired vs wireless in utility

markets, Web access http://smartgrid.testing-blog.com/2012/04/15/wired-vs-wireless-in-utility-markets/

[Petroni12] Petroni P., Smart Grids Operation, automation and protection issues CIRED 2012

Lisbon (Portugal) 29-30 May 2012 [ScTa12] Schleicher-Tappeser, R.: The Smart Grids Debate in Europe. SEFEP working paper,

2012. Web access: http://www.sefep.eu/activities/publications-1/SEFEP-SmartGrids_EU.pdf

[SG-CG/IS 12] CEN-CENELEC-ETSI Smart Grid Coordination Group Smart Grid Information Security

2012 [UC200] SGSP Working Group Use Case WGSP-0200

[UCC] SGCG/M490/E_Smart Grid Use Case Management Process — Use Case Collection, Management, Repository, Analysis and Harmonization

http://www.thefinancialexpress-bd.com/print.php?ref=MjBfMDNfMDVfMTNfMV84OV8xNjIwOTg

http://www.thefinancialexpress-bd.com/print.php?ref=MjBfMDNfMDVfMTNfMV84OV8xNjIwOTg



http://www.sefep.eu/activities/publications-1/SEFEP-SmartGrids_EU.pdf

http://www.sefep.eu/activities/publications-1/SEFEP-SmartGrids_EU.pdf

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9 Annex A - Value Networks

Based on the SmartC2Net use case description (see Section 4) two Value Network (VN) models are

created and presented in this section: a generic classical grid and new SmartC2Net / Smart Grid

model. In lieu of value chains (activity chains) or business models (intra-firm concept), VNs are

capable of expressing (non-sequential) value streams in an inter-firm context, also see [HaSn89] and

[NoRa94|.

Thus, the specified VNs aim at capturing relevant entities, i.e., actor roles, from a business

perspective. In this way, technical processes or systems are eliminated from this perspective.

9.1 Electrical Grid Value Network

In order to be able to extrapolate economic differences between the “classical view” on electrical

grids and on the smart grid presented by SmartC2Net, the VN of “classical” electrical grids will

subsequently be briefly revisited by means of its entities and main value flows, and illustrated in

Figure 57.

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Energy

Generators

/ DER

Energy

Consum er

Energy

Aggregator

DSO

Retailer

W holesale

Market

energy &

pricing

distribute

energy &

flexibility$energy$

Trade energy/flexibility

for balancing

Energy

Prosum er

Energy

Consum er

… "eye ball" consumer

(own demand)

CAM … (central) grid role

Charging

Stat ion Op.

… use case

specific role

reliability 1

2

2

Metering information

3 comply to

agreements

3

4 demand & supply

forecasts

physical attacks

faulty devices

human errors...

energy

$

energy

trade

$

Regulator

$

Regulator … public authorities

$

long-term

price sensitivity of

demand

(assisting stability)

CAM

1

TSO

$energy

long-term trading/reservat.

metering

5 supply sbj. to

long-term pricing

agreements

5

Legend

Figure 57: “Classical” Electrical Grid Value Network

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9.1.1 Entities

9.1.1.1 “Eye ball” consumer in two flavours:

Energy consumer: The energy consumer is the classical consumer not providing any energy or

energy service to any other party.

Energy prosumer: The prosumer extends the role of a consumer by also generating energy

(see dedicated roles).

9.1.1.2 Energy sector:

Generation/Aggregation:

Energy Generators / Distributed Energy Resources (DER): Power plants and small energy

generators (e.g. PVs) producing the energy to be delivered to customers or traded on

markets.

Energy Aggregator: Aggregating individual DERs in order to act on (wholesale) markets

o Representing small actors (like individuals with their PVs) on wholesale market by

trading their resources appropriately

Market & Sales:

Wholesale Market: A (wholesale) market where it is possible to buy and sell energy and

demand flexibility, i.e., short-term (next day, intraday), long-term, and energy balancing

trading.

o Often operated by “Power Exchange” entity

o Scheduled energy exchange & flexibilities (e.g. in terms of primary, secondary, and

tertiary reserves)

o High transmission capacity required in order to avoid arbitrage business due to

different price levels in Control Areas accessing the market

o Incentives for precise reservation requests, e.g. tailored auction mechanisms

o Base load and peak load differentiation

o Trading of intermittent energy resources, e.g., realized in Spanish and US markets4

Retailer (Supplier, Trader): The retailer is the energy role having access to eyeball customers

by selling energy to them. It relies on an existing distribution network and the energy trading

on the wholesale market. It is responsible for acquiring required resources on the wholesale

market and may be confronted with compensation payments in case of unsatisfactory

physical delivery.

o Demand matching dynamicity in minutes (e.g. each 5 minutes) and price dynamicity

at ~ 30 minutes to 60 minutes5 at the minimum.

Distribution / Transmission / Balancing:

Distribution System Operator (DSO): According to the Article 2.6 of the Directive: "a natural

or legal person responsible for operating, ensuring the maintenance of and, if necessary,

developing the distribution system in a given area and, where applicable, its interconnections

4 http://www.smartpowergeneration.com/spg/discussion/flexibility_is_needed_-_but_th

5 National Electricity Market (Australia): http://eex.gov.au/energy-management/energy-procurement/energy-pricing/how-the-energy-market-operates/

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with other systems and for ensuring the long-term ability of the system to meet reasonable

demands for the distribution of electricity".

Control Area Manager (CAM): The European interconnected grid is subdivided into large number of

control areas that control the power that flows across it. These areas are largely independently

operated. Power meters are installed on every power line that crosses a control area boundary, and

the readings are transmitted online to the respective control centres. The Control Area Manger (CAM)

is then responsible for the system stability. The CAM calculates in advance how much

electricity will be needed to cross the control area boundaries to fulfil the supply contracts in

place. The power stations within the control areas are operated in accordance with these

schedules. In many countries a differentiation between the roles of TSOs (see next

paragraph) and CAMs may not exist.

o Corrects short-term and long-term imbalances of energy demand and supply caused by

retailers (whether due to incorrect energy reservation or unexpected demand/supply

patterns), e.g. by using cold reserves, and forwards incurred costs to retailers → balancing of

Control Area

o Actively trades on wholesale market

Transmission System Operator (TSO): According to the Article 2.4 of the Electricity Directive

2009/72/EC (Directive): "a natural or legal person responsible for operating, ensuring the

maintenance of and, if necessary, developing the transmission system in a given area and,

where applicable, its interconnections with other systems, and for ensuring the long- and

short-term (minutes) ability of the system to meet reasonable demands for the transmission

of electricity".

In addition, some use case specific roles may have to be acknowledged, which are detailed in Section

9.1.2.

9.1.2 Main Value Flows

The value flows capture relationships among actors. Here we identify three most significant value

flows and the main issue each of them addresses: (1) stability of the grid, (2) energy generation,

trading and delivery, and (3) regulation.

Stability of the grid: The CAM cares about stability on medium and long term and short term by

acting on the wholesale markets based on monitoring data and information exchanged with DSOs in

order to constantly balance the grid. The DSO and TSO globally coordinate agreements ensuring the

stability of the grid on coarser granular level, i.e. typically the interface is the CAM role.

Energy generation, trading & delivery: Generated resources are directly marketed on (wholesale)

marketplaces or first aggregated and then traded. Retailers then buy required energy to satisfy the

demands of their eyeball consumers. In some cases, energy may directly be sold by the aggregators

to industrial end consumers.

Regulation: The energy market is closely followed by regulatory authorities. The VN captures the

most important relationships where regulators (directly or indirectly) influence the business activities

of roles.

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9.2 SmartC2Net Value Network

With the transition towards smart grids, the resulting Value Network (cf. Figure 58) has to reflect a

series of changes.

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Energy

Generators

/ DER

Energy

Consum er

Energy

Aggregator

EV

Charging

Stat ion

Operator

I nfSP

DSO

Retailer

W holesale

Market

Vendors

Forecaster( Consult ing/

W eather /

Dem and) $

$ +

mete

ring in

fo.

charge/

reserve

e.g

., loo

kup s

erv

ice

$ /

adve

rtis

em

ent

metering

infr. etc.

energy &

flexibility$energy

$

(dynamic) self-control

incentives ($)

& metering inf.

Energy

Prosum er

Energy

Consum er

… "eye ball" consumer

(own demand)

CAM … (central) grid role

Charging

Stat ion Op.

… use case

specific role

reliability 1

2

1

2

Metering &

compensation claims

3 compensation if not

agreement compliant

Com .

Netw ork

Ow ner

Com .

Service

Provider

network infr. $

4 demand & supply

forecasts

4

license $

5 Paid network services,

QoS guarantees, ...

5

attacks

faulty devices

human errors

communicationproblems

...

energy

$

energy

trade

modifieddemand

$

Regulator

$

$

registration$

$

TSO

Regulator

Com .

Netw ork

… communication

services

… public authorities

${ dynamic

trade-off

consumption –

trading

energy &

(dyn.) pricing

(semi-

automatically)

modified

supply

Control

Area

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6 Trade energy/flexibility

for balancing the CA

6

metering

$

$

energy

long-term trading/reservat.

{all-smart-grid-actors}

Aggregated

EV Charging

I nfra-

st ructure

Managem ent

trade energy

7

7 Collective

energy trading

Legend

Figure 58 – SmartC2Net Value Network (with special consideration of chosen use cases)

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Main aspects of these changes are summarized as follows:

The dynamicity of interaction, information exchange and trading is most significantly

changed. More fine-granular interaction and cooperation is required – being enabled via

improved communication capabilities, i.e., introduction of communication service provider

to the VN

Capabilities for influencing demand and supply are substantially improved

Finer-granular metering capabilities in cooperation with modern communication

technologies are newly introduced

Balancing requirements in the distribution grid are substantially changed

The role of DSOs becomes more demanding when facing more DERs to be accommodated for

while maintaining a stable grid with the required power quality. Combined with liberalized

market structures, more intensive interaction between DSOs and retailers may be required;

however the current regulation of DSO role does not provide for it

In the LV grid, aggregation of all information from grid assets for technical and commercial

purposes. Data exchange between different actors on the LV grids and upstream.

More systematic integration of Electrical Vehicle (EV) charging, PVs, wind turbines, and

different size DERs or important new energy usages on the LV, MV and HV is required to

meet soaring demands and mitigate arising grid issues

Usage, collection and transmission of more information lead to more regulatory

requirements in respect of data management

Attack scenarios may also shift from physical-only scenarios to new constellations involving

communication networks and data manipulations.

On the other hand, the long-term business perspective modelled by the interaction of CAMs, DSOs,

and TSOs (see description below) will remain similar to the classical grid case.

The remainder of this section is organized in the description of entities and main value flows

depicted in the SmartC2Net Value Network representation.

9.2.1 Entities (Revised)

There are two different types of consumers: on the one-hand eyeball consumers aiming at satisfying

their own demands and on the other hand use case-specific additions.

9.2.1.1 “Eye ball” consumer

o Energy consumer: same as in the classical grid.

The energy consumer may (but need not) provide Smart Metering Data to all

interested parties and might allow flexible load scheduling (this a specific

function for use cases such as AMR / CEMS) as a 3rd party service for energy

efficiency.

o Energy prosumer: same as classical grid.

Adaptation of demand to the local supply may be offered as a 3rd party

service with high automation requirements

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E.g. via virtual metering, prosumers may directly trade their

resources with other consumers/prosumers. Virtual metering may

also be used in the case of separation of supply and demand location

of individual prosumers.

Dynamic demand & supply adaption as a service requires

customers/prosumers willingness to adapt their behaviour based on

perceived economic benefits.

9.2.1.2 Energy sector

Energy Generators / Distributed Energy Resources (DER): see classical grid.

o More flexibility and interaction with DSO may be required for balancing the grid

Energy Aggregator: see classical grid.

The energy supply is then utilised by market entities (trading & sales):

Wholesale Market / Local Markets: A (wholesale) market where it is possible to buy and sell

energy and demand flexibility

o See classical grid above

o Trading of local energy flexibilities / local balancing & shorter-term trading are

essential new features

More dynamicity required esp. for distribution grid resources trading, e.g. in

seconds, and supply-demand balancing, e.g. in milliseconds.

Higher importance of efficient trading of ancillary services (flexibilities), i.e.

entity requiring flexibility the most should be rewarded with an efficient

assignment (requires incentives and suitable auction mechanisms)

Retailer


o More efficient trading may be required with ability to snatch more efficient deals on

better metering/ forecasting

The following central grid roles are recognized:

Distribution System Operator (DSO): In addition to the classical case, the DSO is now

responsible for two-directional power flows and regional grid access for DERs, grid stability,

efficient integration/regulation of renewables at the distribution level and regional load

balancing (please also see CAM) for the case of smart grids. The DSO has central

responsibility for maintaining the stability and power quality in the distribution grid. Under

changed regulatory constraints, DSOs may aim at directly controlling local demand and

supply, offered as a special service. Beyond that, the use of metering information now

shared with the CAM (see next paragraph) may be diversified. The costs for maintaining the

power quality may also be diversified based on the new role of local supply or trading

(supply incentives; retailers compensation etc.) facilitating DSOs in active control of power

lines and flows in the distribution grid.

o Pricing updates (incentives) e.g. in milliseconds for balancing parts of the distribution

network

Control Area Manager (CAM):

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o Smart Grid: Clearer incentives / compensation mechanisms for unbalanced energy

demand & supply by retailers are required

Transmission System Operator (TSO): see classical grid.

9.2.1.3 Telco sector (complementary roles)

Communication Service Provider (CSP): The smart grid is about embedding advanced

communications and remote sensing into the electric power system to improve reliability,

optimize energy delivery, engage the consumer and expand the usage of renewable energy

resources. Wireless embedded machine-to-machine (M2M) solutions for utility automation

are becoming more important as they relate to the smart grid. Leveraging on established

relations with end user for wireless connectivity and on cost efficiency for deploying and

offering connectivity to DSO and TSO, Telecommunications companies will be playing an

increasingly greater role in common applications such as Automatic Meter Infrastructure,

Distribution Automation, Demand Response, supervisory control, data acquisition for SCADA,

building management, home energy management and electrical vehicle charging [FIER11].

The CSP is therefore the operator of the required communication network, i.e., provider of

telecommunication services like wireless access to meters. The CSP is also responsible for

providing Internet access to end customers at Customer Premises (CPs) – this may be

handled as bundled service or as independent contracts.

In addition the CSP can supply connectivity services to the DSO and the TSO for monitoring

and managing smart grid equipment. Depending on business conditions the connectivity

services provided could extend to a deeper integration between the CSP network and its

enablers and the DSO/TSO communication network and grid. In this case CSP can also enable

a series of market driver positively affecting the smart grid business case.

Communication Network Owner (CNO): CNOs are the owners of the communication

network on which the CSP operates. Often one entity may overtake both roles.

Vendor: Vendors provide infrastructure for communication networks, but also for metering

the grid and/or its data processing. Communication network vendors may act in the role of

the CSP by operating a network for a communication network owner (or several owners) due

to efficiency reason. This is a standard model common to mobile networks today.

3rd Party Forecasting Service: Beyond technical components assisting the forecasting of

supply or demand patterns in the future, external consulting services may be used.

9.2.1.4 Use case-specific roles

o EV Charging Station Operator (CSO): Operator of a Charging station – which is an

electrified parking lot with several Charging Stations (CSs) – is independent or owned

by Energy provider, DSO, etc. Thus, providing an equivalent service to filling stations

– please refer to the use case description for more detailed definitions.

Somehow cooperates with DSOs (ensuring sufficient energy can be delivered

to cars of customers)

Reservation system or comparable mechanism for balancing demand

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Establishment of a sustainable business case, e.g., by combination with other

services like paid parking lots or garages

o E-Mobility Service Operator: System including services for EV owners to find charging

stations as well as for the charging station operator to manage several charging

stations (may sometimes legally be owned be CSOs or CS chains).

Balancing of customers according ‘available energy’ (grid utilization, charging

slots, …)

Guidance of customers / providing lookup services, e.g. integration with

SatNavs or apps and the related integration with navigation service

providers.

Potential issue: Who operates this service across different charging station

providers? (Problem of universal access of information)

Link to Information Service Providers potentially visualizing or using provided

data

o Information Service Providers: Commonly available services provided by a third

party, e.g. weather information needed to predict PV production or Aggregated EV

Charging Infrastructure Management (see below):

May require access to data → potential problems with confidentiality of

information or varying market interests (e.g. competitors may not agree on a

single platform)

Openness of market access may be nutritious, but difficult

E.g., Aggregated EV Charging Infrastructure Management: Collectively acts on

energy markets, especially intra-day markets, for individual CSOs by

aggregating their energy demand requirements and placing bids at

marketplaces. If no such role exists, retailers may provide the energy directly

to CSOs–see Energy Consumer.

9.2.2 Main Value Flows (Revised)

The following paragraphs summarize and aggregate the main value flows in the VN. Further details

can be inferred from the visual representation as well as from the entity descriptions:

Stability of the grid: The CAM cares about short-, medium-, and long-term stability by carefully

monitoring the grid and influencing other actors to modify the demand or supply levels. Thus, CAMs

get active on the wholesale market, exchange information with DSOs and set energy reservation

requirements for retailers. CAMs finally correct imbalances between supply and demand through

reserves from the wholesale market. DSOs in contrast are responsible for assuring grid stability and

power quality on dynamic short-term basis in the distribution grid. Thus, in smart grids they may

actively influence demand of end customers or supply on the axis of DERs. This may be based on

incentives or regulated. The DSO and TSO globally coordinate agreements ensuring the stability of

the grid on coarser granular level, i.e. typically the interface is the CAM role. Long-term wholesale

agreements may also be dedicated to the role of TSO (besides the active balancing of the CAM role).

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Energy generation, provisioning & trading: In the case of SmartC2Net, DERs will have higher

importance and thus need to be better integrated and (decentrally) managed.

Regulation: Additional regulation may be necessary regarding the DER connection rules, the safety

and security of the smart grid and the protection of individuals, e.g., privacy and sensitive handling of

information.

Communication in Smart Grids: Communication networks are required for all smart grid entities due

to their requirement for exchanging information. All entities not operating their own network are,

hence, customers of a CSP. The most direct relationship may be established with DSOs probably

managing a series of sites with devices requiring the access to reliable communication infrastructure.

Nevertheless, also charging station owners, consumers, etc. may deliver information required for

balancing the smart grid or may receive information as added value (e.g. consumption statistics and

price signals). An important relationship also exists to consumers who themselves require Internet

access, but also Customer Premises Equipment (CPE) for realizing SmartC2Net use cases may require

connectivity. Thus, communication services essentially link the smart grid entities.

EV Charging: The central place for charging is the CS where demand and supply also need to be

balanced or coordinated. The purchasing of energy for each CS is typically collectively handled. This is

further assisted by a macroscopic view such as provided by E-Mobility Service Operators potentially

redirecting costumers in early stages. Such services may require a listing fee (registration) to be part

of a nation wide / EU-wide / global assistance. Eye-ball consumers may also pay fees for better

support or may have to consume advertisements (may not be possible on typical SatNav devices)

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10 Annex B - UC templates

10.1 USE CASE NAME: Medium Voltage Control

10.1.1 Description of the Use Case

10.1.1.1 Name of Use Case

Use Case Identification

ID Domain(s)

Name of Use Case

Distribution Grid

Management / Smart

Substation Automation/

Distributed Energy

Resources

Voltage Control in Medium Voltage Grids connecting DERs

10.1.1.2 Version Management

Version Management

Changes / Version Date Name

Author(s) or Committee

Domain

Expert

Area of

Expertise /

Domain /

Role

Title Approval

Status draft, for

comments, for

voting, final

v.0

based on the

CEN/CENELEC/ETSI

SGCG Use Case

WGSP-0200

25/01/2013 Giovanna Dondossola RSE

Roberta Terruggia RSE

ICT for

Distribution

Grid

Operation

and

Substation

Automation

Researchers Draft

v.1 11/03/2013 Giovanna Dondossola RSE


Draft

v.2

EAB feedback,

protocols

15/05/2013 Giovanna Dondossola RSE


Final

10.1.1.3 Scope and Objectives of Use Case

Scope and Objectives of Use Case

Related business case

Scope The introduction of Distributed Energy Resources (DERs) can influence the status of the

power grid. The behaviour of DERs can affects the capacity of the DSO to comply with the

contracted terms with the TSO and directly the quality of service of their neighbour grids.

DSO has to face with units whose behaviour is both unknown and uncontrollable and

investments on conventional reactive power control devices in substations may become

ineffective. This difficulty to meet the contracted terms and the quality of service standards

not only could be transferred into charges to the DSO, but also affects the TSO operation

because the scheduled voltages at grid nodes could not be observed and voltage stability

problems cannot be managed properly. In order to maintain stable voltages in the

distribution grid the Voltage Control function is introduced. This main goal can be extended

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in order to achieve other important objectives as supply ancillary services, minimize the cost

and the KWh consumption, provide reactive power support for distribution buses, reduce

energy losses and provide compatible combinations of the above objectives.

Objective The primary aim of this use case is to address the communication needs of a Voltage Control

(VC) function for medium voltage grids connecting Distributed Energy Resources (DERs). The

actions derived from the VC function are evaluated with the objective of defining an ICT

architecture suitable for security analysis. The VC use case is a didactic case illustrating the

need of cyber security in smart grid applications, first because its behaviour influences both

system operation and economy, second because of the high level inter-networking

requirements of its ICT architecture.

10.1.1.4 Narrative of Use Case

Narrative of Use Case

Short description – max 3 sentences

The Medium Voltage Control function optimizes the voltage profile and power flows to maintain a stable voltage at

customer site in a defined area of the distribution grid with distributed generators, flexible loads and other deployed power

equipment. The function involves different data flows both from internal and external actors that must be considered in

order to perform a cyber security analysis. The loss or corruption of the measurements and set points may cause cascading

effects with high impact on the power grid.

Complete description

The connection of DERs to medium voltage grids can influence the status of the whole power grid. Voltage profiles and

power flows in active distribution grids change dynamically, mainly because of the stochastic production of the renewable

sources. The power injected by distributed generators can overload feeder segments or raise the voltage beyond the limits

in parts of the grid. The behaviour of DERs can affect both the capacity of the DSO (Distribution System Operator) to comply

with the terms contracted with the TSO (Transmission System Operator) and the quality of service of their neighbour grids.

The automatic voltage regulation provided by the OLTCs (On Load Tap Changer) of the substation transformers and

compensation measures, as used in passive grids, may be insufficient to grant the supply requirements established by the

norm EN 50160. This difficulty to meet the contracted terms and the quality of service standards beside causing the

imposition of sanctions to the DSO, can also affect the TSO’s operation because grid nodes cannot maintain the scheduled

voltages and voltage stability problems cannot be managed properly.

The main purpose of the VC function is to monitor the status of the active distribution grid from field measurements and to

compute optimized set points for DERs, flexible loads and power equipment deployed in HV/MV substations. The function

monitors the voltage and power flow in critical points of the controlled grid. The status of the grid based on actual

measurements and grid topology as required by the control algorithm, is computed by a State Estimator, that creates an

accurate profile from available measurements. Optimization of the voltage profile is acquired by controlling reactive and

active power injection by distributed generators and energy storage equipment, and setting OLTCs and switched capacitor

banks. Besides, costs of control actions and load/generation forecasts in the area have to be taken into account to select

the appropriate control strategy. Considering the hierarchical architecture of the electric grid, a controlled area is a Medium

Voltage (MV) section of the grid, typically underlying a primary (HV/MV) substation and having points of common coupling

with low voltage distribution buses or the upper level grid.

The VC function is performed by the Controller on a node of a HV/MV substation control network. Figure 59 schematizes

the Voltage Control Function: starting from the inputs the function computes a Voltage profile and makes it operative by

sending set points to customer and utility devices.

In order to pursue the previously defined objective, the Controller computes the optimal states of the controllable devices

across the substation area. In a generic case, the optimization algorithm takes into account combinations of

technical/economic objectives and constraints, including requirements on power exchange at points of common coupling

with the upper grid. As part of a coordinated optimization process within the substation, suitable devices for control actions

are selected. Depending on the grid area to which the voltage control is applied and on the objectives of the optimization

process, generation/load units can be controlled directly by the Controller or via the Flexibility Operator (in the following

referred with the term Aggregator).

After every change of equipment state, due to an explicit request or to an automatic action, the substation is notified the

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new state or the operating point, inclusive of the information on available regulation ranges. If during the execution of the

optimization steps the topology of the grid changes, the application is interrupted and the solution is re-optimized. If during

the execution some operations are unsuccessful, then the solution is re-optimized excluding the malfunctioning devices. If

some controllable devices are unavailable for remote control, then the solution does not involve these devices but takes

into account their reaction to changes in operating conditions.

The main actors and how they interact are presented in

Figure 60. The control strategy requires information from sources external to the DSO domain. From the operational point

of view, the optimization function has to accept voltage regulation requests by the TSO whenever a transmission grid

contingency requires the application of preventive measures to avoid voltage collapse. Load and generation forecasts are

used to optimize the operation of distributed devices, while the economic optimization is based on market prices and DER

operation costs. A first major design assumption underlying the use case’s ICT architecture is that all the information

related to DER features, grid topology changes, requests by TSO, load/generation forecasts and market data are sent to the

Controller by the DMS (Distribution Management System) application in the DSO centre. This design choice preserves the

integrity of the distribution grid operation by limiting the number of communication channels at the substation level and

concentrating the communications with the external actors at the DSO centre level. In absence of criticalities, the VC

function is executed periodically (e.g. every 15 minutes) for optimization purposes, but its execution can be triggered

asynchronously by critical events (e.g. under/over voltage event, TSO requests, grid topology changes). The total response

time from the start of the elaboration to the end of the set point actuation, depends on actuation time constants of OLTC

and DER power electronics plus the communication overhead.

Figure 61 shows the UML Use case diagram where the actors and the (sub-)use case are depicted considering a normal

behaviour. The actors interact with the (sub-) use case “Voltage Control” that represents the main functionality of the

system.

Figure 63 shows how the actors and the functions of the Medium Voltage Control Use Case can be mapped to the smart

grid plane of Smart Grid Architecture Model (SGAM).

The main elements of the use case are placed into the Distribution and DER domains. The zones varying from the Market

zone of the Aggregator to the Field zone of control functions of the OLTC, Capacitor bank, DER and Flexible Load.

In the middle we have the Generation and Load Forecast functions placed in the cell Enterprise zone/Distribution domain

and integrated with the DMS.

TSO EMS and DMS Control Functions are in the Operation zone hosting all the active grid operation functions. The

Substation Automation System and the Voltage Control Functions with the SetPoint Calculation are placed in the Station

zone.

The architectural layout deployed for implementing the VC function depends on the responsibilities attributed to the use

case roles according to country-specific organisation and regulation. This Use Case assumes that the control of HV/MV

substations is under the responsibility of the DSO who has a network connection to the DERs. The data supply chain of the

VC function depends on several communication links enabling remote access from systems outside the perimeter of the

DSO operation. The DMS application in the DSO centre has permanent links (the green WAN in Figure 64) with four actors

(TSO, Aggregator, Generation Forecaster and Load Forecast); the Controller in the DSO substation has permanent

communication links (the red WAN in Figure 64) with third party DERs, possibly deploying heterogeneous communication

technologies, located in different geographical areas; communications between DMS and the substation automation and

control system through the DSO SCADA links (the blue WAN), eventually based on telecommunication services.

As seen the Medium Voltage Control use case involves different main area networks: Aggregator, TSO, DSO (Center), (DSO)

Substation, DER and Flexible Load networks. The communications can be intra area or inter area. In Figure 65 we observe a

schema of the different areas and of the communications. It is possible to identify the following different networks:

NW1: Wired LAN local to Substation, distinguishing different network segments that corresponds to separate

control layers, e.g. station, bay and process layers

NW2: Wireless/wired WAN that may use commercial cellular or private wireless technology. This network

connects the substation with the DER sites

NW3: Private wired WAN. This network connects the DSO Operation Center with the Substation. It may be based

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on dedicated communication services via wired WAN

NW4: Wired LAN local to DSO Operation Center, distinguishing different network segments that corresponds to

separate operation layers, e.g. DMS and MDMS

NW5: Wired WAN. This network connects the TSO Center with the DSO Operation Center. It may be based on

dedicated communication services via wired WAN

NW6: Public IP. This network connects the Aggregator with the DSO Enterprise Center

NW7: Wired WAN. This network connects the DSO Operation Center with the DSO Enterprise Center. Most

probably it will be based on dedicated communication services via wired WAN.

Note that the networks involving DER and Aggregator are WAN network and can be wired or wireless. In particular for the

network to the DER the wireless technology is desirable.

The main control and communication components are depicted in Figure 66. In this use case different communication

protocols are involved, in Figure 66 the main of them are represented.

The sequence diagram of the VC function is presented in Figure 69 where the information exchange is addressed.

One of the inputs of the VC function is the generation forecast: Figure 67 shows a sketch of the generation estimation

function. Figure 68 shows the sequence diagram with the main information flow.

By focusing on the core of the VC scheme, it is clear that the correct computation of the optimal set points depends on the

provision of correct operation and economic data from all communication sources. A malicious attack to one of the

communication links may cause either the loss of input data (generation forecasts, economic data from the Aggregator, TSO

requests, topological changes), or the loss of output setpoints, or the introduction of faked input/output values/setpoints.

The use case highlights sample communication attacks that may lead the control function to diverge from optimum set

point values or, even worse, to produce inadequate set points with cascading effects on connected generators. In Figure 62

an anomalous scenarios is represented through the (mis)use case diagram. The figure depicts how a (mis)user can attack

the system. Such abnormal scenarios to the VC function support the evaluation of the impact on the supplied power that

will depend on the size of the grid section, the amount of installed distributed generation, the control network topology

over the power grid structure and the extension of the attack itself. The evaluation of attack processes to the VC function is

aimed at identifying security controls to counteract those attacks which might compromise the voltage profile.

The global impact of such cyber attacks to the Voltage Control functions on the supplied power depends on the grid size

and the amount of distributed generation, both these factors varying on a geographical base. By focussing on the Italian

profile and targeting the integration of an amount of renewable energy of about 40 GW within 2020, the distribution grid

development plan requires the building of about 10% new HV/MV substations.

The analysis of the attack impact on the supplied power depends on the control network topology on the top of the power

grid structure. By applying an extreme case approach, the impact value associated to future smart grids endowed with the

Voltage Control function depends by the extension of the attack effect. For example, an attack to the DER network could

cause the disconnection of all the generators connected to the MV feeders of a given substation (e.g. less than 100MW); an

attack to the substation networks could be able to disconnect one or several substations (e.g. less than 1 GW); a control

centre attack, causing the disconnection of all the substations in a given control centre, could count 6 GW of unsupplied

power.

By mapping such impact values on the power scales identified by the SGIS working group, it results that the impact of those

cyber attacks to the communications of the Voltage Control functions may be associated, respectively, to the Medium, High

and Critical impact levels.

In section 4.2 of the template some anomalous scenarios are analysed with focus on the effect of different attacks (floding

based DoS and fake messages) to the communications involved in the Use Case. The related Sequence Diagrams are

presented in Figure 70, Figure 71, Figure 72, Figure 73 and Figure 74.

10.1.1.5 General Remarks

General Remarks

10.1.2 Diagrams of Use Case

Diagram of Use Case

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Third party DER Distributor’s device

Voltage Profile

Grid Topology

Fieldmeasurem

ent

Marketprices

ResourceOperation

costs

TSOsignals

LoadForecast

Voltage Control

Function

GenerationForecast

Figure 59 - Voltage Control

Aggregator TSOGeneration

Forecast

DMS

Medium Voltage Grid Controller (MVGC)

DER OLTCCapacitor

BankFlexible Load

Load Forecast

Figure 60 - Voltage Control - Actors Interactions

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Figure 61 - Voltage Control - Use Case Diagram

Figure 62 - Voltage Control - Use Case Diagram - attack scenarios

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Market

Enterprise

Operation

Station

Field

Process

Generation Transmission Distribution DERCustomerPremise

Aggregator

Load Forecast

Gen. Forecast

TSOEMS DMS

Sub.Autom. System

MVCG

OLTC CtrlCapacito Bank Ctrl

DER Ctrl

Flexible Load Ctrl

Figure 63 - Voltage Control – Mapping on SGAM

Aggregator

Secondary SubstationAutomation&Control

Primary Substation Automation&Control

Enterprise Comm. Network(WAN)

DER Flexible loads EnergyStorage

DSO

TSO

GenerationForecast

Transmission Grid

HV

MV

MV

LV

Control Control Control

Control

Control

Control

Control

Control

Technical Flexibility&Performance


& Flexibility

Load Forecast

Control

Control

OLTC

Control

Capacitor Bank

Control

DER Comm. Network(WAN)

DSO Comm. Network(WAN)

Figure 64 - Voltage Control - Overview of involved communications

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TSO Center

Aggregator Site

DER SiteDSO/Customer


DSO Substation

FieldSubstation

AutomationSystem

DMS

Flexible load siteDSO/Customer

DSO Enterprise CenterEnterpriseSystems

NW6

NW5

NW7

NW3

NW2

NW4

NW1 MVGC

Figure 65 – Voltage Control – Communications

Figure 66 – Voltage Control - Component Layer

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Automated

Meter Management

Weather Forecast

Grid DB Management

Generation Forecast

DMS

Figure 67 - Generation Forecast

Figure 68 - Generation Forecast - Sequence Diagram

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Figure 69 – Voltage Control - Sequence Diagram

Figure 70 - Voltage Control - DoS Attack to DER

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Figure 71 - Voltage Control - DoS Attack to MVGC

Figure 72 - Voltage Control - Fake DER Set point

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Figure 73 - Voltage Control - Fake DER Set point (Man in the Middle)

Figure 74 - Voltage Control - Fake TSO signal

10.1.3 Technical Details

10.1.3.1 Actors: People, Systems, Applications, Databases, the Power System, and Other

Stakeholders

Actors

Grouping (Community) Group Description

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Actor Name see Actor List

Actor Type see Actor List

Actor Description see Actor List

Further information

specific to this Use Case

Meter Data Management

System

System System for validating, storing,

processing and analyzing large

quantities of meter data

Weather forecast System Provides weather forecast used for

different utility business processes

(scheduling, planning, operational

planning, operation ...)

Grid DB Management System System that manages the DB of the

electric network consistency

Aggregator Role Offers services to aggregate energy

production from different sources

(generators) and acts towards the grid

as one entity, including local

aggregation of demand (Demand

Response management) and supply

(generation management). In cases

where the aggregator is not a supplier,

it maintains a contract with the

supplier.

Transmission System

Operator (TSO)

Role According to the Article 2.4 of the

Electricity Directive 2009/72/EC

(Directive): "a natural or legal person

responsible for operating, ensuring the

maintenance of and, if necessary,

developing the transmission system in

a given area and, where applicable, its

interconnections with other systems,

and for ensuring the long-term ability

of the system to meet reasonable

demands for the transmission of

electricity". Moreover, the TSO is

responsible for connection of all grid

users at the transmission level and

connection of the DSOs within the TSO

control area.

Generation forecast System Computes forecast for renewable

generation in controlled area based on

weather forecast

Load forecast System Computes forecast for load in

controlled area

DMS System Distribution Management System a

system which provides applications to

monitor and control a distribution grid

from a centralized location, typically

the control center. A DMS typically has

interfaces to other systems, like an GIS

or an OMS

Medium Voltage Grid System Medium Voltage Grid Controller

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Controller (MVGC) implementing the Voltage Control

Function

Substation Automation

System (SAS)

System Substation Automation System

implementing the automation

sequences and the control functions of

interfacing process level control

devices

DER Device Generic Distributed Energy Resource -

"DER devices are generation and

energy storage systems that are

connected to a power distribution

system" (IEC 62357)

Flexible load Device Load that can be modulated

Capacitor bank Device A switchable bank of shunt capacitors. May be generalized as

Shunt Compensator

(A section of a shunt

compensator is an

individual capacitor or

reactor). (IEC 61970)

OLTC Device On Load Tap Changer. Mechanism for

changing transformer winding tap

positions.

10.1.3.2 Preconditions, Assumptions, Post condition, Events

Use Case Conditions

Actor/System/Information/Contract Triggering Event Pre-conditions Assumption


The Voltage Control algorithm

applies to a MV grid under a

Primary Substation and operate

only controllable device directly

installed on the MV grid.

DER ancillary services

The use of DER ancillary services

is defined by contracts or regional

regulation.

Substation Control System can

operate only DERs having

subscribed some agreement with

Distribution System Operator.

Generally only a subset of

installed DER is controllable.

Costs of DER ancillary services

The algorithm takes in account

dispatching costs for DER active

and reactive power.

Different remuneration of

ancillary services offered by DERs

are possible:

- administrated price: fixed price established by Authority bodies;

- Market scheme: DER operators

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fix prices for their services (not fully realistic for MV networks);

- Mixed approach.

DER storage

It is assumed that storage units

are owned and operated directly

by the Distribution Company in

order to increase grid control

capabilities.

There is an integral constraint on

control strategies to maintaining

the same level of charge on 24

hour time horizon.

DMS

DMS knows:

- DERs features (Nominal power, Capability, Controllability, etc.)

- Load forecast for each MV load,

- Generation forecast for each DER, controllable or not.

Grid measurements

Grid measurements are available

from substation devices and from

DERs.

State Estimation

State estimation of controlled MV

grid under a Primary Substation is

performed by either the Medium

Voltage Grid Controller or the

Control Centre (DMS).

Execution of control voltage

algorithm

Control loop is executed:

- Periodically (15’) - On critical

under/overvoltage event - On grid topology change

Signals related to grid stability

(normal, critical, alarm, …)

coming from TSO can influence

the execution of control voltage

algorithm (e.g. changing

optimization criteria or overriding

commands).

Generation Forecast

Forecasts updated every 12 hours

with granularity of 1 hour. Valid

for 36 hours

10.1.3.3 References /Issues

References

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No

.

References Type Reference Status Impact on Use Case Originator/O

rganisation

Link

1 European Report SGCG/M490/E_Smart

Grid Use Case

Management Process

— Use Case

Collection,

Management,

Repository, Analysis

and Harmonization

Public Specification CEN/CENELE

C/ETSI

2 Use Case SGSP Working Group

Use Case WGSP-0200

Public Specification CEN /

CENELEC /

ETSI

3 European Report SGCG/M490/B_Smart

Grid Report First set

of Standards Version

2.0 Nov 16th

2012

Public Standards CEN/CENELE

C/ETSI

4 International

Standard

IEC 60870-5-104 IS Communication IEC TC57

5 International

Standard

IEC 61850(-7-420) IS Communication /

Data Model

IEC TC57

6 International

Standard

IEC 62351 TS Security IEC TC57

7 International

Standard

NIST SP800-53 & 800-

82, IR 7628

SP, IR Security NIST

8 International

Standard

IEC 61970 IS Data Model IEC TC57

9 International

Standard

IEC 61968 IS Data Model IEC TC57

10 Article Monitoring and

Control of Active

Distribution Grid

Public Specification CIRED 2012 http://www.cired2

012-workshop.org/

11 Article Impact of DER

Integration on the

Cyber Security of

SCADA Systems –The

Medium Voltage

Regulation Case

Study

Public Security Issue CIRED 2012 http://www.cired2

012-workshop.org/

12 Project FINSENY Public Specification EU FP7

project

http://www.fi-ppp-

finseny.eu/

10.1.3.4 Further Information to the Use Case for Classification / Mapping

Classification Information

Relation to Other Use Cases Grid monitoring and control, State Estimation, Generation management, Load management, Storage management,

Advanced DMS and Distribution Automation, Grid emergency management, Power quality, Weather forecast, market signal

Management

Level of Depth

High Level

http://www.cired2012-/




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Prioritisation

Needed for countries with high DER penetration on distribution grid

Generic, Regional or National Relation

Generic

View

Technical

Further Keywords for Classification

Voltage and VAR Control, DER Management, Cyber security, ICT architectures

10.1.4 Step by Step Analysis of Use Case

Scenario Conditions

No. Scenario

Name

Primary

Actor

Triggering

Event

Pre-Condition Post-Condition

4.1.1 Generation

Forecast

Estimation

Generation

forecast

Periodically New info available New generation forecast available

4.1.2 Information

acquisition

DMS Periodically /

Asynchronous

TSO signal or new

info

Info integrated with local data

4.1.3 Forwarded info DMS Periodically

/Asynchronous

DMS receives new

data

Medium Voltage Grid Controller obtains

input for the control algorithm

4.1.4 Grid

measurement

dispatch

Third party DER

/ Distributor’s

device

Periodically Field dispatches

new measurements

Medium Voltage Grid Controller obtains

new measurements

4.1.5 Forward of grid

measurements

Medium

Voltage Grid

Controller

Periodically Substation Control

System has new

SCADA and DER

measurements

DMS receives new measurements

4.1.6 Execution of

control voltage

algorithm

Medium

Voltage Grid

Controller

Values out of

range

The state is not

acceptable

Computation of new setpoints (horizon 24

h)

4.1.7 Set Setpoints Substation

Automation

System /

Medium

Voltage Grid

Controller

New setpoint New setpoints

computed

Devices change their settings

4.2.1 DoS Attack: DER DER Attacker launches

an attack

Missing measurements

4.2.2 DoS Attack:

Medium Voltage

Grid Controller

Medium

Voltage Grid

Controller

Attacker launches

an attack

Missing measurements

4.2.3 Fake DER Setpoint DER Attacker launches

an attack

Abnormal behaviour

4.2.4 Fake DER Setpoint

(Man in the

Middle)

DER Attacker launches

an attack

Abnormal behaviour

4.2.5 Fake TSO signal Medium

Voltage Grid

Controller

Attacker launches

an attack

Incorrect State estimation leads to

abnormal behaviour

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10.1.4.1 Steps – Normal

Scenario 4.1.1

Scenario

Name :

Generation Forecast Estimation

Step

No.

Event Name of

Process/Activit

y

Description of

Process/Activity

Servic

e

Information

Producer

(Actor)

Informatio

n Receiver

(Actor)

Informatio

n

Exchanged

Technical

Requirement

s R-ID

1 Periodic Meter data

collection

Collecting data from

meters about the

grid status

GET Meter Data

Management

System

Generation

Forecast

Grid status

2 Periodic

every 12

hours

Weather data

collection


weather forecast

service about the

weather forecast

GET Weather

forecast

Generation

Forecast

Weather

forecast

3 Periodic Grid topology

data collection


Grid DB

Management about

the grid topology

GET Grid DB

Management

Generation

Forecast

Updated

Grid

Topology

4 Periodic

every 12

hours

Forecast

estimation

Calculate the

forecast of active

power generation

EXECU

TE

Generation

Forecast

Generation

Forecast

Updated

Generation

forecast for

each DER

Scenario 4.1.2

Scenario

Name :

Information acquisition

Ste

p

No.

Event Name of

Process/

Activity

Description of

Process/Activity

Service Information

Producer

(Actor)

Information

Receiver

(Actor)

Information

Exchanged

Technical

Requirements

R-ID

1 TSO

changes

algorithm

paramete

rs

(Asynchr

onous)

TSO

message

Send signals influencing

the execution of

control voltage

algorithm (e.g.

changing optimization

criteria or overriding

commands).

REPORT/C

REATE

TSO DMS TSO Signals

2 Periodic

every 12

hours

DER

Generatio

n Forecast

Update Generation

forecast for each DER

CREATE Generation

forecast

DMS Updated

Generation

forecast for

each DER

3 Periodic Load

Forecast

Update load forecast CREATE Load

forecast

DMS Updated

Load

forecast

4 Periodic Energy /

Ancillary

Costs

Update Energy /

Ancillary Costs

CREATE Aggregator DMS Updated

Energy /

Ancillary

Costs

5 Periodic Load/Gen

Customer

program

Programs of load and

generation of the

customers

CREATE Aggregator DMS Load/Gen

Customer

program

Scenario 4.1.3

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Scenario Name : Forwarded info

Step

No.

Event Name of

Process

/Activity

Description of

Process/Activity

Service Informatio

n

Producer

(Actor)

Information

Receiver

(Actor)

Informatio

n

Exchange

d

Technical

Requirements R-

ID

1 TSO

signal

received

TSO

changes

algorithm

paramete

rs

(Asynchr

onous)

TSO

signal

forward

Send signals influencing

the execution of control

voltage algorithm (e.g.

changing optimization

criteria or overriding

commands).

CREATE DMS Medium

Voltage Grid

Controller

TSO Signals

2 Periodic Update

DER

features

informati

on

Update Features

information (Nominal

power, Capability,

Controllability, etc.) of

DER installed on the MV

grid

REPORT DMS Medium

Voltage Grid

Controller

Updated

Load/DER

Features

3 Grid

topology

changes

Update

grid

change

Send configuration

change of the controlled

MV grid (grid topology

reconfiguration, new

DER/load installation)

REPORT DMS Medium

Voltage Grid

Controller

Updated

Grid

Topology

4 Periodic

every 12

hours

Forward

generatio

n

forecast

Update Gen forecast for

each DER

CREATE DMS Medium

Voltage Grid

Controller

Updated

Gen

Forecast

for each

DER

5 Periodic Forward

load

forecast

Update Load / forecast

for each Load

CREATE DMS Medium

Voltage Grid

Controller

Updated

Load

Forecast

for each

Load

6 Periodic Forward Energy /

Ancillary

Costs

Update Energy /

Ancillary Costs

CREATE DMS Medium

Voltage Grid

Controller

Updated

Energy /

Ancillary

Costs

Scenario 4.1.4

Scenario

Name :

Grid measurement Acquisition

Ste

p

No.

Event Name of

Process

/Activity

Description of

Process/Activity

Service Informatio

n

Producer

Information

Receiver

(Actor)

Informatio

n

Exchange

Technical

Requirements

R-ID

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Page 128 of 244

(Actor) d

1 Periodic

seconds

OLTC

Measure

ments

OLTC Measurements CREATE OLTC

Substation

Automation

System

OLTC

Measurem

ents (P,Q,V)

2 Periodic

seconds

Capacitor

bank

Measure

ments

Capacitor bank

Measurements

CREATE Capacitor

bank

Substation

Automation

System

Capacitor

bank

Measurem

ents

(P,Q,V)

3 Periodic

seconds

DER

Measure

ments

DER Measurements CREATE DER Medium

Voltage Grid

Controller

DER

Measurem

ents

(P,Q,V)

4 Periodic

seconds

Flexible

load

Measure

ments

Flexible load

Measurements

CREATE Flexible

load

Medium

Voltage Grid

Controller

Flexible

load

Measurem

ents

(P,Q,V)

5 Periodic

seconds

Field

Measure

ments

OLT/Capacitor bank

Measurements

CREATE Substation

Automatio

n System

Medium

Voltage Grid

Controller

OLTC/Capa

citor bank

Measurem

ents

(P,Q,V)

Scenario 4.1.5

Scenario

Name :

Forward of grid measurements

Step

No.

Event Name of

Process

/Activity

Description of

Process/Activity

Service Informatio

n

Producer

(Actor)

Information

Receiver

(Actor)

Informatio

n

Exchange

d

Technical

Requirements

R-ID

1 Periodic Measure

ments

forward

Medium Voltage Grid

Controller forward the

SCADA and DER

measurements

CREATE Medium

Voltage

Grid

Controller

DMS SCADA and

DER

measureme

nts

Scenario 4.1.6

Scenario

Name :

Execution of control voltage algorithm

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

(Actor)

Information

Receiver

(Actor)

Information

Exchanged

Technical

Requirements

R-ID

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10.1.4.2 Steps – Alternative, Error Management, and/or Maintenance/Backup Scenario

Scenario 4.2.1

Scenario Name: DoS Attack: DER

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Requirements

R-ID

1 Attacker

launches

DoS Attack The attack floods

the DER with

CREATE Attacker DER Anomalous

traffic

1 Periodic

every 15

/Triggered

by grid

topology

changes

minutes /

State Estimation Execute State

Estimation

EXECUTE Medium

Voltage Grid

Controller

Medium

Voltage Grid

Controller

Estimation

of the Grid

state

2 State from

state

estimation

Check state Check if the

parameters are within the limits

EXECUTE Medium

Voltage Grid

Controller

Medium

Voltage Grid

Controller

Estimation

of the Grid

state

3 Triggered

by TSO

signal /

Set point

calculation

Optimized Set

point calculation

Algorithm

(horizon 24 hours)

EXECUTE Medium

Voltage Grid

Controller

Medium

Voltage Grid

Controller

Set point

Calculation

Scenario 4.1.7

Scenario

Name :

Set Setpoints

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

(Actor)

Information

Receiver

(Actor)

Information

Exchanged

Technical

Requirements

R-ID

1 New set

point

OLTC / Capacitor

bank Set point

Send OLTC/

Capacitor bank

Set point

CREATE Medium

Voltage Grid

Controller

Substation

Automation

System

Capacitor

bank Set

point ΔQ +/-

ΔV +/-

OLTC Set

point

ΔV +/-

2 New set

point

OLTC / Capacitor

bank Set point

Send OLTC /

Capacitor bank

Set point

CREATE Substation

Automation

System

OLTC /

Capacitor

bank

Capacitor

bank Set

point ΔQ +/-

ΔV +/-

OLTC Set

point

ΔV +/-

3 New set

point

DER Set point Send DER Set

point

CREATE Medium

Voltage Grid

Controller

DER

DER Set

point

ΔP +/-

ΔQ +/-

4 New set

point

Flexible load Set

point

Send flexible load

Set point

CREATE Medium

Voltage Grid

Controller

Flexible load

Flexible load

Set point

ΔP +/-

ΔQ +/-

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an attack abnormal

messages

2 DER is

under

attack

DER

communications

down

The Medium

Voltage Grid

Controller doesn’t

receive the

measurements

from DER

GET DER Medium

Voltage Grid

Controller

Missing

measurements

Scenario 4.2.2

Scenario Name : DoS Attack: Medium Voltage Grid Controller

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Requirements

R-ID

1 Attacker

launches an

attack

DoS Attack The attack floods

the MVGC with

abnormal

messages

CREATE Attacker Medium

Voltage Grid

Controller

Anomalous

traffic

2 Medium

Voltage Grid

Controller is

under attack

Medium Voltage

Grid Controller

communications

down

The DER and

SCADA

measurements

don’t reach the

DMS

GET Medium

Voltage Grid

Controller

DMS Missing

measurements

Scenario 4.2.3

Scenario Name : Fake DER Setpoint

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technic

al

Require

ments

R-ID

1 Attacker

launches

an attack

Fake setpoint The attacker

sends a fake

setpoint to DER

CREATE Attacker DER DER Setpoint

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2 DER

changes

its

settings

Abnormal

execution

DER receives a

setpoint and

changes its

settings

EXECUTE DER DER Settings

Scenario 4.2.4

Scenario

Name :

Fake DER Setpoint (Man in the Middle)

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Requirements

R-ID

1 Medium

Voltage

Grid

Controller

sends

DER

setpoint

Message

interception

Attacker

intercepts the

setpoint message

from Medium

Voltage Grid

Controller

CREATE Medium

Voltage Grid

Controller

Attacker DER setpoint

2 Attacker

changes

message

Message change Attacker changes

the values of

setpoint

EXECUTE Attacker Attacker Fake DER

setpoint

3 Attacker

forwards

the fake

message

Message forward Attacker forwards

the fake message

CHANGE Attacker DER Fake DER

setpoint

4 DER

changes

its

settings

Abnormal

execution

DER receives a

setpoint and

changes its

settings

EXECUTE DER DER Settings

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Scenario 4.2.5

Scenario Name : Fake TSO signal

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Requirements

R-ID

1 Attacker

launches an

attack

Fake TSO signal Attacker sends a

fake TSO signal

message

CREATE Attacker Medium

Voltage Grid

Controller

TSO signal

2 Receive of

TSO signal

State Estimation MVGC executes

algorithm

EXECUTE Medium

Voltage Grid

Controller

Medium

Voltage Grid

Controller

Incorrect

state

estimation

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10.1.5 Information Exchanged


Name of Information

Exchanged

Description of Information Exchanged Requirements to information data R-ID

Updated Grid Topology Information regarding the characteristics of the

grid elements (nodes, loads, generators and

lines). Configuration change of the controlled

MV grid (grid topology reconfiguration, new

DER/load installation)

Standard Protocols: IEC 60870-5-104, TCP/IP

Weather forecast Weather forecast, weather data Standard Protocols: Web services, TCP/IP

TSO signals Signal influencing the execution of control

voltage algorithm (e.g. changing optimization

criteria or overriding commands).

Voltage setting, Reactive Power setting, AVR

inclusion/exclusion

Standard Protocols: IEC 60870-5-104, TCP/IP

Updated generation forecast Active power production plan on an hour base

on a time horizon of 36 hours (36 values of

active power). Generation coefficient 0<C<1

Standard Protocols: IEC 61968-100, IEC 60870-

6, IEC 60870-5-104, TCP/IP

Updated load forecast The future load is predicted on the basis of

reference loads (seasonal patterns), stochastic

fluctuations, active demand effects, weather

forecast, day type. Load coefficient 0<C<1

Standard Protocols: IEC 61968-100, IEC 60870-

6, IEC 60870-5-104, TCP/IP

Updated Energy/Ancillary costs Costs for the modulation of active and reactive

power and reward schemes

Standard Protocols: IEC 62325, IEC 61968-100,

IEC 60870-6, IEC 60870-5-104, TCP/IP

Updated Load/DER Features Update Features information (Nominal power,

Capability, Controllability, etc.) of DER

Standard Protocols: IEC 61968, IEC 61850-7-

420, IEC 60870-5-104, TCP/IP

OLTC Measurements and States Voltage values, AVR included/excluded Standard Protocols: IEC 61850-8-1, IEC 60870-

5-104, TCP/IP

Capacitor bank Measurements and

States

Voltage values, Reactive power values,

included/excluded

Standard Protocols: IEC 61850-8-1, IEC 60870-

5-104, TCP/IP

DER Measurements Voltage values, Active and Reactive power

values

Time Requirements: 4 sec [refresh time on the

CC HMI]

Standard Protocols: IEC 61850-7-420, IEC

61850-8-1, IEC 61850-90-5, IEC 61850-90-1, IEC

60870-5-104, TCP/IP, UDP/IP

Flexible load Measurements Voltage values, Active and Reactive power

values

Standard Protocols: IEC 61850-8-1, IEC 61850-

90-5, IEC 61850-90-1, IEC 60870-5-104, TCP/IP,

UDP/IP

Grid state estimation Estimation of the current state of the grid Standard Protocols: IEC 61970, IEC 61968, IEC

60870-5-104, TCP/IP

Capacitor bank Set point Capacitor bank Set point ΔQ +/-

ΔV +/-


61850-8-1, TCP/IP

OLTC Set point OLTC Set point

ΔV +/-


61850-8-1, TCP/IP

DER Set point DER Set point

ΔP +/-

ΔQ +/-


60870-5-104, IEC 61850-90-5, IEC 61850-90-1,

IEC 61850-8-1, TCP/IP

Flexible load Set point Flexible load Set point

ΔP +/-

ΔQ +/-


61850-90-5, IEC 61850-90-1, IEC 61850-8-1,

TCP/IP

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10.1.6 Common Terms and Definitions

Common Terms and Definitions

Term Definition

AVR Automatic Voltage Regulator


DMS Distribution Management System

DSO Distribution System Operator

EMS Energy Management System

GIS Geographic information system

HV High Voltage

IP Internet Protocol

LAN Local Area Network

MV Medium Voltage

MVGC Medium Voltage Grid Controller

OMS Outage Management System

OLTC On Load Tap Changer

PEV Plug-in Electric Vehicle

P(f) Active power P(f) is a function of frequency f. The active power generated and active power consumed

at each moment should be equal. A deviation from this equilibrium results in a deviation from the 50 Hz

frequency. So keeping this equilibrium between active power generation and consumption means

maintain frequency

Q(U) Reactive power Q(U) is a function of voltage U. The reactive power on the grid should be kept in

equilibrium. Reactive power is an extra load for the grid, leaving less capacity for active power, resulting

in a local voltage drop. So keeping reactive power in equilibrium means maintaining voltage.

SAS Substation Automation System

SGAM Smart Grid Architecture Model

TSO Transmission System Operator

V Voltage

VPP Virtual Power Plant


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10.2 USE CASE NAME: Electrical Vehicle Charging in Low Voltage Grids




ID Domain(s)

Name of Use Case

Distribution Grid Electric Vehicle Charging in Low Voltage Grids


Version Management

Changes /

Version

Date Name


Domain

Expert

Area of

Expertise /

Domain /

Role

Title Approval

Status draft, for comments,

for voting, final

0.2 Jan.2013 SB, JG/FTW draft

0.4 Feb/Mar

13

SB, JG/FTW draft

1.0 8.03.13 SB/JG FTW V1.0 released

1.1 27.03.13 SB Changes after

review

1.2 25.04.13 SB EAB feedback

1.3 31.05.13 SB/JG Add “Aggregated

charging

infrastructure

entity”, price info


Scope and Objectives od Use Case

Related business case

Scope Low voltage distribution grids

Markets

Distribution grid operation Objective Satisfy the charging demands of arriving EVs in such a way that the

generated and stored energy is efficiently used and the grid is not overloaded.

Enable electrical vehicle charging to become a flexible consumption resource that can be used to balance energy and power resources in the LV grid along with decentralized production as well as other loads (e.g. households).

Provide a system architecture enabling interoperation between new actors such as charging station operators (charging aggregator) and their connection to existing actors such as DSOs and energy providers.

Enable DSOs to monitor state of low voltage grid under EV load conditions.



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Charging of electrical vehicles in low voltage grids is challenging due to highly synchronized demand patterns of charging as

well as high loads. This use case covers the controlled charging of electrical vehicles in a low voltage grid, taking into

consideration the EV owner, a charging infrastructure owner/provider as well as the DSO. Regarding the latter, the use case

aims to utilize the high demand flexibility of the charging process to balance grid and energy in the low voltage grid.


The overall electrical vehicle charging deployment overview is depicted in

Figure 75. It consists of 5 main parts listed in the following:

1) A Charging Station installation is provided that can be represented by a) private charging scenario with a few charging spots. The private sector at home includes garages, carports and parking grounds around single or multi-family homes. b) In the semi-public sector, the charging stations are operated for example in parking grounds or underground parking of hotels, banks, gastronomy companies, shopping centres or at car dealerships c) be represented by a public charging scenarios where several charging spots are controlled by a charging station controller. The charging spots are public, meaning that a public group of EV owners can charge their electrical vehicles at them.

2) Local LV Grid resources being local production and storage that will operate in an interplay with the electrical vehicle charging to provide energy management services towards the grid as well as cost and environmentally efficient charging operations.

3) Secondary Substation containing DSO equipment to manage metering, monitoring as well as grid control.

4) The DSO domain representing the link of the low voltage grid to the DSO operations; including requirements towards significant low voltage grid sub-systems such as electrical vehicle charging.

5) The “Cloud” representing services in the open networks/internet used to: a) provide a market for trading energy and flexibility resources, b) to enable information needed for local control (e.g. weather) and finally, c) for a charging station operator to coordinate the allocation on its CS controllers, define prices for its services and provide routing services for the EV owners/drivers (using the Charging Station Routing). For this service, the CSO would pay.

Details of the individual components/systems are described in the actor lists.

For the given electrical vehicle deployment scenario a total of 7 networks have been identified. A

network here represents a given network infrastructure with a specific purpose. In reality, each

network may be realized by different or similar technologies or several networks may be operated as

a single network. This identification of different networks enables to define different deployment

scenarios and resulting networking architectures in which advanced control tasks must operate. A

scenario and its analysis can help to clarify which networks are involved and thereby how the

communications may affect the scenario. The networks are defined as follows:

Network 1 – Metering. The metering network is owned by the DSO or a metering infrastructure

operator. It is a network used to collect smart meter data measurements at the last mile. The smart

meter network is usually based on powerline communications, cellular or proprietary wireless

solutions.

Network 2 – Sub-station network. This network is an internal bus-network in the secondary

substation. It is owned by the DSO and connects equipment in the substation. May be based on

Ethernet.

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Network 3 – Public IP Network. The Public IP network represents the open Internet. This is the

easiest platform for third parties to provide their services, such as routing services to EV users, or

weather services. The public IP network can be based on everything from wired xDSL based

technologies to cellular data access.

Network 4 – eCar Communication. This communication is between the charging station and the

electrical vehicle itself. The communication is usually wired and may be running through the charging

cable itself. Information about the state of the car, e.g. state of charge, preferred charging speed,

etc. may be provided through this network.

Network 5 – Private IP Network The private IP network represents a local network infrastructure

utilized by the infrastructure owner to connect local elements. For instance charging spots may be

connected to the charging station through this network. It could be based on PLC or Ethernet.

Network 6 - LV Grid Management Network. The DSO may choose to deploy an own closed

networking architecture used for grid components to communicate. Thus could be to communicate

with inverters, protection devices as well as sensors in the grid.

Network 7 – DSO Network. The DSO network is the network connecting the DSO management and

control systems (e.g. SCADA) towards the secondary sub-station. These networks are usually closed.

They may be based on fibre put out by the DSO as the cables to substations were put in the ground.

To define how these components are foreseen to interact over the provided networks, a total of

three main scenarios have been defined. 1) A charging scenario, 2) an energy and power

management scenario and 3) a market scenario. Each scenario is described pictorially through a use

case diagram identifying actors, their sub-use cases and their interactions to support the scenario

and a message sequence diagram to define how components and actors communicate. These

scenarios are briefly described in the following:

Charging Scenario:

See Figure 76 and Figure 77.

This scenario has the EV Owner/driver as the main actor. The scenario defines how the EV

Owner/driver is interested in charging his/her electrical vehicle and having it fully charged when

needed again. In the private charging case it is clear where to charge. In the public charging case, also

a pre-charging phase exist where EV owners/drivers can search for charging stations.

The charging operations are controlled locally by a charging station controller. The controller is

responsible for trying to make charging cheapest (for the EV owner if he/she pays after energy

consumption and/or the charging station (infrastructure) operator, if he/she provides a flat-rate

charging service. The control further needs to take into consideration local limitations provided by

the DSO such as grid limits or load objectives provided by the operator to maintain the service quality

and help improve utilization of local resources.

The pre-charging phase called reservation is not mandatory, but allows a better planning of the

resources at a public charging station and improves the probability to find available resources when

the EV user tries to plug in. The use case continues with plug-in in which the schedule is updated. A

periodic event calculates the grid situation taking into account generation, consumption and storage

and might lead to a plan update. The charging period ends with the stop charging event created

either by completion of the plan or by a plug-out and leave event.

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Energy and Power Management:


This scenario considers the DSO as the main actor. Based on local LV grid conditions as well as

requirements on MV level, the DSO tries to balance the power resources in the low voltage grid. The

goal is to make sure the grid operation is within acceptable limits, to ensure that grid components

are not overloaded and also to make sure that enough energy can be provided to supply the charging

service. The DSO provides requirements towards local production, storage and consumption. E.g. the

DSO will ensure to signal to the charging station controller when grid power resources are sparse or

the voltage is too low as well as to request certain load flexibility behavior that enables to balance

the grid.

Energy Market Operation:


This scenario covers the interactions between the actors of this use case in relation to the market.

Important aspects here are a distribution market where not only energy is sold, but also flexibility.

I.e. the charging station operator may include in the business model to sell flexibility while

maintaining the interests of his/her customers to charge vehicles when they are to be used. The DSO

can purchase such flexibility on the market or in a direct business relationship with the CSO to have

power quality management resources. The scenario also considers interactions with new energy

providers/aggregators that have local resources that should be utilized locally, e.g. for charging, or, in

combination with charging, to provide services towards the MV grid level.

The functions of the use case are depicted in Figure 82 based on the Smart Grid Architecture Model

(SGAM). Most functions are provided in the distribution domain to monitor and manage the Low

Voltage grid considering load and flexibility of EV charging processes. In the DER and Customer

Premise Domain exist local energy application controllers as well as monitoring (e.g. metering and

events by registering EVs) and actuation (start/stop charging, change charging intensity, …). In the

market zone the aggregation of LV grid energy resources (production, storage) and demand

resources provides a market to exchange such resources.


General Remarks

-


Diagram of Use Case

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DSO

Local LV Grid

ressources (DER)


EVprivch


Cloud

NW1: Metering

NW2: Sub-station NW

NW3: Public IP Network

NW4: eCar

CommunicationNW4: eCar

Communication

NW5: Private IP Network

NW6: LV Grid Management Network

Private

Charging

SpotEVpubch

Public

Charging

Spot

NW7: DSO Network

Charging

Station

Controller

Public

Smart

Meter

Photovoltaic

Inverter

Battery

Inverter

Private

Smart

Meter

Energy

Management

Gateway

Metering

Head-end

System

Metering

Aggregation

(NNAP)

Low Voltage

Grid Controller

Meter Data

Management

System

Distribution

Management

System

(SCADA)

Information

Services

Market

(Distribution/Transport)

Charging

Station

Routing &

Reservation

Aggregated

Charging

Infrastructure

Management

Figure 75 Use case components and Networking Connectivity Options

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Page 140 of 244

Energy

Providers

EV Owner/

Driver

Charging

Station

Operator

Reserve Charging

Space

Plug in/out EV

Negotiate energy

prices

Provide Charging Control

Directives (price motivation)

Provide Charging

Infrastructure

Provide Energy

Sell Energy

Manage Energy and

Power (Quality)<<include>>

Charge

DSO

<<

inclu

de

>>

<<in

clud

e>>

<<include>>

<<include>>

Metering<<

exte

nds>

>

<<include>>

<<include>>

E-mobility

Service

Operator Figure 76 - Use Case Diagram for EV charging scenario

FP7-ICT-318023/ D1.1 ver 2

Page 141 of 244

Availability

Check

Charging

Station

Routing &

Reservation

Charging

Station

Controller/

Gateway

Metering

Aggregation

Low Voltage

Grid Controller

Smart

MeterEVpubch

Charging

SpotEV Owner

/Driver

Energy

Providers

Find Charging Station with Context

Available Resources?

Available Power & Load ObjectivesAvailable Place, Energy (& Price)

Plugin & Context (SOC, Stay duration)

Reservation

Availability

Check

Market ConditionsNegotiate Price

Price Signals

Plugin & Context

Ideal Charging

Periods/Price

Signals

Planning

Planning &

Estimation

Start/Stop Charging

AP Update

...

...

Plugout

Metering Metering Data

Energy Consumption

Billing

Charging Opportunities

Start/Stop Charging

Available Power & Load Objectives


Available Resources? Current & Future

Demand, Flexibility

Planning

Start/Stop Charging

Start/Stop Charging

Aggregated

Charging

Infrastructure

Management

Available Resources? Current & Future

Demand, Flexibility

Figure 77 - Message Sequence Diagram for EV charging scenario

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Page 142 of 244

Energy

Providers /

Aggregators

Charging

Station

Operator

Manage Power in Grid

(Plan & Control)

DER Owner

Battery (DER)

Owner

Provide Energy

Provide &

Plan Load

<<inclu

de>>

<<include>>

Consumers

Provide Load

Metering and Sensoring

<<include>>

DSO

Provide & Plan

Energy

<<include>>

<<

inclu

de

>>

Figure 78 - Use Case Diagram for energy and power management scenario

FP7-ICT-318023/ D1.1 ver 2

Page 143 of 244

LV Grid Mgmt.

Charging

Station

Controller/

Gateway

Low Voltage

Grid Controller

DSO

Photovoltaic

Inverter

Battery

InverterInformation

Services

GIS Data,

Operation

Objectives and

set-points

Monitoring &

Alarms

Data for

prediction

(Metering,

Weather)

Power & Energy

Control Loop

Metering

Aggregation

Production Now

Current and Planned State

(SoC, Charging, Providing)

Load & Production

Prediction

Available Resources? Current & Future Demand, Flexibility

Production Limits

Planning &

Estimation

Storage Control Objectives

Storage Control


Consumption Now

Planning & Control

DMS

(SCADA)

Figure 79 - Message Sequence Diagram for energy and power management scenario

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Page 144 of 244

Energy

Providers/

Aggregators

Charging

Station

Operator

DER Owner

Battery (DER)

Owner

Generate &

Sell Energy

Sell Load Flexibility

<<inclu

de>>

Energy

Customers

Load

MeteringDSO

<<include>>

<<

inclu

de>

>

Buy Reserves for Balancing

EV Owner/

Driver

Sell Charging Service

Buy Charging Service

Buy Energy

<<include>>

<<include>>

Buy Energy

Figure 80 - Use Case Diagram for Energy Market scenario

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Sell Production

Meter Data

Management

DMS/

SCADA

Charging

Station

ControllerDSO ConsumerCharging

Station

Operator

Battery OwnerDER Owner

EV Owner/

Driver

Energy

Providers &

Aggregators

Market

(Distribution

/Transport)

Sell Decentralized

Energy Production

Sell Aggregated Energy

Production

Buy Energy & Demand Flexibility

Power/Energy Control Need

Sell Demand Flexibility

Sell Decentralized

Energy Production

Sell Decentralized

Energy Production

Sell Demand Flexibility

Billing

Billing

Billing

Negotiate Prices

Price Signals

Ideal Charging Periods/

Price Signals

DSO Demands

Sell Demand

Flexibility

Metering

CSO Demands

Price Signals

Billing

Billing

Aggregated

Charging

Infrastructure

Management

Figure 81 - Message Sequence Diagram for Energy Market Scenario

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Market

Enterprise

Operation

Station

Field

Process

Generation Transmission Distribution DER Customer

Premise

Low Voltage Grid

Control

Metering Production

Control

Home

Control

Actuation &

Monitoring

Actuation &

Monitoring

Actuation &

Monitoring

Metering

Aggegation

Information

Services

DMS

Transport & Distribution Market

Charging

Infrastructure

Management

Meter Data

Management

System

Charging

Station

Control

Charging Station Operation

Energy Provider / Aggregator

Figure 82 - SGAM Function Layer

Charging

Station

Controller

Metering

Aggregation

Low Voltage

Grid ControllerMDMEVpubch

PV

Inverter

Start/stop

charging

Metering Data Error

Get Consumption now

Data missing error

Get production now

MDM Error

Query MDM

Estimate load

Under

uncertainty

Reduced available power

Change

schedule

Figure 83 – AS3 Metering information interrupted

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Charging

Station

Controller

Low Voltage

Grid ControllerEVpubch

PV

Inverter

EV Owner

/Driver

Start/stop

charging

Heartbit

timeout

Schedule

With power

constraints

New reservation/plugin

Refuse temporarily (service

restricted)

Heartbit

Figure 84 – AS2 LVGC-CSO connection interrupted

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DSO

Charging

Station

ControllerLow voltage

grid controller

E-mobility

Service

Operator

Charging

Station

Routing &

Reservation

PS2.10

Charging

spot

PS2.6

PS1.8

PS 1.6, PS 1.9

PS1.6, PS1.9

PS 2.4

PS 2.9

DMS

PV Local

Production

Battery

Storage

PS

2.8

PS

2.7

PS1.

1, P

S1.

3

PS

1.2,

PS

1.5

Aggregator & CSO

PS

3.3

MarketPS3.5

PS

2.5

PS3.4

Meter

Meter Aggregation

PS 1.11

PS1.

11

PS

3.6

Aggregated

Charging

Infrastructure

Management

PS1.3

PS1.4, PS1.7

Figure 85: Diagram of the Interactions described in section 4.1



Stakeholders

Actors





Further information

Components associated

Electrical Vehicle

Owner

Person The owner or user of an

electrical vehicle demanding

charging services.

Requests charging service

(demand, time window),

EV or Plug-In Hybrid

Electrical Vehicle

(PHEV)

-

Charging Station

Operator (CSO).

Role Operator of a Charging station

(which is an electrified parking

lot with several Charging Spots)

is an independent enterprise or

owned by Energy provider,

DSO, etc.

- it aggregates EV load, offers

demand flexibility.

- Builds and maintains the

- CS controller - Charging spots

(CS), sub-meters - Grid node/main

meter

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charging schedule for all EVs

connected to its charging spots

- Receives from DSO (LVGC)

actual and predicted available

power profile

- reports the EV load profile

- handles user payment for EV

services

- clearance with energy

provider or market

Every Charging station in a LV

grid, even from different CSOs,

becomes allocated an amount

of energy resources

proportionally to the number

of charging spots.

E-Mobility Service

Operator

Role - Lists the best charging station

locations to EVs,

- Handles reservations

- Receives from CSPs

availability updates

- May be owned by

charging station

operator.

- Reservation mgmt.

- Routing server

Distribution System

Operator (DSO)

Role - limits charging capacity of CS

- LVGC receives load max/min profile from primary station

- LVGC receives price information from

- LVGC calculates set points for aggregators, DG, storage

- LVGC/sec.station, - Primary station - Grid

Energy Provider Role - Provides energy to customers.

- Sends price signals, receives load information,

- May be an aggregator An Energy Provider may also be an actor aggregating many distributed energy resources.

Aggregator Role An entity able to aggregate

several production units as well

as demand flexibility. This

enables the aggregator to

operate on the market.

- May be an energy provider as well as provider of demand flexibility.

Consumer Person Other consumers in a LV grid

that provide loads and needs

to be considered in the

power/energy management

-

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views.

Battery (storage)

Owner

Role receives set points for Storage

charging and discharge from

DSO (LVGC)

- Fixed Storage, controller, meter

Charging Spot (CS) System - A dumb unit connecting an EV electrically to the grid via a plug. It is controlled by a home gateway/charging station controller.

-

Distributed Energy

Resource (DER)

System - receives set points from DSO (LVGC)

- reports generation

PV system, Wind mill

Inverter power Control,

meter

Meter Data

Management

System (MDMS)

System System for validating, storing,

processing and analyzing large

quantities of meter data.

-

Distribution Market System A market where it is possible to

buy and sell energy and

demand flexibility

-

Information Services System Commonly available services

provided by a third party. E.g.

weather information needed to

predict PV production.

-

Charging Station

Routing &

Reservation

System System including services for

EV owners to find charging

stations as well as for the

charging station operator to

manage several charging

stations.

-

Aggregated Charging

Infrastructure

Management

System System enabling to manage

several charging stations

providing interfaces to external

sub-systems (routing +

reservation), monitoring and

management of flexibility.

Operated by the CSO

Distribution

Management

System (DMS)

System Overall grid monitoring and

control system for the

distribution grid providing high

level control objectives

towards lower grid levels.

Part of the SCADA system of the DSO.

Metering Head-end

System (HES)

System Central component residing at

the DSO.

Provides interfaces towards

and MDM system.

-

Metering

Aggregation OR

System Local aggregation point OR

Neighbourhood Network

Ref: Smart Meters Co-ordination Group -

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NNAP Access Point (NNAP) is a

functional entity that provides

access to one or more LNAP’s,

metering end devices,

connected to the

neighbourhood network (NN).

Smart Metering Use Cases

Low Voltage Grid

Controller (LVGC)

System Local DSO driven controller

located in the secondary sub-

station.

The LVGC implements a Substation Control System.

Photovoltaic

inverter

System PV Inverter enabling to reduce

the production output to the

grid if strictly needed.

-

Battery Inverter System Battery Inverter also including

a control system to manage the

batteru charging/discharging.

In cases where a large storage

exist in the LV grid, this

inverter is usually providing

main control functions – e.g.

frequency stability control.

-

Charging Station

Controller

System A control box controlling when

charging spots can be activated

and at which charging speeds.

It plans charging in relation to

DSO’s and CSO’s requirements.

-

Energy Management

Gateway

System Same as charging station

controller. Only controls a few

charging spots. Is also

responsible for controlling

other in-household flexible

loads and production. It is also

known and referred to as a

Home Gateway due to its

capabilities for home

automation beyond energy

management.

This system implements the Customer Energy Management System.

EV System Electrical vehicle or Plug-In

Hybrid Electrical Vehicle (PHEV)

-

Smart Meter (SM)

System A smart meter providing

production and consumption

values. May also enable

advanced sensoring providing

active/reactive production,

frequency monitoring, voltage

-

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monitoring, etc.


Use Case Conditions


Charging Station Infrastructure

Management

It serves several charging stations and

their CSOs for instance redirects

reservation requests from traveling EV

users to free charging stations. This

actor is optional, a simpler approach

would be to find charging stations as

POI using the navigation system (but

without knowing their availability)

Reservation in PS1

It is assumed for now that reservation

is done without any commitment or

payment

User registration, payment in PS1

It is important that any EV owner

receives service, even she is not

registered at a certain CSO or system

wide (openness). Since a full charging

costs about 3-4€ and parking in the

same order, we recommend simpler

prepaid approach. However payment

is not considered here in detail.


References

No. References Type Referen

ce

Status Impact on Use Case Originator/Or

ganisation

Link

1 EV Communication

Standard

DTS/IT

S-

00100

31

V0.0.1

Prelimina

ry draft

Communication ETSI ETSI ITS

WG1

2 ISO/IEC 15118

Road vehicles –

Communication

protocol between

electric vehicles and

grid

IEC

15118

Final Describes the

interface between an

electric vehicle and

the charging spot

including securit

IEC

3 Standard

IEC

62196

(1-3)

1- Final

3 – exp.

Dec 13.

Standard for electrical

connectors and

charging modes for

electrical vehicles.

IEC IEC

4 E-Mobility Use cases Work in

progress

E- Mobility co-

ordination group (EM-

CEN- http://e

mic-

FP7-ICT-318023/ D1.1 ver 2

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CG),

SG-CG/M490 smart

grids

CENELEC bg.org/fi

les/plugi

n-

index.pd

f



Relation to Other Use Cases

Will be a sub-use case of the generic Low Voltage grid use-case. Will share functions with the house-

hold use case as these operate in the same domain.

Level of Depth

High Level

Prioritisation

Under conditions of large penetration of electrical vehicles (pure as well as plug-in hybrids)

management of charging is needed unless large investments in grid reinforcements are made. The EV

control will provide an interesting new resource for demand flexibility due to the ability of absorbing

large quantities of energy as well as high flexibility in consumption.


Generic

View

Technical, partially market options


Electrical Vehicle Charging, Demand Flexibility, Low Voltage Grid Management, Aggregator Role,

Charging Station Operator.


Scenario Conditions

No. Scenario

Primary

Actor(s)

Triggering Event Pre-Condition Post-Condition

PS1 EV Charging EV owner EV owner seeks a

charging station

EV and owner are valid

(credentials).

EV owner has a valid

reservation at a certain

charging station, has travelled

there and successfully received

desired charge.

PS2 Energy &

Power

Manageme

nt

DSO Periodical update or

dramatic change in

available power

resources

Data Links are OK,

agreements exist with

charging station

operator and energy

resource providers to

enable control.

No alarms, i.e. the grid power

quality is maintained and

energy resources are available

for future power management.

PS3 Energy

Market

Energy

Providers,

Aggregators

Periodic, based on

types of market

Established business

relations between

primary actors and a

Price agreements and billing

closed.

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Scenario Conditions

No. Scenario

Primary

Actor(s)


and CSO market platform

AS1 Plugged in

Charging

aborted

EV owner Plugin Event Reservation OK Av. Power alarm, no or

partial charging, plugout, leave

AS2 EV demand

control

disrupted

CSO Detection of Comm.

failure

Data flow LVGC CSO

interrupted

Schedule with reduced load

until the condition ends

AS3 Metering

Data flow

disrupted

DSO

(LVGC)

Detection of

missing data

Grid state is OK Conservative Available

Power estimates are

distributed until the

condition ends


For a better understanding of the following steps, the main interactions are depicted in Figure 85.

Scenario (see Figure 76 & Figure 77, Figure 11)

Scenario PS1: EV Charging

Step

No.

Event Name of

Process/

Activity

Description of

Process/Activity

Service Information

Producer

(Actor)

Information

Receiver

(Actor)

Information

Exchanged

Technic

al

Require

ments

R-ID

PS1.1 Charging

Station

Lookup

Find Charging

Station

Identify charging

station and

provide user

context

(expected stay

duration, needed

charge, …)

Optional EV Owner

+ EV

Charging

Station

Routing

Charging

Context.

PS1.2 Availability

Check

Availability

Check and

Response

The Charging

Station

Infrastructure

Mgmt. identifies

charging station

options and

informs EV

Owner.

Optional Charging

Station

Routing

EV Owner Available

charging

opportuniti

es.

PS1.3 Reservatio

n

Charging

Station

Routing

receives

reservation

request and

EV user selects

charging station,

arrival time

energy demand.

May get

additional

Optional EV Owner

+ EV

Charging

Station

Controller

Reserve

message

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redirects it to

CSO

information such

as routing advice.

PS1.4 Process

Reservatio

n

Reservation

handling at the

charging

station

Update Schedule,

allocate

resources

Charging

Station

Controller

Charging

station

Routing

Schedule

update and

resource

availability

PS1.5 Reservatio

n

successful

CSO returns

OK

OK response.

Charging station

Routing updates

its CS availability

list

Optional Charging

Station

Controller

EV Owner Reservatio

n

confirmatio

n

PS1.6 Plugin EV Plugin An EV plugs into

the Charging Spot

and provides

additional/updat

ed context

information

EV Charging

Station

Controller/

Gateway

Updated

Charging

Context.

PS1.7 Plugin

Handling

Re-planning of

resources

The Charging

Station Controller

(re-)/plans the (if

needed) charging

plan

Charging

Station

Controller

Charging

Station

Routing

Schedule

update and

Resource

availability

PS1.8 Start/Stop

Charging,

Change

Charging

Speed

Charging

Process

Management

The charging

station controller

starts/stops

charging as well

as manages

charging speed

Charging

Station

Controller

EV Start/Stop

commands.

Updated

charging

speeds.

PS1.9 Plug-out EV Plugout The EV plugs out

of the Charging

Spot. The

Charging Station

Controller

adapts.

EV Charging

Station

Controller

Plug-out

event

PS1.1

0

Periodic Metering Send charging

metering data to

meter

aggregation

system for billing

purposes

Smart

Meter

Meter

aggregatio

n

Meter data

PS

1.11

Periodic Metering Read meters for

state estimation

Meter

Aggregatio

n

LVGC Relevant

Meter Data


Scenario PS2: Energy Balancing& Power Management

Ste

p

No.

Event Name of

Process/Activit

y

Description of

Process/Activity

Servic

e

Informati

on

Produce

r (Actor)

Information

Receiver (Actor)

Information

Exchanged

Technic

al

Require

ments R-

ID

- Update Provide update The DMS provides DMS LVGC - Setpoints

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LVGC

operatio

n

of the LVGC

operation

settings

information to the

LVGC to update high-

level operation

objectives as well as

changes in data

models such as grid

topology information,

newly connected

charging stations etc.

- Settings

- Data

models (e.g.

grid

topology)

- Update

LVGC

predictio

n

informati

on

Provide update

of the LVGC

data for

prediction

Information is pushed

(or pulled) from

information services

that are useful in the

LV grid management

operation such as

weather data.

Informa

tion

Services

LVGC - Weather

data

- Expected

load profiles

- …

2.1 Periodic Load and

Production

Prediction

The LVGC predicts the

expected production

and load a predefined

time into the future

for planning purposes

LVGC LVGC Updated

prediction

profiles

2.2 Periodic Metering Current load in

different busses of

the LV grid

Meterin

g

Aggrega

tion

LVGC Load

information

on busses

2.3 Periodic Distributed

Generation

Current generated

power in different

busses of the LV grid

Meterin

g

Aggrega

tion

LVGC Generated

information

on busses

2.4 Periodic Set Available power

for EV charging to all

charging stations

LVGC Charging

Station

controller

Available

power

profile

2.5 Periodic Control

Re-planning

The LVGC plans the

local power and

energy resources to

maintain service

quality within

acceptable limits. It

may perform this

planning based on

setpoints from the

MV level.

LVGC LVGC Power and

Energy

control plan

in the LV

grid.

2.6 Periodic Charging Load

profile update

CSO updates the

schedule considering

the preferred loads

from aggregator and

the CSO available

power constraints

Chargin

g

Station

Controll

er

LVGC EV Loads

update

2.7 Overvolt

age/Curr

ent

Limit

Production

If overvoltage/

over-current events

occur the LVGC can

choose to limit the

production in critical

LVGC Photovoltaic

Inverter

Production

Limits

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periods to maintain

power quality.

2.8 Service

quality

deviation

s

Change battery

control

objectives

A local battery in the

grid can be requested

to change its

objectives to

increase/decrease

load to aid in the

operational

parameters

LVGC Battery Inverter Setpoints/o

bjectives for

battery

control

2.9 Power

quality

deviation

s

Change

demand

objectives

The LVGC can request

flexibility services

from the Charging

Station Controller to

increase/decrease

load now and in the

future. This involves

hard constraints on

power availability.

LVGC Charging

Station

Controller

Setpoints/o

bjectives for

-charging

demand

flexibility

- Available

power

profile

2.1

0

Events/A

larms

Monitoring

events/Alarms

A monitoring event or

alarm (depending on

criticality level) is

raised and sent to the

DMS to report about

the current and past

state of the LV grid.

LVGC DMS Event/Alar

m


Scenario: PS3: Energy Market

Step

No.

Event Name of

Process/Activi

ty

Description of

Process/Activity

Se

rvi

ce

Information

Producer

(Actor)

Information

Receiver

(Actor)

Information

Exchanged

Techni

cal

Requir

ement

s R-ID

3.1 Periodic Sell

Production

Local energy sources

(storage and production)

sell energy resources to

an aggregator.

DER/Battery

owner

Aggregator Energy

production

capabilities

3.2 Periodic Sell

Aggregated

Production

Local energy resources

across several LV/MV

grids are aggregated

enabling the aggregator

to act on the retail

market

Aggregator Market Aggregated

energy

production

capabilities

3.3 Periodic Provide

EV charging

demand

The charging station

forwards an already price

optimized demand curve.

CSO EV

Aggregator

(retailer)

demand +

flexibility

capabilities

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(alternatively, it forwards

the demand plus its

flexibility and the

aggregator performs the

price optimization)

3.4 Periodic Price signals pricing information is

provided to energy

providers/aggregators.

Market EV

Aggregator

Price signals

3.6 Periodic Price signals The CSO uses the price

information and the

flexibility of the charging

operation to find an

optimal demand curve

EV

Aggregator

CSO Price signals

3.5 Periodic Price

Optimized

Energy buying

The aggregator buys

updates the energy need

by buying on the intraday

market

EV

Aggregator

Market Demand


Scenario

Scenario (Sub-

scenario)

AS2: EV demand control disrupted

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Requirements

R-ID

1 LVGC CS

connection

lost

Scheduling

under av.

power

uncertainty

Enter

precautious

mode.

Refuse new

requests

CSO Charging

Spots

reduced

charging

duration

Scenario

Scenario (Sub-

scenario)

AS3: Metering data flow disrupted

Step

No.

Event Name of

Process/Activity

Description of

Process/Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Requirements

R-ID

1 consumption

Metering

samples

missing

Estimate

load under

uncertainity

Conservative

calculation of

available

power

CHANGE LVGC CS

controller

Reduced

Available

power

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Name of Information

Exchanged


Reservation Information from vehicle: arrival, expected

departure time, min charging energy, maximum

energy,

Available power Calculation of maximum power that can be

pulled out from a node for charging

Charging load profile Aggregated load profile (plan) for a charging

station

Metered Consumption bus load Aggregated domestic load metered in one

period

Metered Generation power Aggregated bus gen .power in one metering

period

Generation output limitation Control signal to the PV inverted 0<c<=1

Charging start/Stop Sub-meter on/off signal



Term Definition

LVGC Low voltage grid controller

CS Charging spot

EV Electric vehicle

CSO Charging station operator (controls EV parking with several CPs), aggregates EV load, is owned by Energy

provider or charging station infrastructure provider

Routing Pre-charging User Service to find the best CS

EV demand Amount of energy required by an EV

Plugin event User is at CP and plugs in charging (and data) cable

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10.3 USE CASE NAME: External generation site




ID Domain(s)

Name of Use Case



Version Management

Changes /

Version

Date Name


Domain

Expert

Area of

Expertise /

Domain /

Role

Title Approval


for voting, final

0.00 25.01.2013 Rasmus Løvenstein Olsen,

Florin Iov, Jayakrishnan

Radhakrishna Pillai, Rafael

Wisniewski, Christoffer Sloth

draft

0.3 18.02.2013

0.4 10.03.2013 Update

0.5 18.03.2013 Update

0.8 19.07.2013 Rasmus Løvenstein Olsen,

Christoffer Sloth, Florin Iov

Update



Related business case Use case 2: Self-Optimized Low Voltage Grid Domain

Scope With the anticipated increase in small decentralized energy resources from

primary wind and photovoltaic (PV), the low voltage (LV) grids are exposed

to new load scenarios than originally designed for. Further, new high

consumer demands from Electrical Vehicle (EV) mobility and heat pumps

challenge existing LV grid infrastructures additionally. As a result, there is an

increased interest in technologies to improve the LV grid operation. These

mainly entail: local energy storage, active control of energy fed in electrical

grid, flexible demand control (entailing both end-user managed demand

response and autonomic demand control) for house-holds and EVs. This use

case covers the automation and control techniques required for future LV

grids and enables the DSO to utilize the flexibility of the LV grid assets.

The reference scenario for this use case consists of a MV and LV grid

containing: 1) fixed and shift-able energy consumption from households,

small enterprises and EVs, 2) production from PVs and wind turbines, 3)

Energy storage. Hierarchical controller architecture is utilized, where a

distribution management system (DMS) is at the upper most level. This

provides commands to the MV grid controller, which sends commands to

the LV grid controllers as well as flexible generation and consumption in the

MV grid. Finally, the LV grid controller sends commands to flexible assets in

FP7-ICT-318023/ D1.1 ver 2

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the LV grid. The LV grids are connected to the MV grid via a controllable

transformer station with an online tap changer (OLTC).

It is considered that all components in the architecture are connected with a

communication network providing monitoring data from and control of the

individual components. The LV grid implements its own control mechanisms

which are responsible for: a) maintaining an acceptable voltage profile,

security and safety, b) balancing available power resources (energy storage

and generation) with the (flexible) demand, and c) handling the interactions

between a) and b). The control infrastructure is managed by one or more

dedicated LV grid controllers which provide functionality to support the sub-

use cases introduced in the following sections. This Use Case is considering

only faults and performance degradation within the public communication

network, and the system’s overall ability to perform normal grid operation

even during network faults and performance degradation.

Objective The objective is to demonstrate the feasibility of distribution grid operation

over an imperfect communication network




The Use Case is focusing on demonstrating the feasibility of controlling flexible loads and renewable

energy resources in LV grids over an imperfect communication network. Flexibility of LV grids for

upper hierarchical control levels is also investigated














Under these settings, two main scenarios are defined as to show the above characteristics:




models).

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Primary Substation

Automation&Control

MVGC


HV Grid

HV

MV

MV

LV

Prosumer

Consumer

Interm. DER

Consumer

MicroDER

SME

Farm

SME

EnergyStorage

…

MV

LV

...

...

...

...

MV

LV

Use Case 2.3

Prosumer

Retailers

DMS

TSO

ForecastProviders

Markets

AggregatorsMV/LV

WAN

AN


&Performance


& Flexibility

AN Provider(s)

AN Provider(s)

WAN Provider(s)


Automation&Control


Automation&Control


LVGC

Figure 86 Overview of Use Case


General Remarks

The definitions for distributed energy resources used for this Use Case are defined in the table

below. These definitions are taken into account the voltage and current at the connection point as

well as the power rating of the device.

DER Definition Voltage

Ratings

[kV]

Current

Ratings

[A]

Installed

Capacity

[kW]

DER Type

Micro DER < 1 <16 < 5 DER at Household level

e.g. micro CHP, PV

system, wind turbine,

energy storage,

Intermediate DER < 1 > 16 5 < …< 500 DER connected to low

voltage feeders.

Examples: standalone

systems e.g. PV panels

and heat pumps, single

wind turbine, battery

storage, charging spot for

EVs, etc

Large DER > 1 > 16 > 500 DER connected to

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medium voltage grids.

Examples: wind or PV

power plants, Combined

Heat and Power plants,

Supermarkets with

refrigeration systems and

charging stations for EVs,

etc.


Diagram of Use Case

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Market(s)

Data Transport(WAN)

Data Transport(AN)

Control of assets

Retailer

DSO

TSO

ForecastProvider(s)

AggregatorTechnical (MV/LV)



Prosumer

Consumer

Micro DER

WAN Provider(s)

Network

performance

change

Network

congestion

Lost network

connectivity

Network

performance

change

Intermediate DER

Large DER

DMS

AN Provider(s)

ProsumerNetwork

congestion

Lost

Network

connectivity

Figure 87 Overview of use cases

The use cases as defined in the following document will be running on top of a system described in

slightly more details in the following using SGAM depicturing methodology.

Based on SGAM Framework the component layer of the Use Case is shown in Figure 88. In the

following a brief overview of the architecture and functionality of the use case diagram is provided in

component and functional layers as described in [UCC]. This approach describes the relation

between components and functions in terms of electrical grid components (x-axis) and zones of

operation (y-axis) which is helpful also to understand the need for communication between the

various components and functions. This shows the generic interaction between assets and

controllers for the Control of Assets use case.

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Component Layer

TSO


MV grid control



LV grid control

Large DER

DMS


(MV)


Markets


e DERProsumer

Smart Meter

Smart Meter

Smart Meter

Smart Meter

MV Grid Components

LV Grid Components

Station


Field

Process

Operation

Enterprise

MarketWAN Channel(s)

Private Channel(s)

AN Channel(s)

Figure 88 Set of physical components and their locations in the smart grid setup

Communication layer of the Use Case describing different potential communication technologies

between various components is given in Figure 89. Faults and errors causes performance

degradation that needs to be taken into account, which creates the error scenarios for the Data

Transport use cases at Access Network and Wide Area Network level.

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TSO


MV grid control



LV grid control

Large DER

DMS


(MV)


Markets


e DERProsumer

Smart Meter

Smart Meter

Smart Meter

Smart Meter

MV Grid Components

LV Grid Components

Station


Field

Process

Operation

Enterprise

Market

Public internet

xDSL, Fiber, Cable, UMTS, WiMAX

Private net

Fiber, Ethernet, ATM

Private net

PLC,Fiber,

Ethernet, ATM

Private net

PLC,Fiber,

Ethernet, AT, TETRA

Public internet

xDSL, Fiber, Cable, UMTS, WiMAX

Public Access Networks

xDSL, Cellular (UMTS, GPRS), WiMAX, PLC

Site comm.

WLAN, Ethernet, WB-PLC,

Zigbee, Z-wave

Communication Layer

Figure 89 Different communication means used for the various components to interact with each other

Functionalities in the grid that allows the operation and the two cases; commercial and technical

flexibility scenarios. These are connected with the communication lines as shown above, and is

executed on the various grid components as illustrated in Figure 88.

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TSO


MV grid control



LV grid control

Large DER

DMS


(MV)


Markets


e DERProsumer

Smart Meter

Smart Meter

Smart Meter

Smart Meter

MV Grid Components

LV Grid Components

Station


Field

Process

Operation

Enterprise

Market Market prices

Weather

information

Commercial

aggregation

HV grid management,

GIS system data,

planning tools,

visualisation

MV/LV grid

management, GIS

system data, planning

tools,

visualisation

Technical aggregation

Grid resynch., fault detection and

isolation, demand side mngt and

response, curtailment, ancillery services

Protection and monitoring

Warnings and alarms for

grid failure

Actuation Actuation Actuation

Protection and metering

Functional Layer

Figure 90 Different functionalities used in the system in order to be able to execute the use cases over the

network on the different physical components

In the following part of this document, high level descriptions of the use cases, step by step, will be

done.

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Stakeholders

Actors





Further information


Micro DER Distributed energy resources at house hold

level. Examples of such resources are: wind

turbine, PV system, micro CHP, energy

storage, EVs, etc

Intermediate DER Distributed energy resources connected to

low voltage feeders. Examples of such

resources are: standalone systems e.g. PV

panels and heat pumps, single wind turbine,

energy storage, charging spot for EVs, etc.

Entities connected to the LV

grid, but not belonging to

households or small

enterprises

Large DER Distributed energy resources connected to medium voltage grids. Examples of such resources are: wind and PV power plants, Combined Heat and Power plants, Supermarkets with refrigeration systems and charging stations for EVs, etc.

Consumers Role Consumers that are not offering flexibility in

operation and control such as: households,

small enterprises

Prosumers Role Consumers that are offering flexibility in operation and control. They can be connected at LV or MV grids and can contain micro, intermediate, or large DER.

Smart household or small

enterprise

Smart Meter (SM) System The metering end device is a combination of the following meter-related functions from the Smart Metering reference architecture: • Metrology functions including the conventional meter display (register or index) that are under legal metrological control. When under metrological control, these functions shall meet the essential requirements of the MID; • One or more additional functions not covered by the MID. These may also make use of the display; • Meter communication functions.

Every household is equipped

with a smart meter.

Comm. Network Provider Role Provides communication services to the

system, e.g. M2M infrastructure.

Distribution System Operator (DSO)

Role

According to the Article 2.6 of the Directive: "a natural or legal person responsible for operating, ensuring the maintenance of and, if necessary, developing the distribution system in a given area and, where applicable, its interconnections with other systems and for ensuring the long-term ability of the system to meet reasonable demands for the distribution of electricity". Moreover, the DSO is responsible for regional grid access and grid stability, integration of renewables at the distribution level and regional load balancing.

Utility companies

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Transmission System Operator (TSO)

Role

According to the Article 2.4 of the Electricity Directive 2009/72/EC (Directive): "a natural or legal person responsible for operating, ensuring the maintenance of and, if necessary, developing the transmission system in a given area and, where applicable, its interconnections with other systems, and for ensuring the long-term ability of the system to meet reasonable demands for the transmission of electricity". Moreover, the TSO is responsible for connection of all grid users at the transmission level and connection of the DSOs within the TSO control area.

Transmission system

operator(s)

Technical Aggregators MV/LV Role Offers services to aggregate signals/information regarding flexibility of different consumers and prosumers from MV and LV grids respectively. This aggregated information is used by hierarchical control levels.

Retailer Role Entity selling electrical energy to consumers - could also be a grid user who has a grid connection and access contract with the TSO or DSO. In addition, multiple combinations of different grid user groups (e.g. those grid users that do both consume and produce electricity) exist. In the remainder of this document, the terms customer/consumer and grid user are used interchangeably where appropriate.

Markets Market for trading energy and ancillary

services

Power, Energy, Ancillary

Services

Forecast Provider System Compute forecast for consumption and renewable generation in a given area based on weather forecast, historical data, etc.

May be separate for wind,

Solar Irradiance, consumption,

etc.


System System placed in the secondary substation aiming to control assets on LV feeders and provide flexibility to upper control levels.


System System placed in the primary substation aiming to control assets on MV feeders and provide flexibility to TSO and DMS.

LV Grid Components System Grid components such as transformers, cables, breakers, etc.

MV Grid Components System Grid components such as transformers, cables, breakers, etc.

Distribution Management System

System A system which provides application to monitor and control a distribution grid from a centralized location, typically a control centre


Use Case Conditions


AN/WAN between communicating

entities (MVGC, LVGC and Assets)

Change in network

performance (no-congestion)

“Normal” cross

traffic patterns in

network

-Bidirectional communication with

consumers can be done for effective

network reconfiguration.

-Traffic increase is caused by external

factors, i.e. uncorrelated with the

control traffic.

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AN/WAN between communicating

entities (MVGC, LVGC and Assets)

Congestion in network High load network

condition

- Bidirectional communication with



- Some QoS configuration possibilities

exists

-Traffic increase is caused by external

factors, i.e. uncorrelated with the

control traffic.

AN

Wired/wireless network

Network connection is lost Pre-existent

connection at

network layer

- Requires a notion of logic

connectivity between entities at

network layer.

- The cause of lost connectivity is in

the network (i.e. we delimit from non-

responsive devices/crashed devices).

AN

Wireless networks

Link conditions changed “Normal” channel

condition

- Some link reconfiguration

possibilities exists and is accessible




- Change of channel conditions are

uncorrelated with the power grid and

happen at random time intervals.

AN

Wireless networks

Link capacity reached High load on AN - Some QoS options exists for

reconfiguration of the link




- Factor that triggers the congestion

state is not correlated with the control

system, e.g. too many customers in

the network

AN

Wireless networks

Link connection is lost Pre-existent

connection at link

layer




- Alternative AN’s are available.


References

No. References Type Reference Status Impact on

Use Case

Originator/Organisation Link

1 Public SG-CG/M490/C

Smart GridReference

Architecture

V 3.0

2 Public



Relation to Other Use Cases This sub-use case must exploit the flexibility offered in sub-use cases 1 and 2 in the low voltage grid controller.

Level of Depth

High level description

Prioritisation

High/Mandatory


Regional

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View

Technical


Smart grid control, network failure resilience

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Scenario Conditions

No. Scenario

Name

Primary

Actor


4.1 Base Case WAN/ANPro

vider

No events in WAN/AN Normal Operation Normal operation

4.2 Network

Performanc

e Changed

WAN/ANPro

vider

Change in network

performance

Normal Operation

4.3 Network

Congestion

WAN/AN

Provider

Congestion in network Normal Operation Congestion

4.4 Lost

Network

Connectivit

y

WAN/AN

Provider

Network connection is lost Normal Operation Loss of connectivity

Each of these scenarios is considering three subcases as:

Energy balance – where the operation of MV grids is targeted. LV grids are considered aggregated and the LVGC is offering flexibility to MVGC. Thus MVCG is primarly controlling the assets such as Large DER, prosumers and LV grid via LVGC to keep the energy balance. The primary actor involved here is the WAN Provider

MV control – where the focus is to control the voltage profile on MV grids using reactive power capabilities offered by Large DER, MV prosumers and the secondary substations on MV side. The primary actor involved here is the WAN Provider

LV control - where the focus is to control the voltage profile on LV grids using reactive power capabilities offered by Micro and Intermediate DER, flexible consumption and production at household or small and medium enterprises. The primary actor involved here is the AN Provider(s)

These subcases may involve only some of the actors while other are neglected as mentioned above.


Grid operations

In normal operation the grid is operated as follows. Starting from the lowest level (right in the

figure), consumers and DERs sent measurements to the LV grid controller and receive setpoints from

the LV grid controller. The measurements from LV assets are aggregated before they are sent to the

MV grid controller. Similarly, the LV grid control receives an aggregated setpoint from the MV grid

controller that must be dispatched to the individual LV assets. The MV grid controller communicates

with Large DERs and LV grid controllers to exchange aggregated flexibility, measurements, and

setpoints. Additionally, the MV grid controller sends the aggregated flexibility to the DMS, which

generates setpoints based on the available flexibility, weather information, and market conditions.

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Aggregation (LV)

LV grid control



Large DERMicro DER/


Consumer

Measurements


Measurements



DMS

Weather information

Setpoint



Measurements

Measurements

Measurements

NetworkStatus/

performance





Measurements


Markets

Price signal


NetworkStatus/

performance

Individual

setpoints (MV)




Measurements


Weather information

Bids

Accepted bids

Setpoints

Measurements

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

Scenario

Scenario

Name :

Base Case

Step

No.

Event Name of

Process/Activ

ity

Description of

Process/Activit

y

Servic

e

Information

Producer

Information

Receiver

Information

Exchanged

Technical

Requiremen

ts R-ID

1 Periodica

lly

Status and

measurement

collection

Data regarding

status of the grid

is collected and

other information

such as wind

GET MV grid

controller, grid

sensors, smart

meters, grid

components

Technical

aggregator, LV

grid controller,

MV/LV grid

management

Grid status

data (Voltage,

frequency, …)

2 Periodica

lly

Actuation

calculations

Determine

response to

demand/supply

EXECU

TE/SET

Technical

Aggregator, LV

grid controller

Actuators, LV

grid controller

Actuation

signals,

reference

signal to LV

grid

controller


Change in network performance

This scenario deals with time varying performance in the network, and the adaptation of access methods to provide reliable data exchange between entities communicating.

Scenario

Scenario Name : Network performance change

Step

No.

Event Name of

Process/Activit

y

Description

of

Process/Act

Service Information

Producer

(Actor)

Information

Receiver

(Actor)

Information

Exchanged

Technical

Requiremen

ts R-ID

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ivity

1 Change in

network

performanc

e (no-

congestion

Network

monitoring;

access adaptation

mechanisms

Monitoring of

network

performance

leads to

detection of

performance

loss

GET Communicati

on Network

Provider

Monitoring Potentially

network

performance

measurement

data, and signal

to controller

2 Change and

recalculation

of access

reconfigurati

on

parameters

EXECUTE Monitoring Information

access manager

Access

configuration

parameters

* This scenario is relevant for both WAN and AN.




Aggregation (LV)

LV grid control


Large DERMicro DER/


Consumer

Measurements




DMS

Weather information

Setpoint



Measurements

Measurements

NetworkStatus/

performance





Measurements


Markets

Price signal


NetworkStatus/

performance




Measurements


Weather information

Bids

Accepted bids

Setpoints

Measurements

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

Aceessreconfiguration


AN network condition change

AN network condition change

WAN network condition change



WAN network condition change


Congestion in network

This scenario deals with more severe network conditions, i.e. congestions in the network, and the adaptation of access methods to provide reliable data exchange between entities communicating.

Scenario

Scenario Name : Congestion in network detected

Step

No.

Event Name of

Process/Activit

y

Description

of

Process/Act

ivity

Service Information

Producer

(Actor)

Information

Receiver

(Actor)

Information

Exchanged

Technical

Requiremen

ts R-ID

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1 Network

congestion

detected

Network

monitoring;

access adaptation

mechanisms

Monitoring of

network

performance

leads to

detection of

performance

loss

GET Communicati

on Network

Provider

Monitoring Potentially

network

performance

measurement

data, and signal

to controller

2 QoS/network

option

availability

and

reconfigurati

on

GET/EXE

CUTE

Communicati

on Network

Provider

Communication

Network

Provider

QoS parameter

settings

3 Change and

recalculation

of access

reconfigurati

on

parameters

EXECUTE Monitoring Information

access manager

Access

configuration

parameters

*NB This scenario is relevant for both WAN and AN




Aggregation (LV)

LV grid control


Large DERMicro DER/


Consumer

Measurements




DMS

Weather information

Setpoint



Measurements

Measurements

NetworkStatus/

performance





Measurements


Markets

Price signal


NetworkStatus/

performance




Measurements


Weather information

Bids

Accepted bids

Setpoints

Measurements

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

QoS/Network/reconfiguration


AN congestion detection and reaction

AN congestion detection and reaction





WAN congestion detection and reaction

WAN congestion detection and reaction


Aceess reconfiguration

Aceess reconfiguration

Lost network connectivity

This scenario addresses the case where devices loose connectivity at the network layer. The case assumes a certain notion of connectivity, e.g. as in TCP.

Scenario

Scenario Name : Lost Network Connectivity

Step

No.

Event Name of

Process/Activit

Description

of

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Requiremen

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y Process/Act

ivity

(Actor) (Actor) ts R-ID

1 Network

connection

is lost

Network manager A timeout or

other type of

error triggers

a detection of

a lost

network

connection.

Assumes a

notion of a

logic

connection

between

entities.

GET Network

provider

Information

access manager

Error signal

2 Reestablishm

ent of

connection;

potentially try

different

network

interfaces in

this process.

EXECUTE Information

access

manager

Target device Connection

signals




Aggregation (LV)

LV grid control


Large DERMicro DER/


Consumer

Measurements




DMS

Weather information

Setpoint



MeasurementsMeasurements

NetworkStatus/

performance





Measurements


Markets

Price signal


NetworkStatus/

performance




Measurements


Weather information

Bids

Accepted bids

Setpoints

Measurements

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

NetworkStatus/

performance

AN Lost network connection

Timeoutmessage

Timeoutmessage

Success OK

NetworkStatus/

performance

NetworkStatus/

performance

AN Lost network connection

Timeoutmessage

Timeoutmessage

Success OK

Reconnect&pot. net. Reconf.

Reconnect&pot. net. Reconf.

Re-establishment of access

Re-establishment of access



Name of Information Description of Information Exchanged Requirements to information data R-ID

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Exchanged

Measurements Set of measurements from assets to upper level

control.

Individual setpoints Setpoints for assets in MV/LV grids such as

active and reactive power references, voltage

references, etc.

Network Status/Performance

Registration information; entity

capability

Deregistration information; who is

deregistering

IP address of information source; capability;

Network location information,

interface specification

IP address; interface possibilities;

Request for information or

subscription request for information

Request information for information

subscription; requirements to information

quality, delivery times etc.



Term Definition

Entity An entity is defined as some functional component (SW and HW) that will need to interact with the

smartc2net platform

Platform The communication platform that provides services and functionality for the control algorithms to

efficiently and reliably access distributed information elements

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10.4 USE CASE NAME: Automated Meter Reading (AMR) and Customer Energy

Management Systems (CEMS)




ID Domain(s)

Name of Use Case

Distribution Grid,

Customer

Automated Meter Reading (AMR) and Customer Energy Management

Systems (CEMS)


Version Management

Changes /

Version

Date Name


Domain

Expert

Area of

Expertise /

Domain /

Role

Title Approval


for voting, final

0.01 11.01.2013 CH/TUDO Draft

0.02 27.01.2013 FTW Draft

0.05 28.01.2013 CH/TUDO Draft for

comments

0.06 10.03.2013 CH/TUDO

0.08 21.03.2013 TUDO

0.09 25.03.2013 TUDO Draft

0.10 15.05.2013 Antonio Bovenzi (RT) Threat

Analysis

Researcher Draft

0.12 17.05.2013 FK/TUDO Draft

0.15 07.06.2013 FK/TUDO Draft



Related business case -

Scope Power Grid domains:

- Distribution networks - Households

ICT domains:

- Home Area Networks - Neighbourhood Area Networks

Objective

Automated Meter Reading:

Collection of energy consumption data from electric, gas, water and heating metering devices

Transmission of aggregated data from the households to the energy utilities/meter reading operators for billing and accounting

Provide (local) feedback system to the customers in order to provide transparent insight on the current energy consumption and enabling indirect demand side management

Aggregate information of energy consumption in order to balance the

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distribution grid by enabling direct demand side management

Customer Energy Management Systems:

Improve distribution grid stability by enabling direct demand side management

Reduce energy costs for consumers by shifting flexible loads to less expensive time slots or improve utilization of local energy resources

Provide added-value services to the customers




Automated Meter Reading (AMR) is an enabling technology, which is capable of generating precise

multi-sector metering data and aggregate them on local grid operator side for large-area and in-

house analysis of current energy consumptions as well as grid load conditions. Additionally, current

efforts in context of the Internet of Things aim to connect more devices in the household to create a

more intelligent Home Area Network (HAN) including components of Customer Energy Management

Systems (CEMS) like Distributed Energy Resources (DER) and storages, demand side management,

domestic electric vehicle charging and user interaction. In context of AMR, this adds an additional

way of home building automation by combining the energy consumption of accordant components

with the current status of the energy grid to improve its stability by shifting flexible loads balanced

with the neighborhood area network.


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AMR is often referred to as the key application for enabling a Smart Grid. Basically, AMR represent

different approaches for automatically collecting energy consumption data from electric, gas, water

and heating metering devices and transmitting these data to the meter reading operator for billing

and accounting. This information enables the energy utilities for an accurate meter reading and a

detailed forecast of the predicted energy consumption. Since several years AMR systems are already

deployed mainly for industrial and commercial customers, based upon an integrative approach by

combing the actual metering components and a WAN interface for remote meter reading. Due to the

European Mandate M/441, a monthly billing for the customer and a roll-out of Smart Meter in 80%

of all European households until 2020 is targeted, which requires cost-efficient, modular concepts for

the comprehensive deployment of Smart Metering devices in a large number of households

considering a variety of application scenarios. Due to different technology life cycles for energy

components and ICT components a modular system is targeted in most of the approaches. Usually a

Metering HAN Gateways collect and store metering data from several metering devices, like

electricity, gas, water and heating meters by short range radio, e.g. ZigBee or Wireless M-Bus. The

collected data is securely transmitted bundled to the meter reading operator by different access

technologies, based on wireless, wired or PLC technologies. Moreover, a local feedback system gives

the consumer/prosumer transparent insight into his current energy consumption. In conjunction

with available tariff information motivation for reducing overall power consumption can be achieved.

The high-level AMR system architecture is depicted in Figure 91 consisting of the following

components:

1) Electricity metering devices collecting electrical energy consumption in short term intervals enabling variable time intervals and different tariff options.

2) Sub-Metering devices for gas, water, heating collecting energy consumption in long term intervals in order to provide automated meter reading

3) A communication gateway (HAN metering gateway) collects data from the metering and sub-metering devices via short range transmission technologies and aggregates data for providing wide area connectivity to the meter reading operator/energy utility.

4) A user feedback system, which can consist of a display or a PC application, provides feedback on a short term interval to the customers in order to enable indirect DSM by providing current pricing and consumption information.

5) A meter reading operator is providing the infrastructure for the metering devices and is located on the backend system side.

In the context of SmartC2Net, the following AMR scenarios with reference to [4-9] have been

identified. A detailed scenario structure with appropriate use cases is illustrated in Figure 93. It is

depicted how the individual physical components are laid out. The Smart Meters (SM) of the AMR

use case measure the amount of energy, gas and water used in the household. Therefore a

connection between the flexible and non-flexible loads and the Smart Meter is necessary. The SM

interfaces with the Local Network Access Point (LNAP) which provides the WAN connection for

upload of the metering data. It is to be considered that, due to legal restrictions out of privacy

concerns, it is possible that a direct connection between SM and Energy Management Gateway

(EMG) might not exist. A EMG has the ability to controls flexible loads, private parking spots and

home automation devices. The state of these devices, along with current tariff and consumption

information, is made available for the consumer by an external display which also provides a certain

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degree of control over the CEMS. The LNAP has an interface to the Neighborhood Network Access

Point (NNAP) which itself connects to the Head End System (HES) with its subsequent set of devices

and roles. These are the Meter Data Management System (MDMS), Metering Data Aggregator

(MDA), Distribution Network Operator (DSO), Aggregator, Metering Operator and Energy Service

Provider.

Scenario 1: Measurement (MM)

For considering all amount of customer’s supply, meter reading and tariff configuration are

integrated in the measurement procedure. Different actors (A, B, C – see chapter 10.4.3.1)

participate in the measurement procedure to ensure that tariff parameters are kept valid (Set tariff

parameters) on provider- and customer side. Meter reading can be divided in two sub-procedures,

Reading on demand and Scheduled reading:

MM.01 Reading on demand See Figure 94 and Figure 95

This use case describes how a request may be made to the AMI (Advanced Monitoring

Infrastructure) for an on demand reading and how the AMI responds. The request may relate

to current register / index readings or to historical values (e.g. stored at the end of a billing

period). The request may be issued by Actor A or Actor B. This use case may be used to

retrieve not only the values of billing registers / indexes but any values that need to be read

on demand, under the conditions that it is for authenticated authorized actors and with full

respect of data privacy.

MM.02 Scheduled reading See Figure 97, Figure 98 and Figure 99

This use case describes how Actor A obtains meter readings at regular intervals and how a

meter reading schedule (which indicates what data has to be read from the smart meter at

which point in time) is configured.

MM.03 Set tariff parameters See Figure 100, Figure 101 and Figure 102

For billing configuration, the setup of billing parameters is needed. The use case Set billing

parameters describes Actor A setting the parameters that represents consumer account

arrangements. Billing parameters are Payment mode, Tariff scheme, Prices, Thresholds and

response actions and Data sets.

Scenario 2: Customer information provision (CI)

CI.01 Provide information to consumer See Figure 103, Figure 104, Figure 105 and Figure 106

This use case describes how information may be provided to consumers by the AMI system

via the simple external consumer display.

Information may be generated by actors outside the AMI system and communicated via the

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AMI infrastructure or may be generated within the system and presented for display on

devices within the metering system.

Scenario 3: Collect AMI events and status information (ES)

The AMI provides functionality to screen and manage AMR related information with focus on supply

quality as well as tamper and fraud detection.

ES.01 Tamper and fraud detection Detect tampering of the metering system (physical integrity, electromagnetic field,

communication, security, fraudulent use of the meter by customer, etc.) and detect tamper

of connection to network.

ES.02 Manage supply quality See Figure 107, Figure 108 and Figure 109

This primary use case describes how information concerning supply quality is being

monitored by providing it on a regular basis to actor A and/or sending it on a regular basis to

a simple external consumer display.

ES.03 Advanced monitoring Uploading of data and information to permit e.g. monitoring of outages (electricity), network

leakage detection (water) and identification of possible meter malfunction.

In addition, diagnostics (mainly for electronic components), the meter / metering system,

status information (e.g. battery condition credit/prepayment mode) and identification of

incorrectly sized or blocked meters(water) can be performed.

Additionally to the basic functionality of the AMR deployment, a more balanced usage of volatile

renewable energy sources (RES) and shift-able and controllable load system (CLS) in the distribution

grids is possible by an actively integration of the components on the customers side. In this context,

several customer energy management system (CEMS) are presented, like locally managed and self-

sustaining Micro Grids, virtual power plant and centralized load coordination like DSM or DER based

on dynamic energy prices. All approaches focus on the bidirectional integration of DER and

prosumers (producers and consumers) from both power and communication engineering's point of

view. This includes volatile RES such as wind farms and photovoltaic systems, as well as energy-aware

households, which are enabled by AMR to get a detailed forecast of the energy demand and

additional transparency in energy consumption at the customer's side. Moreover, based on CLS and

Distributed Generation (DG) through combined heat and Power (CHP) generation, micro-turbines

and intelligent photovoltaic (PV) panels, the ability to balance load peaks and valleys is given. These

approaches require, however because of the distributed installations and small shift-able load

potential, an aggregation of multiple DER, which creates a common control, for example by means of

incentive systems and a sufficient amount of potential shift provides. Through concepts such as VPP,

microgrids and energy hubs, different components are combined using various networking concepts

into a logical, partly independent group (e.g. isolated networks). At this point, the seamless

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integration and reliable and near real-time connectivity within the households by a CEMS, which is

required for DER and DSM at the customers side, are key capabilities of reliable power distribution

grids.

The high-level CEMS system architecture is depicted in Figure Figure 91 consisting of the following

components:

6) Flexible and non-flexible load systems within the households (e.g. air conditioning units, household appliance, etc.)

7) Decentralized power production / distributed energy resources (e.g. photovoltaic panels, local CHP, micro wind turbines, etc.)

8) A communication gateway (control hub) providing connectivity to the in-house networks and components and enabling remote access and data services to the WAN.

9) Electricity metering devices collecting electrical energy consumption in short term intervals enabling variable time intervals and different tariff options.

10) An enhanced user feedback system, which provides the basic metering functionality and additional services for indirect and direct DSM, e.g. the customers provide flexibilities by enabling a flexible start time for their household appliances, like washing machines or dish washers.

11) In order to aggregate a large number of customers, an external service provider collects and manages the flexibilities, which are provided by the customers. This service can be covered by energy utilities or external service providers.

All in-house components assume to be connected via a CEMS, which can be realized by a dedicated

wired or wireless home automation system (e.g. narrowband PLC, broadband PLC, BUS systems,

ZigBee, W-MBus, etc.) or a shared medium provided by the customers in-house networks (e.g.

wireless LAN, broadband PLC, etc.). At least one access technology (at least cellular networks), but

possible more communication means depending on the existing possibilities, e.g. power line, 3G or

fiber (if already installed in the household) and communication technologies as well as operators

may differ between households.

In the communication infrastructure some entities exists that performs the important role of a) data

aggregation from the various sources of large numbers of households and other buildings/sites that

extracts features usable by the prediction and control algorithms applied, b) power prediction based

on the aggregated information, as well as other information such as weather forecasts and finally c)

the control of the energy grid based on the predicted power need. All of this operates, as mentioned

in local environment and will need to be coordinated with the MV grid whereas communication on

the various levels also needs to happen here.

The control network is shown in Figure 91 and consist of the following domains:

12) Connected to the control hub within households via the communication hub 13) Connected to data aggregation, power prediction and control units within the low voltage

grid

In the context of SmartC2Net, the following CEMS scenarios with reference to [9-16] have been

identified. A detailed scenario structure with appropriate use cases is illustrated in Figure 93. It is to

be considered that, due to legal restrictions out of privacy concerns, it is possible that a direct

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connection between SM and EMG might not exist.

Scenario 1: Demand and generation flexibility for technical and commercial operations

This scenario is providing use cases on flexibility features as DER, active customers/active load and

flexibility use for markets, services or grid operation. The use cases direct load and generation

management, flexibility offerings as well as receiving consumption, price or environmental

information for further action by consumer or a local energy management system are contained in

this scenario.

Direct load and generation management See Figure 110 and Figure 111

Signals and metrological information are provided to the home/building via an interface

called the Smart Grid Connection Point (SGCP). The following signals can be distinguished:

1. Direct - load / generation / storage management 2. Emergencies

The functions described below can be labelled as a “Direct load control” use case, following

the definition of Eurelectric, which is referenced in the Sustainable Processes workgroup’s

report.

Flexibility offerings Not included within this use case

Flexibility offerings are sent from flexibility providers to one or more (potential) users of

flexibility. These offerings are negotiated and if successful exercised by the acquiring party.

The offerings state the available flexibility in the dimensions of time, power/energy and

finance.

Receiving consumption, price or environmental information for further action by consumer or a local energy management system See Figure 112, Figure 113, Figure 114 and Figure 115

This use case describes how information regarding price and environmental aspects is sent

from upstream actors to CEMS and how information regarding energy consumption or

generation as well as smart device statuses are being sent back to the consumer and

upstream actors.

Scenario 2: Grid related use cases

Several use cases are describing existing functionalities, especially coming from power automation,

network operation and monitoring (SCADA). Those use cases are well known today, but have to be

adapted to the Smart Grid in order to realize spreading of intermittent power sources (generation or

storage) at any level of voltage.

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Grid related use cases in smartC2net are divided in sub use cases Voltage control and power flow

optimization VVO, Microgrid management, Monitoring the distribution grid, Fault Location,

Isolation and Restoration (FLIR) as well as Forecast. This use cases are driven by grid management

and control algorithms and are detailed in [18].

Scenario 3: Electric vehicle charging and low voltage grids

Charging of electrical vehicles in low voltage grids is challenging due to highly synchronized demand

patterns of charging as well as high loads. This use case covers the controlled charging of electrical

vehicles in a low voltage grid, taking into consideration the EV owner, a charging infrastructure

owner/provider as well as the DSO. Regarding the latter, the use case aims to utilize the high demand

flexibility of the charging process to balance grid and energy in the low voltage grid [19].

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General Remarks

-


Diagram of Use Case

Figure 91: Advanced Smart Meter Reading and Customer Energy Management System Scenario

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Simple external

consumer display

Home automation end device

Energy Management Gateway (EMG)

Smart Meter (SM)

Customer Energy Management System (CEMS)

Substation Level Operator LevelAutomated Meter Reading (AMR)

Local Network Access Point

(LNAP)

Flexible Loads

Non-Flexible Loads

Metering Operator

Private Charging Spot

Aggregator

Distribution Network Operator


Metering Data Aggregator

Related to EV Use Case



Meter Data Management System


Neighborhood Network Access Point (NNAP)

Figure 92: Physical components of the use case and their locations in the Smart Grid setup

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DG.01. Direct Load /Generation

management

DG.02. HL-UC Flexibility offerings

DG.03. HL-UC Receiving consumption, price or environmental information for further action by consumer or a local

energy management system

CI.01. Provide Information to

consumer

ES.01. Tamper and Fraud detection

ES.02. Manage supply quality

ES.03. Monitoring

MM.01. Obtain meter reading on demand

MM.02. Obtain scheduled meter

reading

MM.03. Set tariff parameters

Keys

Customerinformation provision AMR Use Cases

<< extends >>

Actor A Actor B Actor C

Demand and Generationflexibility for technical and

commercial operations

Electric Vehicle REF: Use Case Name: Electrical Vehicle

Charging in Low Voltage Grids

Reference to use casedocument

Use Case ClusterUse Case Cluster

Use Case

Actor D

[WGSP Actor B]

[WGSP Actor A]

Collect AMI eventsand status information

<< extends >>

Measurement

Grid related REF: Use Case Name:

External Generation Site and Island Mode

CEMS Use Cases

Figure 93: Detailed use case clustering structure

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Diagrams of AMR Use Case

The diagrams of AMR use case are structured in sub-processes billing, customer information

provision as well as collect AMI events and status information.

Diagrams of sub-process Measurement (MM)

Diagram of Use Case

MM.01. Obtain meterreading on demand

SU3. Read meter

Actor BActor A

<<includes>>

Figure 94: MM.01 Obtain meter reading on demand (refer to [4])

Actor A EMG Smart Meter

1: Send (Meter read request)

2: Invoke SU3()

3: SU3 invoked()

4: Send (Requested reading)

Figure 95: Sequence diagram MM.01.01 - Obtain remote meter reading on demand (refer to [4])

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Actor A Smart Meter

1: Send(Meter read request)

2: Send (Meter read)

Figure 96: Sequence diagram MM.01.02 - Obtain walk-by meter reading on demand (refer to [4])

ActorA

MM.02. Obtainscheduled meter reading

SU3. Read Meter

MM.02.01. Configurereading schedule

SU1. Writeinformation

<<extends>>

<<includes>>

<<includes>>

Figure 97: MM.02 Obtain scheduled meter reading (refer to [5])

Actor A EMG Smart meter

1: SU3 invoked()

2: Send (Meter read)()

Figure 98: Sequence diagram MM.02.01 - Obtain scheduled meter reading (refer to [5])

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1: Send (Reading schedule)

2: Invoke SU1()

3: SU1 invoked()()

4: Send (Confirmation)

sd optional

Figure 99: Sequence diagram MM.02.02 - Configure reading schedule (refer to [5])

MM.03. Set billingparameters


Actor BActor A

<<includes>>

Figure 100: MM.03 Set tariff parameters (refer to [6])

Actor A EMG Smart meter Display

1: Send (Billing parameter)

2: Invoke SU1()

3: Send(Notification)

4: SU1 invoked()

5: Send(information)

sd optional

sd optional

Figure 101: Sequence diagram MM.03.01 - Set tariff parameter in the smart meter (refer to [6])

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Actor A EMG NNAP / LNAP

1: Send(Billing parameter)

2: Invoke SU1

3: SU1 invoked

4: Send(confirmation)

sd optional

Figure 102: Sequence diagram MM.03.02 - Set tariff parameter in the LNAP/NNAP(refer to [6])

Diagrams of sub-process customer information provision

Diagram of Use Case

CI.01. Provideinformation to customer


Actor A

Actor C

Actor B

Figure 103: CI.01. customer information provision (refer to [8])

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1: Send(information message)

2: Invoke SU1()

3: SU1 invoked()


sd optional

Figure 104: Sequence diagram CI.01.01 - Send information to meter display (refer to [8])


1: Send(information message)

2: Invoke SU1()

4: SU1 invoked()


sd optional

Smart meter

3: Send(Information message)

Figure 105: Sequence diagram CI.01.02 - Send information to simple external consumer display (refer to [8])

Smart meter Display

1: Send(Actual meter reads / power quality and/or device status)

Figure 106: Sequence diagram CI.01.03 -– Smart Meter publishes information on simple external consumer

display (refer to [8])

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Diagrams of sub-process collect AMI events and status information

Diagram of Use Case

ES.02.01 Configure powerquality parameters to be

monitored

MM.01 Obtain meterreading on demand

MM.02 Obtainscheduled meter reading

CI.01.01 Send toinformation to meter display

ES.02 Managesupply quality


SU3. Read meter

Actor A Actor C

<<extends>><<extends>> <<extends>> <<extends>>

Figure 107: ES.02 - Manage supply quality (refer to [7])


1: Send(Power quality parameters)()

2: Invoke SU1()

3: SU1 invoked()

4: Send (Confirmation)

sd optional

Figure 108: Sequence diagram ES.02.01 - Configure power quality parameters to be monitored (ref. [7])

Smart Meter Display

1: Send (Supply quality message)

Figure 109: Sequence diagram ES.02.02 - Smart meter sends information on power quality to display (refer to

[7])

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Diagrams of CEMS Use Case The diagrams of CEMS Use case are structured in sub-processes grid related use cases as well as

demand and generation flexibility for technical and commercial operations.

Diagrams of sub-process demand and generation flexibility for technical and commercial

operations (DG)

Diagram of Use Case

Actor A MDM EMG NNAPSmart Metering Gateway

(LNAP) Actor D Energy Management Gateway CEMS Smart Appliance / Generators Display

Load Mgmt. Command

Load Mgmt. command

Load management system

CCM

Start of load adjustment notification

Order of load adjustmend

Feedback status

End of load adjustment notification

End of load adjustment

End of load adjustment period + sending load curve recorded for this period

Feedback status

End of load adjustment period + sending load curve recorded for this period

par

par

Announcement of load adjustment

Expected change in consumption

Expected change in consumption

Figure 110: DG.01.01 - Direct load / generation demand – appliance has end-decision about its load

adjustment (refer to [14])

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(LNAP)Actor D Energy Management Gateway CEMS Smart Appliance / Generators Display

Load Mgmt. Command

Load Mgmt. command

CCM

Load adjustment notification

Start of load adjustmend period

Feedback status

End of load adjustment notification

End of load adjustment period

Confirmation that load has been adjusted

Feedback status

Confirmation that load has been adjusted

par

par

Figure 111: DG.01.02 - Direct load / generation demand - appliance has no control over its own load

adjustment (refer to [14])


(LNAP)Actor D Energy Management Gateway CEMS Smart Appliance / Generators Display

Individual appliance consumption / generation information

Total and / or forecased house consumption / generation

Total and / or forcased house consumption / generation

Total and/or forecased house consumption / generation

Total and/or forecased house consumption/generation

par





Figure 112: Sequence diagram DG.03.01 - Information regarding power consumption / generation of

individual appliances (refer to [16])

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Actor A MDM EMG NNAP Smart Metering Gateway(LNAP)

Actor D Energy Management Gateway CEMS Smart Appliance/Generators Display

Total and / or forecased house consumption / generation

Total and / or forcased house consumption / generation

Total and/or forecased house consumption / generation


par





Smart Meter Functionality

Total house consumption

Total house consumption

Figure 113: Sequence diagram DG.03.02 - Information regarding total power consumption (refer to [16])


(LNAP) Actor D Energy Management Gateway CEMS Smart Appliance/Generators Display

Gateway

Price and environmental information


par

Confirmation






par

Confirmation

Confirmation New price and environmental information

New price and environmental information

Confirmation reception new price and environmental information

Figure 114: Sequence diagram DG.03.03 - Price & environmental information (refer to [16])

CEMS Smart Appliance/Generators Display

Information on total consumption & subscribed power

Warning signal

Warning signal

Figure 115: Sequence diagram DG.03.04 - Warning signals based individual appliances consumption (refer to

[16])

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Stakeholders

Figures

Actor AMetered Data Aggregator

Meter Data Collector

Meter Operator

Meter Data Management

Actor B

Consumer

Actor CActor D

Supplier



Metering End Device External Consumer Display Home Automation End Device

Figure 116: External Actors (refer to [1])

Actors





Further information


EXTERNAL ACTORS

A Summarized Actors (

Figure 116, refer to [1])

External actor interacting with the system

functions and components via the HES

MDA (belongs to Actor A) System Metering Data Aggregator

Entity which offers services to aggregate

metering data by grid supply point on a

contractual basis.

NOTE: The contract is with a supplier. The

aggregate is of all a supplier's consumers

connected to a particular grid supply point.

The aggregate may include both metering

data and data estimated by reference to

standard load profiles

MDMS / MDM (belongs to

Actor A)

System Meter Data Management System

System for validating, storing, processing

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and analysing large quantities of meter

data.

B Summarized Actors (


External actor interacting directly with the

smart meter (Metering End Device).

Consumer (belongs to Actor

B)

- End user of electricity, gas, water or heat.

NOTE: As the consumer can also generate

energy using a Distributed Energy Resource,

he is sometimes called the "Prosumer".

MO (belongs to Actor B) People/Company Meter Operator

Entity which offers services on a contractual

basis to provide, install, maintain, test,

certify and decommission physical metering

equipment related to a supply.

C Summarized Role (



simple external consumer display.


C)

Role Consumer/Prosumer

D Summarized Role (



home automation end device.


D)

- Consumer/Prosumer

ESP (belongs to Actor D) People/Company Energy Service Provider: Organization

offering energy services to the consumer.

NOTE: an example consists of a role

responsible for creating awareness

regarding rational energy consumption.

They also provide the required knowledge

to the consumer allowing him to reduce his

energy consumption. Within this role he will

supply data / information to the consumer

through the meter.

Supplier People/Company Entity that offers contracts for supply of

energy to a consumer (the supply contract).

Within this role he will initiate DSM

activities

NOTE: In some countries referred to as

Retailer

E Summarized Role (refer

to [1])

External actor responsible for the

installation, operation, maintenance and

de-installation of the system components. It

may access, if properly identified and

authorized, those components either

directly, via local operation and

maintenance interfaces, or from a system

component from a higher hierarchical level

(e.g. meters may be accessed for

maintenance purposes via NNAPs or the

HES).

MO (belongs to Actor E) People/Company Meter Operator

Entity, which offers services on a

contractual basis to provide, install,

maintain, test, certify and decommission

physical metering equipment related to a

supply.

DNO (belongs to E) People/Company Distribution Network Operator

Market surveyor (belongs to

Actor E)

People/Company Actor responsible for evaluating the

conformity of the Metering End Device to

the requirements of Directive (2004/22/EC).

Smart appliance / Generator

(external actor)

System The smart appliance with integrated EM,

directly receiving data from the grid,

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through the SGCP. The appliance may

contain of be connected to a Plug in

electricity meters that measures individual

appliance consumption or output.

Since the smart appliance / generator is

outside the scope of the SGCG, it must be

seen as an external actor

INTERNAL ACTORS (refer to [1])

Head End System (HES) System Central Data System collecting data via the

AMI of various meters in its service area. It

communicates via a WAN directly to the

meters and/or to the NNAP or LNAP.

NNAP System The Neighbourhood Network Access Point

is a functional entity that provides access to

one or more LNAP’s, metering end devices,

displays and home automation end devices

connected to the neighbourhood network

(NN). It may allow data exchange between

different functional entities connected to

the same NN.

LNAP System The Local Network Access Point is a

functional entity that provides access to

one or more metering end devices, displays

and home automation end devices

connected to the local network (LN). It may

allow data exchange between different

functional entities connected to the same

LN.

Smart Meter (SM) System Meter with additional functionalities one of

which is data communication.

Simple external consumer

display

System Display providing accurate information on

consumption, tariffs and so on in order to

increase consumer awareness.

Home automation end

device

System Device providing additional functionalities

enabling consumers to interact with their

own environment.

CEMS (Customer Energy

Management System)

System CEMS is any device/software or group of

them installed in the customer facilities

which allows the visualization of

metrological information, price and warning

signals by the customer and has the

capability to take action automatically or

after approval by customer on any home

appliances.

Energy Management

Gateway

System Equipment sending and receiving smart grid

related information and commands

between actor A and the CEMS, letting the

CEMS decide how to process the events.

The communication is often achieved

through an internet connection of through

a wireless connection


Use Case Conditions


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Access ICT Networks

No triggering event Households are

equipped with

control and

communication hubs

Primary network is cellular networks

Households No triggering event Houses are equipped

with smart meters

As a minimum the household power

consumption/production is measured


References

No. References Type Reference Status Impact on

Use Case

Originator/Organization Link

1 Report Smart Meters Co-

ordination Group -

Smart Metering Use

Cases

final All AMR use

cases

Smart Meters

Coordination Group

-

2 Report CEN-CENELEC-ETSI

Smart Grid

Coordination Group

– Sustainable

Processes

final ES.01, ES.03 CEN-CENELEC-ETSI Smart

Grid Coordination Group

-

3 CEN/CLC/ETSI/TR

50572:2011 E

Functional reference

architecture for

communications in

smart metering

systems

final All CEMS use

cases

CEN/CLC/ETSI/ -

4 Report BI.01. Obtain meter

reading on demand

draft MM.01 CEN/CLC/ETSI/ -

5 Report BI.02. Obtain

scheduled meter

reading


6 Report BI.03. Set billing

parameters


7 Report MSQ.01. Manage

supply quality

draft ES.02 CEN/CLC/ETSI/ -

8 Report CI.01. Provide

information to

consumer

draft CI.01 CEN/CLC/ETSI -

9 Report WGSP-0301 Short

term load and

generation

forecasting

draft GR.01 CEN/CLC/ETSI/ SM-CG

Use case

repository

10 Report WGSP-0200 Voltage

control and power

flows optimization

VVO


Use case

repository

11 Report WGSP-0400

Microgrid

management


Use case

repository

12 Report WGSP-0600

Monitoring the

distribution grid


Use case

repository

13 Report WGSP-0901

Congestion

management by

direct control


Use case

repository

14 Report GENERIC USE CASE

WGSP-2120

Managing energy

draft DG.01 CEN/CLC/ETSI/ Link

https://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&cad=rja&sqi=2&ved=0CE0QFjAC&url=http%3A%2F%2Fiectc57.ucaiug.org%2FWG21%2FShared%2520Documents%2F2012-03-28%2520Frankfurt%2520(Germany)%2520Meeting%2FA8%2520Generic%2520Use_%2520Case%2520WGSP%25202120%2520Managing%2520Energy%2520Consumption%2520or%2520Generation%2520ver%25205.doc&ei=QCFIUf61MpPb4QS26IHIDg&usg=AFQjCNHKXlZaK_bEwhwyLuLiPldYRlHy1A&sig2=lP_3euFScdDRJN7QzCJ0dA

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consumption or

generation with

smart appliances

15 Report WGSP-2128 - High

level use case -

Flexibility offerings

draft DG.02 CEN/CLC/ETSI/ SM-CQ

Use case

repository

16 Report GENERIC USE CASE

WGSP-2110

Receiving

metrological, price

or environmental

information for

further action by

consumer or a local

energy management

system

draft DG.03 CEN/CLC/ETSI/ Link

17 EU mandate M/441

18 SmartC2Net Use case

description

Sub-use Case 2.3:

External Generation

Site

draft SmartC2Net consortium -

19 SmartC2Net Use case

description

USE CASE NAME:

Electrical Vehicle

Charging in

Low Voltage Grids

draft SmartC2Net consortium -

20 Research Paper Basic concepts and

taxonomy of

dependable and

secure computing

Published - Avizienis, A. ; Vytautas

Magnus Univ., Kaunas,

Lithuania ; Laprie, J.-C. ;

Randell, B. ; Landwehr, C.

Link



Relation to Other Use Cases Electric vehicle charging within the households is covered by the EV UC and information exchange is required. Interfaces to the control

algorithms of the MW UC needs to be specified.

Level of Depth

HL-UC

Prioritization

Mandatory


Smart metering has a generic relation to all European countries due to the mandate M/441 of the EU to get 80% smart metering

deployments until 2020. The control aspect needs to be aligned to the European mandate M/490, but depends on the actual regional and

national deployed system architecture and needs to be evaluated for all different scenarios.

View

Technical



Scenario Conditions

No. Scenario

Name

Primary Actor Triggering Event Pre-Condition Post-Condition

Scenario AMR

Measurement (MM), (refer to [4-6])

PS1 MM.01.01 -

Obtain

remote

Actor A

Actor A decides he wants a

particular meter read or

meter reads.

The metering and

communications are

installed, operating.

Success

Actor A has the read he requested.

https://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=4&cad=rja&sqi=2&ved=0CFQQFjAD&url=http%3A%2F%2Fiectc57.ucaiug.org%2FWG21%2FShared%2520Documents%2F2012-03-28%2520Frankfurt%2520(Germany)%2520Meeting%2FA7%2520Generic%2520Use_%2520Case%2520WGSP%25202110%2520Metrological%2C%2520Price%2520or%2520Environmental%2520Information%2520ver%25205.doc&ei=QCFIUf61MpPb4QS26IHIDg&usg=AFQjCNHdUl6ZH1KjQX2k7SCSemFCmLie-g&sig2=ySwyzW99HF2SnfwSEACUeQ

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1335465&sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A29463%29

FP7-ICT-318023/ D1.1 ver 2

Page 203 of 244

Scenario Conditions

No. Scenario

Name


meter

reading on

demand

Minimal Guarantee

The metering system is operating as

before the request.

Actor A is aware of the reason for not

receiving the read.

PS2 MM.01.02

- Obtain

walk-by

meter

reading on

demand

Actor B

Actor B decides he wants a

particular meter read or

meter reads.

Success

Actor B has the read he requested.

Minimal Guarantee


before the request.

Actor B is aware of a reason for not

receiving the read.

PS3 MM.02.01 -

Obtain

scheduled

meter

reading

Actor A The timer triggers a meter

reading.

There is a valid

contract between

actor A and

consumer.

Communication

with the meter is

established.

A reading schedule

and data collection

scheme (e.g. load

profile) are

established and

activated in the

system.

Success:

Actor A has received all required metering

data.

Minimal Guarantee:

Actor A has the reason explaining why he

did not receive the expected information

PS4 MM.02.02 -

Configure

reading

schedule

Actor A Actor A needs readings from

the meter on a regular basis

Communication

between all actors

can be established.

Success:

Reading schedule is established in the

system.

Optionally, reading schedule has been

activated.

Optionally, confirmation is received by

Actor A.

Minimal Guarantee


before the request.

Actor A has the reason explaining why the

request was or will not be completed.

PS5 MM.03.01

– Set tariff

parameter

in the

smart

meter Actor A

Actor A wants to set a billing

parameter that is not yet

known by the Smart Meter.

Communication

between all actors

can be established.

Success

The billing parameter is received by the

Smart Meter.

Optionally, billing parameter has been

activated.

Optionally, the change of parameter is

shown on the display


Actor A.

Minimal Guarantee:

Actor A has a reason explaining why the

request was or will not be completed

PS6 M.03.02 –

Set tariff

parameter

Actor A Actor A wants to set a billing

parameter that is not yet

known by the LNAP/NNAP.

Communication

between all actors

can be established.

Success

The billing parameter is received by the

LNAP/NNAP.

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Scenario Conditions

No. Scenario

Name


in the

LNAP/NNA

P

Optionally, billing parameter has been

activated.


Actor A.

Minimal Guarantee:

Actor A has a reason explaining why the

request was or will not be completed

Customer information provision (CI), (refer to [8])

PS7 CI.01.01 -

Send

information

to meter

display

Actor A Actor A wants to show

information on the meter

display.

Communication

between all actors

can be established.

Success:

The information is received by the meter

display.

Optionally, actor A received confirmation.

Minimal Guarantee

The message is not displayed

PS8 CI.01.02 -

Send

information

to simple

external

consumer

display

Actor A Actor A wants to show

information on a simple

external consumer display.

Communication

between all actors

can be established.

Success:

The information is received by a simple


Optionally, actor A received a

confirmation.

Minimal Guarantee


PS9 CI.01.03 -

Smart

Meter

publishes

information

on simple

external

consumer

display

Timer Timer triggers to smart

meter to display

information on actual meter

reads / power quality

and/or device status on the

simple external consumer

display

Smart meter has a

schedule indicating

at which times

which information

needs to be pushed

to the simple

external consumer

display

Communication

between all actors

can be established.

Success:

The information is received by a simple


Minimal Guarantee


Collect AMI events and status information (ES) (refer to [7])

PS1

0

ES.02.01 –

Configure

power

quality

parameters

to be

monitored

Timer Actor A wants to configure

power quality parameters

to be monitored

Communication

between all actors

can be established.

There is a valid

contract between

Actor A and the

consumer.

Success:

Power quality parameters are received by

the Smart Meter.


Actor A

Minimal Guarantee:

Actor A is aware of the reason for failure

PS1

1

ES.02.02 –

Smart

meter

sends

information

on power

quality to

display

Smart Meter Smart Meter is triggered to

display information about

supply quality

Information about

supply quality is

available in Smart

Meter.

Communication

between all actors

can be established.

Smart Meter has an

active schedule

Success:

Information is received by a display

Minimal Guarantee:

Information is not received by display

FP7-ICT-318023/ D1.1 ver 2

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Scenario Conditions

No. Scenario

Name


indicating when to

send messages to

the display.

Scenario CEMS

Demand and Generation flexibility for technical and commercial operations (DG) (refer to 14, 16]

PS1

2

DG.01 –

appliance

has end-

decision

about its

load

adjustment

Actor A or

Actor B

Actor A or Actor B wants to

send a load management

command to the market

Communication

connection between

all actors is

established

The consumer

configured the

CEMS and/or the

participating devices

(appliances and

generators). The

consumer

configured the

device settings and

thresholds

Information on total

consumption or

consumption per

appliance is

available in the

CEMS

The Smart Appliance / generator

executed the load management command

and Actor A or Actor B received the

feedback with a load curve recorded for

this period

PS1

3

DG.01.02 –

appliance

has no

control

over its

own load

adjustment

Actor A or

Actor B

Actor A or Actor B wants to

send a load management

command to the market

Communication

between all actors

can be established

The consumer

configured the

CEMS and/or the

participating devices

(appliances and

generators). The

consumer

configured the

device settings and

thresholds

Information on total

consumption or

consumption per

appliance is

available in the

CEMS

The appliance executed the load

management command and Actor A or

Actor B received the feedback

PS1

4

DG.03.01 –

Information

regarding

power

consumptio

n /

generation

of

Smart

appliance /

Generator

New consumption /

generation information is

available in the smart

appliance / generator

Communication

connection between

all actors is

established

(forecasted) consumption / generation is

received by actor A and/or actor B and/or

display

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Scenario Conditions

No. Scenario

Name


individual

appliances

PS1

5

DG.03.02 –

Information

regarding

total power

consumptio

n

Smart Meter New

consumption/generation

information is available in

the Smart Meter

Communication

connection between

all actors is

established

(forecasted) consumption/generation

information is received by actor A and/or

or Actor B and/or display

PS1

6

DG.03.03 –

Price &

environme

ntal

information

Actor A or

actor B

New price and

environmental information

is available in Actor A or

Actor B

Communication

connection between

all actors is

established

Price and environmental information is

received by Smart Appliances

PS1

7

DG.03.04 –

Warning

signals

based

individual

appliances

Smart

appliance

The CEMS received

information on a new

operation to be executed

The subscribed

power limits are

made known to the

smart appliance

Warning signal is received by display

and/or smart appliances


Scenario Name : Reference:

Scenario AMR

Measurement (MM)

MM.01.01 - Obtain remote meter reading on demand Ref. [4], subchapter 3.1.1

MM.01.02 - Obtain walk-by meter reading on demand Ref. [4], subchapter 3.2.1

MM.02.01 - Obtain scheduled meter reading Ref. [5], subchapter 3.2.1

MM.02.02 - Configure reading schedule Ref. [5], subchapter 3.1.1

MM.03.01 - Set tariff parameter in the smart meter Ref. [6], subchapter 3.1.1

MM.03.02 – Set tariff parameter in the LNAP/NNAP Ref. [6], subchapter 3.2.1

Customer information provision (CI)

CI.01.01 – Send information to meter display Ref. [8], subchapter 3.1.1

CI.01.02 - Send information to simple external consumer

display

Ref. [8], subchapter 3.2.1

CI.01.03 – Smart Meter publishes information on simple

external consumer display


Collect AMI events and status information (ES)

ES.02.01 – Configure power quality parameters to be

monitored


ES.02.02 – Smart meter sends information on power quality to

display


Scenario CEMS

Demand and Generation flexibility for technical and commercial operations (DG)

DG.01.01 – appliance has end-decision about its load

adjustment

Ref. [14], subchapter 2.1

DG.01.02 – appliance has no control over its own load

adjustment


DG.03.01 – Information regarding power consumption /

generation of individual appliances


DG.03.02 - Information regarding total power consumption Ref. [16], subchapter 2.2

DG.03.03 - Price & environmental information Ref. [16], subchapter 2.3

DG.03.04 - Warning signals based individual appliances Ref. [16], subchapter 2.4

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Fault/threat analysis/scenarios

In this section the possible failures in the CEMS/AMR UC are considered. In particular, the focus is on

security threats that can hamper the CEMS main functionalities. Indeed, the CEMS may operate in a

very hostile environment since it can be connected to home automation devices and to the EMG by

means of shared network (e.g., the home WiFi, office LAN). The use of already deployed IP network is

extremely appealing since the cost for cabling and network interfaces is rapidly. However, IP-based

networks, when not well secured are subject to cyber security attacks.

The shift towards such a scenario may expose the communication and the CEMS critical components,

to attacks. For instance, an attacker can be:

a hacker with no intent to cause damage and who is satisfied by the penetration of systems

accessible through the Internet;

a criminal (e.g., disgruntled employee of the Energy Supplier or Energy Service Provider) who wants

to cause financial loss to the customer or to the energy service provider;

a customer with malicious objectives, e.g., to tamper the system with fraud purposes.

The attack can be executed either from the Internet or from a device connected to the HAN which

has been previously tampered, such as a personal computer or the LNAP, and may have special

information or authorizations (e.g., EMG login credentials, remote management of home automation

devices).

All in-house components are assumed to be connected to the CEMS. Among the functionalities of the

CEMS depicted in the use case diagrams (see Figures 20-25), the most critical operations that must

be secured are: i) direct load/generation management (DG.01.01) and ii) communication of power

consumption information (DG.03.01). The considered misuse cases are depicted in Figure 21.

consumption

Scenario AMR

Measurement (MM)

Scenario Name : Reference:

MM.01.01 - The metering system finds the request to be

invalid


MM.01.01 - The metering system finds that the role fulfilled by

actor A does not have the necessary access rights


MM.02.01 - System finds the data nor plausible or missing Ref. [5], subchapter 3.2.2

Customer information provision (CI)

CI.01 Provide information to consumer Ref. [8], subchapter 3.4

Collect AMI events and status information (ES)

ES.02 Manage supply quality Ref. [7], subchapter 3.3

Scenario CEMS

Demand and Generation flexibility for technical and commercial operations (DG)

DG.01 Direct load / generation management

DG.02 HL-UC Flexibility offerings

Ref. [14]

Ref. [16]

FP7-ICT-318023/ D1.1 ver 2

Page 208 of 244

Figure 117:Mis-use diagrams for the considered CEMS functionalities

The alteration or missed delivery of load adjustment commands that can be performed by means of

active attacks, i.e., the attacker tries to alter system resources or affect their operations. This may

compromise the capability of the customer to use the smart appliances or even the execution of

emergency procedures Figure 104 When the attacker is able to compromise a limited number of

CEMS the impact of the attack is low; however, when the attack is coordinated and several CEMS

systems are compromised (e.g., more than 100) or when some critical CEMS are violated (e.g., police

and fire departments systems) the impact of the attack can range from moderate to high (e.g., when

the CEMS systems of a very extended area, such as a city, are all compromised in a limited interval of

time). In the following we refer to this misbehaviour as incorrect direct load generation management,

mis-use case DE.01 (see Figure 21).

The access to power consumption/generation data shall also be secured against non-authorized

accesses. In other words customer power-related data shall be protected against passive attacks, i.e.,

attempts to learn or make us of information from a system without affecting its resources. As a

matter of fact, this is mandatory according to privacy law in some countries of the European

Community, such as Germany. Moreover, sophisticated burglaries could be architected when such

information is not secured. For example, thieves can exploit power consumption data to infer when

persons are not in the buildings and then plan physical penetrations. The impact of such an attack

can be classified as low. In the following we refer to this misbehaviour as disclosure of power

consumption information, DE.02 (see Figure 21).

For the aforementioned motivation, the network security requirements that shall be guaranteed in

CEMS systems are confidentiality, integrity and availability. In particular, for the communication of

direct load/generation management operations (i.e., load and emergency commands) integrity and

availability shall be guaranteed; while confidentiality, integrity and availability shall be assured when

power consumption data are exchanged.

According to the CEMS logical architecture described in Section 1 the most critical components

involved in the aforementioned operations are the EMG and the CEMS. Indeed, these can be

connected to the home WiFi and the likelihood to be exposed to malicious attacks is higher with the

respect to the components that are in dedicated network and when not protected by firewall or

other security mechanisms (e.g., encryption).

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Incorrect Direct load and generation management (DE.01)

The considered active attacks that compromise the integrity and/or the availability of EMG/CEMS

and lead to incorrect direct load generation management, are:

Man In the Middle (MIM) – an opponent captures messages exchanged between the EMG

and the CEMS. It can partially alter the content of the messages, or the messages are delayed

or reordered to produce an unauthorized effect.

Masquerade – an opponent sends fake messages the EMG pretending to be a different

entity.

Denial of Service (DoS) – the attacker floods anomalous messages to the EMG. It prevents or

inhibits the normal use or management of the communication facilities and/or the

components.

These attacks have been selected since they are usually performed by exploiting the most commonly

computer system and network vulnerabilities (e.g., sensitive data exposure, insecure object

references, broken authentication and session management, security misconfiguration). MIM and

Masquerade attacks can violate both integrity and availability; while, DoS violates only availability.

Tables Scenario D.01.01-D.01.03 detail the considered active attack scenarios. It is worth noting that

just one interaction is considered for the mis-use cases DG.01.01 and DG.03.01; in particular, it is

assumed that the Actor D starts the communication. However, a similar analysis can be applied when

Actor A initiates the communication.

The step by step description of the MIM attack is also explained for the sake of clarity. As for other

attacks (i.e., masquerade and DoS) the explanations can be extracted from the Description of

Process/Activity field.

Scenario DE.01.01

Scenario Name: MIM

Step

No.

Event Name of

Process /

Activity

Description of

Process/Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Require-

ments R-

ID

1 Attacker

captures

a

message

that

wants to

alter

MIM – load

command

interceptio

n

The attacker

intercepts and alters

a load adjustment

command sent by

the EMG

Load

Manage

ment

EMG Attacker Load

management

command

2 Attacker

replies an

altered

load

message

MIM –

sending

altered

load

command

The attacker

modifies the

message

intercepted at step

1 and then sends it

Load

Manage

ment

Attacker CEMS Altered load

management

command

3 Attacker

captures

the reply

to the

previousl

y altered

message

MIM –

interceptin

g and

altering

expected

change

message

The attacker

intercepts and alters

the expected

change message

(i.e. the reply to the

load adjustment

command )

Expected

change

CEMS Attacker Expected

change

message

FP7-ICT-318023/ D1.1 ver 2

Page 210 of 244

Figure 118 Mis-sequence diagram for the MIM attack

The MIM attack assumes an adversary can (i) observe messages exchanged, (ii) intercept messages

and (iii) reply messages with altered content (e.g., a load adjustment command sent by the EMG).

The attack takes place when the adversary intercepts the load adjustment command sent by the

EMG. Then, the attacker modifies the message previously intercepted (step 2 in Table Scenario

DE.01.01) and sends it to the CEMS. The CEMS is not aware of the adversary modification and takes

the load adjustment command as appropriate and reply to the message. Hence, the attacker

intercepts and alters the expected change message sent by the CEMS (i.e. the reply to the load

adjustment command) and finally sends the altered message to the EMG. In this scenario, it is

assumed that the CEMS sends the response message to the EMG. However, the attacker might also

be able to redirect all messages sent by the CEMS to himself, e.g., by means of DNS tempering.

4 Attacker

replies an

altered

expected

change

message

MIM –

sending

altered

expected

change

message

The attacker sends

the message altered

at step 3

Expected

change

Attacker EMG Altered

expected

change

message

Scenario DE.01.02

Scenario

Name:

Masquerade

Step

No.

Event Name of

Process /

Activity

Description of

Process /

Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Require-

ments R-

ID

1 Attacker

sends a

fake

message

Masquerade –

sending fake

load

adjustment

The attacker

pretending to be

an authorized

entity (e.g.,

Load

Manage-

ment

Attacker EMG Fake load

management

command

FP7-ICT-318023/ D1.1 ver 2

Page 211 of 244

command energy service

provider) sends a

fake load

adjustment

command

2 The EMG

receives

the load

adjust-

ment

com-

mand

EMG – sending

load

management

command

The EMG believes

the message

received at step 1

was transmitted

by an authorized

entity and it

forwards the load

management to

CEMS

Load

Manage-

ment

EMG CEMS Altered load

management

command

3 CEMS

receives

the load

managem

ent

command

from

EMG

CEMS – sending

the load

management

command

CEMS sends the

start of load

management

notification to

Display

Visualizat

ion of

load

manage-

ment

CEMS Display Load

management

command

4 CEMS

receives

the load

managem

ent

command

from

EMG

CEMS – sending

load

adjustment

CEMS - decides

which Smart

Appliances needs

to be adjusted

and sends an

order of load

adjustment to the

Smart Appliances

/ generators

Load

Manage

ment

CEMS Smart

Appliances /

generators

Order of load

adjustment

5 Smart

Appliance

s /

generator

s receive

the order

of load

adjustme

nt

Smart

Appliances /

generators –

sending

adjustment

feedback

The Smart

Appliances /

generators decide

to switch on/off

based on the

consumer’s

settings and send

feedback to CEMS

Load

Manage

ment

Smart

Appliances /

generators

CEMS Load

adjustment

feedback

6 CEMS

receives

feedback

from

smart

appliance

s /

generator

s

CEMS – sending

change

consumption

CEMS informs

EMG on which

change in

consumption to

expect.

Load

Manage

ment

CEMS EMG Change in

consumption

7 EMG

receives

the

change in

consumpt

ion from

CEMS

EMG – sending

change

consumption

EMG forwards the

change in

consumption to

what it believes is

the authorized

entity

Load

Manage

ment

EMG Attacker Change in

consumption

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Page 212 of 244

Figure 119: Mis-sequence diagram for the Masquerade attack

Scenario DE.01.03

Scenario Name: DoS

Step

No.

Event Name of

Process /

Activity

Description of

Process /

Activity

Service Information

Producer

Information

Receiver

Information

Exchanged

Technical

Require-

ments R-ID

1 Attacker

replies an

altered

load

message

DoS – sending

anomalous

message

The attacker

sends an

anomalous

message to the

EMG

- Attacker EMG Anomalous

management

command

N Attacker

replies an

altered

load

message

DoS – sending

anomalous

message

The attacker

sends an

anomalous

message to the

EMG

- Attacker EMG Anomalous

management

command

N+1 Actor D

sends an

emergency

load

adjustment

command

Impossibility

to receive the

emergency

load manage-

ment

procedure

The EMG is

overloaded due

anomalous

messages

received by the

attacker

Emer-

gency

load

manage-

ment

Actor D - Emergency

load

management

command

FP7-ICT-318023/ D1.1 ver 2

Page 213 of 244

Figure 120 Mis-sequence diagram for the DoS attack

Disclosure of power consumption information (DE.02)

In this section the focus is on passive attacks that compromise the confidentiality of power

consumption information exchanged between the EMG and the smart appliances. As for the active

attacks that compromise the integrity and availability, similar analyses performed for the mis-use

case DE.01 also apply for the power consumption communication.

The considered passive attacks that compromise confidentiality are:

Release of message content: the opponent tries to eavesdrop transmissions;

Traffic analysis: the opponent observes the pattern of the messages to discover the location

and the identity of the parties involved in the transmissions, and the frequencies and the

length of exchanged messages.

Scenario DE.02.01

Scenario Name: Release of message content

Step

No. Event Name of

Process /

Activity

Description of

Process /

Activity

Service Informa-

tion

Producer

Informa-

tion

Receiver

Information

Exchanged

Technical

Require-

ments R-

ID

1 New

consumption

/ generation

information is

available for

the SA/

generator

SA/Gen –

sending new

power-

related

information

Smart appliance

/ generator

sends

information

regarding

consumption to

the CEMS

SA Power

consumption

/ generation

information

SA /

generator

CEMS Individual

appliance

consumption

/ generation

2 CEMS

received

CEMS –

sending new

The CEMS

aggregates

House power

consumption

CEMS Display Total and/or

forecasted

FP7-ICT-318023/ D1.1 ver 2

Page 214 of 244

Figure 121: Mis-sequence diagram for the Disclosure of message attack

Table Scenario DE.02.01 details the disclosure of message content scenario. When the smart

appliance / generator sends information regarding consumption to the CEMS, the CEMS aggregates

and/or forecasts total consumption and sends this information to the display and to the EMG. The

consumption

/ generation

information

per individual

appliance

house power-

related

information

and/or

forecasts total

consumption

and sends this

information to

the display

/ generation

information

house

consumption

/ generation

3 CEMS

received

consumption

/ generation

information

per individual

appliance

CEMS –

sending new

house power-

related

information

The CEMS

aggregates

and/or

forecasts total

consumption

and sends this

information to

the EMG

House power

consumption

/ generation

information

CEMS EMG Total and/or

forecasted

house

consumption

/ generation

4 The attacker

intercepts the

message

Attacker –

reading

house power-

related

information

The attacker

intercepts the

message and

reads the

content about

power

consumption/

generation

House power

consumption

/ generation

information

SA

/generator

Attacker Total and/or

forecasted

house

consumption

/ generation

5 EMG received

(forecasted)

consumption

/ generation

EMG –

sending new

house power-

related

information

EMG forwards

information to

Actor D

House power

consumption

/ generation

information

EMG Actor D Total and/or

forecasted

house

consumption

/ generation

FP7-ICT-318023/ D1.1 ver 2

Page 215 of 244

attacker may intercept the message and if no cryptography method is used he/she reads the content

about power consumption/ generation.

As for the traffic analysis attack the only differences with respect the attack depicted in Figure 29

(i.e., the scenario DE.02.01) is that we are assuming that the adversary cannot understand the

message. Hence, the opponent needs to intercept several messages in order to observe the

communication pattern and discover relevant information (e.g., location and the identity of the

parties involved in the transmissions).



Name of Information

Exchanged


Metering – Metering Values

(periodically)

Metering – Metering Values

(aggregated)

Metering – Metering Values (Billing)

Metering – Parameter

Sub Metering – Metering Values

(periodically)

Sub Metering – Parameter

Control – Switching Command

Control – Status Information

Control – Parameter



Term Definition

AC Air Conditioning Unit

AMI Advanced Monitoring Infrastructure

AMR Automated Meter Reading

Cellular Network Cellular Network

CEMS Customer Energy Management System

CHP Local CHP

CI Customer Information

CLS Controllable Load System


DG Distributed Generation

DNO Distribution Network Operator

DoS Denial of Service

DSM Demand Side Management

ES Events and Status

ESP Energy Service Provider

FLIR Fault Location, Isolation and Restoration

HAN Home Area Network

EMG Energy Management Gateway

HES Head End System

ICT Network Communication Network

LNAP Local Network Access Point

MDA Metering Data Aggregator

MDMS Meter Data Management System

MIM Man In the Middle

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MM Measurement

MO Meter Operator

NAN Neighbourhood Area Network

NNAP Neighbourhood Network Access Point

Power Grid Power Grid

RES renewable energy sources

SM Smart Metering

SSM Supply Side Management

UI User Interface


Communication Hub

Control Hub

Household Appliance

Power Predictor

Control Entity

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11 Annex C - Table of Requirements

This annex contains the list of Requirements with the mapping on the project WP where are addressed.

Considering the priority of the Requirements these are marked as follows:

Now (the requirement is taken into serious consideration inside the project)

Wish (the requirement is considered desirable but not yet scheduled in the project activities)

Future (to be considered at some point in time)

11.1 Requirements for Medium Voltage Control Use Case

Requirement ID

Title Description WP2 WP3 WP4 WP5 WP6

System Level Requirements

Architectural

REQ_001 Number of primary substation per center

Each center controls <min,max> primary substations.Min, max values depend on the specific topology of the telecontrol grid. In the scenario addressed in SmartC2Net Min=20, Max = 100, Avg=60

x x

REQ_002 Grid topology Per each substation includes all the topological parameters, e.g. number of HV/MV transformers (i.e. n=2), number of MV lines(i.e. n=12), number of DER per MV line (i.e.n=10), number of MV loads per MV line(i.e. n=60/100), number of Secondary Substations per MV lines(i.e. n=40/100)

x x

REQ_003 Hosting capacity <0,15>MW generated by DERs connected to the MV lines of a primary substation

x x

Communication

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Requirement ID


REQ_004 DER network availability Any DER communication link should be available 8755 hs / year

x x

REQ_005 Compliance with standards The VC communications will be compliant with standard protocols, if available

x x x x

Dependability

REQ_006 Control infrastructure reliability and availability

The communication infrastructure for control operations should be available with a value of at least 99.999%(*) (Center -Substation communication) and 99.95 (DER- Substation communication) (*) This very restrictive requirement is meant to highlight that the availability needs to be near 100% on each time instant

x x

REQ_007 Control infrastructure redundancy

The communication infrastructure for control operations should use redundant heterogeneous communication links as backup solutions to fault tolerance

x x

Security

REQ_008 Control infrastructure security

The communication infrastructure for control operations should guarantee protection against intentional threats

x x

REQ_009 ICT maintenance Remote ICT maintenance activity to substation devices does not adversely affect the VC operation

x

REQ_010 ICT maintenance logging Remote ICT maintenance actions to substation devices are logged

x

Use Case Level Requirements

Communication

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Requirement ID


REQ_011 DER network heterogeneity Due to differences in the geographical coverage of communication technologies the VC shall work with heterogeneous DER networks (e.g., wired, wireless)

x x

REQ_012 Substation-DER data communication

The Substation - DER communication main measures are: bandwidth (i.e. 10 - 56 Kbps), data rate (i.e. measurements every 2 seconds)

x x x x

REQ_013 Centre-Substation data communication

The Center - Substation main measures are: bandwidth (i.e. 10 kbps), data rate (i.e. generation forecast update every 12 hours)

x x x x

REQ_014 Frequency of radio-based substation-DER communications

frequency band, i.e. in Europe LTE allowed frequencies are 800, 900, 1800, 2600 MHz and band numbers are 3, 7, 20

x x

REQ_015 Centre-Substation transmission time

end-to-end transmission delay (i.e. 20 ms-2 sec) x x x

REQ_016 Substation-DER transmission time

end-to-end transmission delay (i.e. 20 ms-15 sec) x x x

Functional

REQ_017 Control loop The control loop is triggered by critical events (e.g. under/over voltage event, TSO request, grid topology change). In absence of criticalities, the VC function is executed on a periodic base (e.g. every 15 minutes) for optimization purposes.

x x

REQ_018 Time out of voltage bound violation

<n> unit of time allowed to be out of voltage ranges (i.e. max frequency n= 0.1 sec 50.3 Hz (restrictive range), n=1.0 sec 51.5 Hz(permissive range). Min frequency n=0.1 sec 49.7 Hz (restrictive range), n=4.0 sec 47.5 Hz (permissive range))

x

REQ_019 Voltage deviation +/- 10% Vn x


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Requirement ID


REQ_020 Refresh Time of the DMS Operator HMI

The data values on the central operator interface are refreshed every 2 seconds

x x

REQ_021 Response Time The response time of the VC closed control loop, from the command issue to the end of the set point actuation, including the transmission time and the actuation time. It depends on actuation time constants of OLTC and DER power electronics. It is of the order of seconds

x

REQ_022 OLTC Actuation Time The time taken by OLTC for actuating a set point is 3 seconds

x x

REQ_023 Inverter Actuation Time The time taken by the inverter for actuating a set point is 1-2 seconds

x x

REQ_024 Synchronisation Time The substation and DER controllers provide functionality to synchronise their internal clock

x

Standard/Regulation

REQ_025 DER power wrt grid voltage Norm CEI 0-16 P < 0.1 MW: plants are connected to the LV grids 0.1 MW < P < 0.2 MW: plants may be connected either to the LV or to the MV grids 0.2 MW < P < 3 (6 in case of generation) MW: plants are connected to the MV grids 3 (6 in case of generation) MW < P < 10 MW: plants may be connected either to the MV or to the HV grids 10 MW < P < 100 MW: load plants are connected to the HV grids 10 MW < P < 200 MW: generation plants are connected to the HV grids

x x

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Requirement ID


REQ_026 DER communication systems

Norm CEI 0-16 In order to allow the evolution of distribution grids towards smart grids, it is necessary that all active customers are endowed with a communication system allowing the (real time) data exchange with the DSO. This will allow the DSO to implement optimization logics and to send all customers the signals implementing the actions (e.g. disconnection) needed to guarantee the security of the whole power system.

x x

Component Level Requirements

Architectural

REQ_027 Substation Network Integrity

In order to support the operation integrity of substation systems the communication interfaces in the substation devices have to be limited to essential functions

x

Communication

REQ_028 Ordered data streams The VC algorithm requires the undisturbed execution of acquisition and actuation sequences based on orders flows of status, events and commands

x

REQ_029 Load Forecast Transmission Rate

Load profiles are transmitted every 12 hours x x

REQ_030 Generation Forecast Transmission Rate

Generation forecasts are transmitted every 12 hours x x

REQ_031 Cost Transmission Rate Cost data are transmitted every 1 hour x x

REQ_032 Range of substation-DER communications

The DER-substation distance is within the range of the MV line length, in the order of 5 Km

x x

Functional

REQ_033 Generation Forecast Time Horizon

Active power production plans are given for 36 hours x x

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Requirement ID


REQ_034 Generation Forecast Time Resolution

Active power production plans are given with resolution of 1 hours

x x

REQ_035 Generation Forecast Update Rate

Active power production plans are updated every 12 hours

x x

REQ_036 Load Forecast Time Horizon Load plans are given for 36 hours x x

REQ_037 Load Forecast Time Resolution

Load plans are given with a resolution of 1 hours x x

REQ_038 Load Forecast Update Rate Load plans are updated every 12 hours x x

REQ_039 Cost Update Cost values are updated every 1 hour x x

Standard/Regulation

REQ_040 End-to-End communication integrity

IEC 62351 Part 3 End-to-end integrity of VC communications should be guaranteed through an appropriate configuration of the TLS protocol

x x x

REQ_041 Message Authentication IEC 62351 Part 6 Message authentication of VC communications will follow the standard indications for the specific protocol

x x x

Security

REQ_042 Integrity of transmitted data Transmitted data/measurements/commands are protected against intentional changes (Integrity of transmitted data is preserved in all data exchanges)

x x x

REQ_043 Integrity of stored data Stored data/measurements are protected against intentional changes

x x x

REQ_044 Action authorization Data are available to authorized actions only x x x

REQ_045 Authenticity of data Authenticity of data/measurements/commands is ensured

x x x

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Requirement ID


REQ_046 Communication logging Appropriate logs of VC application messages are made available

x x x

Table 5 Requirements for Medium Voltage Control Use Case

11.2 Requirements for EV Charging Use Case

Requirement ID



Architectural

REQ_200 Aggregator interaction The charging station has to report the aggregated demand, and the aggregator has to provide energy price information.

x

REQ_201 Meter aggregation

In order to realize the decentralized architecture, it is required that all the smart meters readings for households, charging station (aggregated metering), PV production and battery storage in that LV grid can be queried, forwarded or stored by the LV grid controller from a meter aggregation component.

x

x

Functional

REQ_202 Demand response The demand management control target of reducing for example the load in a LV by x% must affect the setpoints calculated by the MV controller accordingly.

x

REQ_203 Charging station reaction to local load increase or production decrease

sudden reduction of the available power in a charging station has to reduce the energy amount (not below the minimum) and the charging duration accordingly

x x

Interface

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Requirement ID


REQ_204 Interface LV controller-charging controller

the LV grid controller and the charging controller have to be able to exchange asynchronous unidirectional messages

x

REQ_205 Aggregator connection Each charging station must interact with an aggregator (aggr. Charging infrastructure manag.)

x

REQ_206 LV Grid-MV grid interface

The MV controller must be able to set setpoints on the LV controllers as a part of the VC goal and to determine P and Q injected, based on the flexibility reported by the LV controller

x x

Use Case Level Requirements

Architectural

REQ_207 Charging spots Charging spots are controlled either by the EMS (home scenario) or by a charging station controller

x

REQ_208 Routing and reservation The routing and reservation service must select the charging station and allocate charging resources to approaching EVs.

x

Interface

REQ_209 EV demand flexibility

An EV has to provide the charging station following demand flexibility data: plug-in time or an estimate of it, minimum amount of energy, maximum amout (full charging) , charging speed supported by the EV. It MAY provide the estimated parking duration.

x

REQ_210 Routing and reservation Charging stations have to report their load forecasts to the routing service, and would receive reservation requests.

x

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Requirement ID


REQ_211 EV connectivity with reservation service

The EV has to communicate wirelessly with the reservation server.

Standard/Regulation

REQ_212 Charging speeds

The charging power can vary from zero up to a maximum charging power supported by both the charging spot and the vehicle

x


Communication

REQ_213 Metering Network Monitoring

Metering network disfunction has to be recognized at the LV grid controller

x

REQ_214 LVcontroller-CS controller link monitoring

A connection disruption of the link LVGC to CS Controller has to be identified

x x

REQ_215 Control links to charging points monitoring

Communication disfunction of a charging point connection has to be identified

Functional

REQ_216 Charging station controller function

The charging station has to be able to calculate/estimate at any point in time the current and the future EV charging demand (time horizon of 6 hours for instance)

x

REQ_217 Charging schedule A charging station maintains a plan (schedule) for all known charging jobs, which is updated in case of event updates.

x

REQ_218 Meter readings The meter reading interval for some components is as low as 1 second.

x x

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Requirement ID


REQ_219 PV control Sudden increase of LV voltage at a PV generation bus has to be corrected by controlling signal from the LV controller to the PV inverter in a matter of X seconds

x x

REQ_220 Interface between car and CP

The EV should provide periodical energy flexibility profile (min and max). This may go beyond the interface specified in IEC15118

x

Security

REQ_221 Secure channel The communication between LVGC and charging stations shall be secured (encrypted, authenticated, etc.)

x

Table 6 Requirements for EV Charging Use Case

11.3 Requirements for External Generation Use Case

Requirement ID



Communication

REQ_400 Access network RTT measurements

Up-to-date Round Trip times measurements of the AN shall be available to the LVGC as well as the assets. RTT estimations shall be expressed in ms.

x x x

REQ_401 Access network throughput measurements

Up-to-date throughput measurements of the AN shall be available to the LVGC as well as the assets. Throughput estimations shall be expressed in bps.

x x x

REQ_402 Access network packet loss probability measurements

Up-to-date packet loss probability measurements of the AN shall be available to the LVGC as well as the assets. Packet loss probability estimations shall be expressed in %.

x x x

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Requirement ID


REQ_403 Access network connectivity measurements

Up-to-date connectivity measurements of the AN shall be available to the LVGC as well as the assets. Connectivity estimations shall be expressed as boolean.

x x x

REQ_404 Access network reconfiguration access

SmartC2Net platform should be able to reconfigure the AN network layers down to the data link layer.

x x

REQ_405 Provisioning of meta quality data of accessed data

The ITC system shall be able to provide meta data that indicates the reliability of the data being provided

x x x

Functional

REQ_406 Voltage variations The voltage profile in LV and MV feeders shall not exceed +/- 10% from the rated value as a 10 min average value. This is stated in DS/EN 50160 and in the Danish Recomedation 16 - Voltage Quality in LV grids.

x

REQ_407 Voltage dips/swells A voltage dip is not allowed to exceed -5% from the rated nominal value. A voltage swell is not allowed to exceed +5% from the rated nominal value. This is stated the Danish Recomedation 16 - Voltage Quality in LV grids. A voltage dip or swell is a rapid decrease or increase in voltage from one sample to the next. This is stated in DS/EN 50160 and in the Danish Recomedation 16 - Voltage Quality in LV grids.

x

Dependability

REQ_408 Resilient network performance operation

Even during network performance degradation, the system shall be able to continue without major loss of control

x x x

REQ_409 Reliable middleware components

Developed middleware components shall be operational to the extend that the components themselves will not fail during tests

x x x

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Requirement ID



Communication

REQ_410 Aggregation of Available Reactive Power

Aggregation of available reactive power shall be computed at secondary substation level. This algorithm shall consider the status and available power from flexible assets in LV feeders.

x x x

Functional

REQ_411 Individual Setpoint for active power - Asset

All flexible assets in MV/LV grids shall be able to receive and follow an admissible setpoint for active power from upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption. This setpoint shall be expressed in [kW].

x x x x

REQ_412 Individual Setpoint for reactive power - Asset

All flexible assets connected through a power converter to MV/LV grids or having reactive power control capabilities shall be able to receive and follow an admissible setpoint for reactive power from upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption. This setpoint shall be expressed in [kVAR].

x x x x

REQ_413 Available active power - Asset

All flexible assets in MV/LV grids shall be able to send information about available active power to upper hierarchical controller(s). This availability shall be defined as the difference from rated/potential active power of the device and the actual production/consumption. A positive sign means power injection into the grid while a negative sign

x x x x

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Requirement ID


means power consumption. The signal shall be expressed in [kW].

REQ_414 Available reactive power - Asset

All flexible assets connected through a power converter to MV/LV grids or having reactive power control capabilities shall be able to send information about available reactive power to upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption. The signal shall be expressed in [kW].

x x x x

REQ_415 Active Power Production - Asset

All flexible assets in MV/LV grids shall be able to send information about active power production to upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption. This signal shall be expressed in [kW].

x x x x

REQ_416 Reactive Power Production - Asset

All flexible assets connected through a power converter to MV/LV grids or having reactive power control capabilities shall be able to send information about reactive power production/consumption to upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption.The signal shall be expressed in [kVAR].

x x x x

REQ_417 Voltage measurements - Asset

All flexible assets in MV/LV grids equipped with voltage measurement devices at their Point of Connection (PoC) shall be able to provide measurement of voltage in PoC to upper hierarchical controller(s). This measurement signal shall be expressed in [V].

x x x x

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Requirement ID


REQ_418 State-of-Charge - Asset Energy storage systems connected to MV/LV grids shall provide to upper hierarchical control levels a signal reflecting their State-of-Charge (SoC). This signal shall be expressed in [%] based on the energy storages rated capacity.

x x x x

REQ_419 Setpoint for active power - LVGC

LVGC shall be able to receive and follow an admissible setpoint for active power received from MVGC. These setpoints shall be expressed in [kW].

x x x x

REQ_420 Setpoint for reactive power - LVGC

LVGC shall be able to receive and follow a setpoint for reactive power received from MVGC. These setpoints shall be expressed in [kVAR].

x x x x

REQ_421 Active power control - LVGC LVGC shall be able to control active power on MV side of the secondary substation. The active power control shall be made using the Setpoint from MVGC, measured active power from assets in LV grids as well as the total available power from the LV assets. The output of the active power control shall be a reference signal for the all flexible assets connected to LV feeders. in [kW].

x x

REQ_422 Active power dispatch - LVGC

LVGC shall be able to distribute the reference signal from active power control to flexible assets in LV grids as individual setpoints for active power. The individual setpoints for active power shall take into account actual power production and availability from the flexible assets . These individual setpoints signal shall be expressedin [kW].

x x

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Requirement ID


REQ_423 Reactive power control - LVGC

LVGC shall be able to control reactive power on MV side of the secondary substation. The reactive power control shall be made using the reactive power setpoint from MVGC or the reactive power reference from Voltage Control in LVGC, measured reactive power from flexible assets in LV grids as well as the total available power from the LV assets. The output of the reactive power control shall be a reference signal for the all flexible assets connected to LV feeders. This reference signal shall be expressed in [kVAR].

x x

REQ_424 Reactive power dispatch - LVGC

LVGC shall be able to compute and distribute the reference signal from reactive power control in LVGC to flexible assets in LV grids as individual setpoints for reactive power. The individual setpoints for reactive power shall take into account actual reactive power production and availability from the flexible assets . These individual setpoints signal shall be expressed in [kVAR].

x x

REQ_425 Aggregation of Available Active Power

Aggregation of available active power shall be computed at secondary substation level. This algorithm shall consider the status and available power from flexible assets in LV feeders.

x x x

Table 7 Requirements for External Generation Use Case

11.4 Requirements for AMR and CEMS Use Case

Requirement ID


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Requirement ID



Architectural

REQ_600 CEMS communication functionalities extensibility

The CEMS shall be extensible for the implementation of further / future communication functionalities

REQ_601 CEMS integrity The components of the CEMS shall be limited to the minimal necessary functionality to avoid costs and security risks

x x x x x

Communication

REQ_602 Home network heterogeneity

The CEMS shall work with heterogeneous home area network (e.g., wired, wireless)

x x x x x

REQ_603 Home network conditions heterogeneity

The CEMS shall work in variable network conditions (e.g., available bandwidth, delay, packet loss)

x x x

REQ_604 Cost Transmission Rate Cost data are transmitted every <n> time intervals x x

Functional

REQ_605 Smart Meter reading The smart meter periodically or on request provides meter readings and complete state and logging information.

x x x x x

REQ_606 EMG metering data computation

The EMG shall apply any necessary pre-computation on the local metering data (if applicable)

x x

REQ_607 EMG load shifting The EMG shall be able to issue commands for load shifting when allowed and possible, as requested by the HES

x x

REQ_608 Tariff information updates The CEMS shall be provided with actual tariff information in intervals of <n> / on tariff change

x x x

Interface

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Requirement ID


REQ_609 Control gateway network interfaces

The CEMS energy control sub-system shall have both WAN network interface and HAN interface

x x x

REQ_610 Metering Gateway network interfaces

The metering gateway sub-system shall have a WAN network interface as well as an interface with HAN

x x x

REQ_611 DER communication The CEMS / AMR house network shall allow the communication with house related DER

x x x

REQ_612 Flexible loads communication

The CEMS house network shall allow the communication with house related flexible load

x x x

REQ_613 User interaction system communication

The CEMS house network shall allow the communication with the house related user interaction subsystem (e.g., the external consumer display)

x x x

REQ_614 Metering Data Aggregation communication

The Smart Meter shall interface with the HES x x x

REQ_615 Aggregation communication The CEMS / AMR shall interface with the Aggregator (i.e., the Flexible load and DER aggregation) for controlling purpose

x x x x

REQ_616 CEMS Network communication

The CEMS shall interface with the communication network

x x x

REQ_617 CEMS power grid interface The CEMS shall interface with the power grid operator x x x x x

REQ_618 CEMS metering communication

The CEMS shall interface with the metering operator x x x x x

REQ_619 Private vehicle charging spot interaction

The CEMS house network shall allow the communication with private vehicle charging spots

x x x

REQ_620 CEMS and home automation communication

The CEMS house network shall allow the communication with home building automation

x x x

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Requirement ID


equipment

REQ_621 Smart Meter EMG connection

Smart meter and EMG might interface if not prohibited due to legal ruling

x x x

Dependability

REQ_622 Control infrastructure availability

The communication infrastructure for control operations should be highly available

x x x

REQ_623 Control infrastructure reliability

The communication infrastructure for control operations should be reliable

x x x

REQ_624 Energy Management Gateway reliability

The EMG shall have an availability of 99% x x x x x

REQ_625 Smart Meter availability The Smart Meters shall be available 99% of the year x x x x x

REQ_626 CEMS reliability The components of the CEMS shall possess a MTBF equal or greater than <n>

x


REQ_627 Intrusion detection false alarm rate

False positives in signaling the attempt to tamper the components and/or the communication shall be limited to a MAX_FP extent

x x x

REQ_628 Time Synchronization The EMG and Smart Meters shall be able to synchronize their clocks with the HES

x x

REQ_629 Metering Data Transmission The EMG / HES and Smart Meters shall be able to exchange metering data in intervals of down to 1 second / on demand

x x x

REQ_630 Access Point WAN Communication

The LNAP / NNAP shall provide a minimum data rate of approx. 20 Kbit/s per connected SM with a maximum Delay of 15 min.

x

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Requirement ID


REQ_631 Communication quality of service reports

The LNAP / NNAP shall monitor the quality of its WAN connection and report any deviation from normal operation to the EMG and HES

X x x x

Standard/Regulation

REQ_632 Compliance with standards The Communication Interfaces and Protocols shall be in compliance with standards wherever applicable

x x x x x

REQ_633 Usage data intervall The intervall in which customer usage information is supplied shall be in accordance with national regulations

x x x

Security

REQ_634 In-house message authentication

The messages exchanged between the components within the HAN that may exploit a shared medium (e.g. WiFi LAN) shall be secured against unauthorized accesses and modifications

x x x

REQ_635 WAN message authentication

The messages exchanged between the CEMS / AMR and external entities (e.g., Metering Aggregator) shall be secured against unauthorized accesses and modifications

x x x

REQ_636 house message confidentiality and privacy

The messages exchanged between the components on the customer shared network (e.g., Wi-Fi LAN) shall be secured against disclosure of information and traffic analysis

x x x

REQ_637 WAN message confidentiality and privacy

The messages exchanged between the CEMS / AMR and external entities (e.g., Metering Aggregator) shall be secured against disclosure of information and traffic analysis

x x x

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Requirement ID


REQ_638 Tamper and fraud detection / protection

The physical components of the CEMS / AMR shall be guarded against manipulation

x x

REQ_639 Software Security The EMG, Smart Meters and LNAP shall be robust against software attacks (for example no standard passwords)

x x x

REQ_640 Attack logging and reporting The EMG, Smart Meters and LNAP shall be able to report detected attacks and tempering attempts

x

REQ_641 Access logging Any access (especially remote ICT access) to the CEMS /AMR components shall be logged

X x

Table 8 Requirements of the AMR / CEMS Use Case

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12 Annex D - Table of KPIs

This annex contains the list of Key performance Indicators with the mapping on the project WP where are addressed.

Considering the scope of the KPI these are marked as follows:

DSO oriented

CSP oriented

CSO oriented

Aggregator oriented

Customer oriented

12.1 Key Performance Indicators for Medium Voltage Control Use Case

KPI_id KPI name Definition Goal WP2 WP3 WP

4 WP5

WP6

Power related KPIs

KPI_001 Unsupplied power Size of grid affected by an attack/fault 0 MW x

KPI_002 DER involved # DERs per HV/MV substation affected by an ICT attack/fault 0 x

KPI_003 Lines involved # MV lines per HV/MV substation affected by an ICT attack/fault 0 x

KPI_004 Loads involved # unsupplied MV loads per HV/MV substation affected by an ICT attack/fault 0 x

KPI_005 Substation involved # HV/MV substations per Control Centre affected by an ICT attack/fault 0 x

KPI_006 Energy losses Amount of lost energy Min value KWatt/h x

KPI_007 Grid Hosting Capacity Amount of RES power per MV line Max value MW x

KPI_008 Power Quality improvements Percentage reduction of voltage variations in MV lines Min value

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4 WP5

WP6

KPI_009 Grid events

# Overvoltages # Undervoltages # Topological changes Min value x

KPI_010 Power grid stability Deviation from optimal voltage profile Min value x

KPI_011 Integrity of measurements # Correct measurements Max value x

KPI_012 Integrity of state estimation # Correct state estimations Max value x

KPI_013 Correct setpoints computation # Setpoints computed correctly Max value x

KPI_014 Cost optimization DSO cost to obtain an optimize voltage profile Min value x

KPI_015 Correct setpoint receipt # Setpoints received correctly Max value x

KPI_016 Security gain_overvoltages # Overvoltages w/o security/ # Overvoltages with security Max value x

KPI_017 Security gain_undervoltages # Undervoltages w/o security/ # Undervoltages with security Max value x

KPI_018 Voltage value (V)

The actual voltage Vh(t) for each electrical component h at time t Setpoint value x

KPI_019 Active Power (P)

The actual active Ph(t) for each electrical component h at time t Setpoint value x

KPI_020 Reactive Power (Q)

The actual reactive Qh(t) power, for each electrical component h at time t. Setpoint value x

Communication related KPIs

KPI_021 Communication Network Availability Mean Time To Failure / Mean Time Between Failure

99,999% (5 minutes per year) for Control Center - Primary Substation communication 99.95% for x x x

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4 WP5

WP6

Primary Substation -DER communication

KPI_022 Fault Awareness Fault detection time Min value T (sec) x

KPI_023

Localization and Isolation Time Faster reaction time to grid faults and ICT attacks Min value T (sec) x

KPI_024 Security gain_measurements # Correct measurements received w/o security /# correct measurements received with security Min value x x x

KPI_025 Security gain_setpoints # Correct setpoints received w/o security /# correct setpoints received with security Min value x x x

KPI_026 Security gain_legal data rate Legal data rate w/o security / legal data rate with security Min value x x x x

KPI_027 Security gain_lost msgs (packets)

# Legal msgs (packets) lost with security /# legal msgs (packets) lost w/o security Min value x x x x

KPI_028 Security gain_discarded msgs (packets)

# Legal msgs (packets) discarded with security /# legal msgs (pakets) discarded w/o security Min value x x x x

KPI_029 Security gain_availability Availability w/o security /availability with security Min value x x x x

KPI_030 Security delay (Transmission) delay with security /# delay w/o security Min value x x x x

KPI_031 Security_IDS # Intrusion attempts detected Max value x

KPI_032 Security_prevention_illegal_action # Prevented illegal actions with security Max value x x

Generic KPIs

KPI_033 Population involved Percentage of people affected by an attack/fault 0%

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4 WP5

WP6

KPI_034 Satisfied requirements # Requirements satisfied Max value x x Table 9 Key Performance Indicators for Medium Voltage Control Use Case

12.2 Key Performance Indicators for EV charging Use Case

In Table 10 we list a number of performance indicators for the EV charging use case. With other words, running the scenario with a certain configuration of

energy demand, supply, topology, charging demand, presence of failures or not, daily prices, etc. will create a (unique) set of these performance indicators,

that should reflect the objectives of users, CSO, DSO, etc.

KPI_id KPI name Definition Goal WP2 WP3 WP4 WP5 WP6

Power related KPIs

KPI_200 Number of Grid Events Amount of grid events and type. [#] Types are:Over-current (line/trafo), Overvoltage (Bus), Undervoltage (Bus)

0 x

x

KPI_201 Severity of Grid Events relative value of a grid event: Over-current: I/I_max-1 (branch), Over-voltage: [U/U_max-1/ (Bus), Under-voltage: U_min/U-1 (Bus)

fraction <1 (0)

x

x

KPI_202 Renewable resource efficiency, general

Renewable energy fed into grid/ Renewable energy generated without curtailment

% x

x

KPI_203 EV Demand reduction control

Demand actual reduction/demand reduction target difference in % (0) x

x

KPI_204 accuracy of LV following MV set points

Accuracy of actual achieving the target P/Q using EV flexibility and PV control

difference in % x

x


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KPI_205 Degradation of power quality without meter data

Define degradation criteria (duration of operation without grid events, etc.) if flexibility/meter data is disrupted (CS or CEMS).

failure duration # of sampling periods x x

x

KPI_206 Degradation of power quality if LV grid controller - charging station fails

Define degradation criteria, if a charging station does not receive actuation from the LV controller for a duration

minutes max Value x x

x

KPI_207 Degradation if PV control network fails

Define degradation criteria in case CEMS with PV and storage does not receive actuation

minutes max Value x x

x

Economical related KPIs

KPI_208 charging load balancing among close charging stations

distribution of load =charged energy/available charging energy

variance 0

x

KPI_209 cost performance minimum cost of energy that could be achieved by the aggregator given the EV flexibility divided by actual CSO costs of energy constrained by the DSO

100% x

x

Generic KPIs

KPI_210 User satisfaction – Level of Service

Average over all EVs Charged energy/maximum requested energy [%].

100%

x

KPI_211 User satisfaction – Availability of Service

Number of served users/number of users requesting service 100%

x

Table 10 Key Performance Indicators for EV charging Use Case

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12.3 Key Performance Indicators for External Generation Use Case


Power related KPIs

KPI_400 Voltage limits in LV and MV feeders

The voltage profile in LV and MV feeders shall not exceed +-10% from the rated value as a 10 min average value.

10%

x x

KPI_401 Rapid Voltage change limit in LV feeders

Rapid voltage changes should not exceed +-5% of the rated value.

5%

x x

KPI_402 Rapid Voltage change limit in MV feeders

Rapid voltage changes should not exceed +-4% of the rated value.

4%

x x


KPI_403 Access network packet loss limit

The application layer packet loss probability shall be low enough to allow the LVGC to adhere to its voltage limits.

<0.01 %* x x

x

KPI_404 Wide area network packet loss limit

The application layer packet loss probability shall be low enough to allow the MVGC to adhere to its voltage limits.

<0.01%* x x

KPI_405 Access network delay limit The application layer packet delay shall be low enough to allow the LVGC to adhere to its voltage limits.

<1 ms* x x

x

KPI_406 Wide area network delay limit

The application layer packet delay shall be low enough to allow the MVGC to adhere to its voltage limits.

<1 ms* x x

Table 11 Key Performance Indicators for External Generation Use Case

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12.4 Key Performance Indicators for AMR and CEMS Use Case

The Key Performance Indicators (KPI) of the AMR and CEMS use case are listed in Table 12


Power related KPIs

KPI_600

Accuracy of energy consumption measurement / estimation

Accuracy of energy consumption measurement / estimation

% Max Value

x x

KPI_601 Balancing and maximization of power grid utilization

Avoidance of peaks and valley of energy consumption in the smart grid

100% x x x

KPI_602 Improvement of power grid stability

Average deviation of grid frequency and phase from normal operation and duration of power grid outages

% Min value x x

KPI_603 DER utilization Utilization of distributed energy resources 100% x x


KPI_604 Availability of Service Availability of the Service, i.e. downtimes / failures 100% x x x x x

KPI_605 Successful transmissions of metering data

Ration of successful metering data transmissions to failed transmissions (i.e. necessary retransmissions)

100% x x x

KPI_606 Currentness of customer feedback system and metering data

Currentness of energy usage and tariff data displayed to the customer and metering data send to the HES

delta t Max Value x x x

KPI_607 Maintainability Ease of deploying Soft- and Hardware upgrades € & time Max Value x

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Economical related KPIs

KPI_608 Amount of energy saved Energy saved per month kWh Max Value x x

KPI_609 Reduction of energy costs Energy costs saved per month € Max Value

KPI_610 Amount of acquired energy consumption data

Ratio of metered consumption to unmetered consumption 100%

KPI_611 Accuracy of energy tariff data

Deviation of customer energy tariffs and prices on the energy market

€ Min Value

KPI_612 Reduction of non-technical energy losses

Minimization of non-technical energy losses (i.e. illegal, unbilled energy consumption)

100% x x

Generic KPIs

KPI_613 User satisfaction with AMR / CEMS

General user satisfaction with AMR / CEMS functionality 100%

x

KPI_614 User satisfaction – Availability of Service

Served users / users requesting service 100% x x x x x

KPI_615 End-user usability Ease of use of the CEMS from an end-user perspective (for example through a user friendly interface)

Max. value

Table 12 Key Performance Indicators of the AMR / CEMS Use Case