Paving the way for Grid Modernisationieeepes-thailand.org/files/DinnerTalk2016/Siemens... · Spectrum Power ANM - Active Network Management Foster renewable generation and keep the

Paving the way for Grid

Modernisation

IEEE PES Dinner Talk 2016 | Bangkok, November

16, 2016 | Anand Menon

siemens.com Restricted © Siemens AG 2016

16.11.2016

Restricted © Siemens AG 2016

Page 2 EM Division ASEAN

Growth of power demand is driving investment

in transmission and distribution

Main driver for

the Energy

Management

market

Renewables and

distributed power

generation grow

above average

2015 2030

Hydro 2.1%

Gas 2.4%

Wind 7.1%

PV 13.8%

Nuclear 1.4%

Coal 1.0%

10.1

Oil -0.2%

3.0%

6.5

CAGR 15-30e

Biomass 5.9%

Global power generation capacity in TW

16.11.2016



Energy system increasingly distributed and driven by

“Prosumer” – new competitors and business models and

transactive layer emerging

Energy chain “classic”

Increasingly distributed: improved integration, resilient networks and expanded services „Prosumer“: New customer choices

16.11.2016



Growing share of renewables and distributed

generation calls for end-to-end energy management

• Further development of electrification levels in emerging economies

• Grid modernization required in many regions

More electrification

• Increasing level of renewable and distributed generation

• Grid stability challenges

Distributed generation

16.11.2016



Spectrum Power ANM - Active Network Management

Foster renewable generation and keep the voltage within the limits

Real time thermal ratingEnergy storage Voltage control device Controllable generation Controllable loads

Network state

1

Problem detection

2

Decision making

3

Set-point command

4

Active Network Management System

No clear direction of

power flow

Violation of voltage

limits

Overload situations

Increasing installation of

renewable energies

Observability

improvement

Volt-/VAR management

Capacity management

Challenges

Improves situational

awareness

Reduces voltage band

violations and equipment

overloads

Minimizes distribution

losses

Supports various network

components

Optimizes in full closed-

loop operation

Scalable and flexible

Highlights

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Page 6 EM Division ASEAN 6

FEEDER LEVEL

16.11.2016



Voltage

characteristic

depends on infed

power and grid

impedance

Meters of a grid segment measure Voltages - Phase Angles - Currents and other PQ

parameters at the same time which makes the grid transparent.

Generation (e.g. Micro generation / PV)

U

l

R+jX R+jX R+jX R+jX I

Voltage limits

loads

~ Controllable

Transformer

MV LV

Smart Grid Applications

Eyes in the network

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REGIONAL LEVEL

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Active Network Management Smart voltage control and conservation voltage reduction

Generators

R+jX R+jX R+jX R+jX I

Q

Line Sections

Consumers

Consumers & distributed generation no control

with storage control

with VAR control (generators, capacitor banks)

with load control

smart control – combination of control devices

with transformer tap control

Line length

Voltage

VN

Vmax

Vmin

Q Q

smart control – conservation voltage reduction (CVR)

16.11.2016



Spectrum Power Active Network Management Active Network Management based on real time state

estimation

Network state

Processing of measurements,

status indications and network

topology

1

Decision making

Generic on-line optimization,

Minimizing limit violations, losses,

operational cost;

conservation voltage reduction

3

Problem Detection

Real time state estimation

using P, Q, I, V

2

Set-point command

Closed loop execution of

calculated set-point commands

4

16.11.2016



Control

RDC Primary

RDC

Secondary

Optimizati

on

Spectrum Power Active Network Management

System components of an hierarchical solution

Da

ta C

on

ce

ntr

ato

r

Battery

Capacity

Management

OLTC AVC

Management

Capacitor

Control

Lo

ca

l C

oo

rdin

ation

& P

rio

ritiza

tio

n

Thermal

Modelling

Local

Thermal

Management Local

Voltage

Management

Fro

nt-

En

d

Capacity

Management

Voltage

Management

SC

AD

A

Topological

Coloring

State

Estimation

Volt / Var

Optimization

Central Control

(Siemens Spectrum Power Active Network Management)

Control

Center

& Assets

Local Control

(Siemens Autonomous Substation Controller)

16.11.2016



Active Network Management Next step: Provision of ancillary services by distributed generation

Estimate

Voltage

Violations

Overloads

Significant

measurement

change

Topology

change

Configured

cycle

Significant

target value

change

Control

16.11.2016



Northern Powergrid

Overview

Distribution Network Operator in

North East England and Yorkshire

3.8 Million customers

Area 25.000 km2

31.000 substations

91.000 km of network

Voltage bands from 132 kV down to 230 V

16.11.2016



Northern Power Grid (NPG) – Grand Unified Scheme

Benefits

• Integrated multi-level hierarchical solution

• Cost reduction and accelerated delivery by using a combination of

network technologies and flexible customer response

Challenge

• Integration of renewable sources push the existing distribution

network to its boundaries causing

- Voltage violations

- Thermal overload of primary equipment

• Multi-level hierarchical solution incorporating a central

Application system with a data warehouse and an

autonomous substation controller using a wide area

communications system

• The Grand Unified Scheme (GUS) brings together

battery storage (6x5MVA), enhanced voltage control,

demand response and real-time thermal rating in

closed loop for optimal grid operation

Solution

Spectrum Power

Active Network

Management

Project partner: Northern Power Grid

Country: United Kingdom

Equipment: 1200 secondary substations, 15 autonomous

substation controllers, 7 batteries, 2 line voltage regulators, 6

controllable transformers, 1 capacitor bank, 10 demand

response contracts

16.11.2016



CONTROL CENTRE LEVEL

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Fault & Outage Management

SCADA / OMS / DMS: The combined solution

Next-generation power distribution management.

The Integration of Distribution SCADA, Advanced Fault and Network Analysis and Outage

Management operated on one technology platform with one

Common User Interface.

Monitor & Operate

Monitor, control and optimize the secure

operation of the electrical distribution network.

Track & Restore Proactively and safely guide operators when

needed most, i.e. during storms and outage-

related restoration activities.

Analyze & Optimize Reduce network loading at peak times and

increase asset utilization, network efficiency

and reliability.

P

16.11.2016



Spectrum PowerTM 7 - Advanced DMS

Distribution Network Applications

16.11.2016



Voltage Stabilization:

Spectrum PowerTM 7 - Advanced DMS

Network Optimization VVC – Use Case

DSSE detects violations

• Network is monitored

continuously by DSSE

• Voltage violations are

indicated in single line

diagram and reported

as alarm

Run VVC

• Manual start:

• User selects violated

equipment, defines

objective and other

settings and starts VVC

• Automatic start

• DSSE violations trigger

VVC. VVC runs with

preconfigured settings

Forward solution

to SPM and execute

• VVC proposes switching

actions for volt / var

controls to improve the

voltage profile

• User may review the

proposed

changes/optimization

• The switching actions are

forwarded as switching

procedure to SPM

(Switching Procedure

Management)

• The switching actions are

executed with SPM

16.11.2016



And what makes the difference ?

Spectrum Power ADMS

with integrated Active

Network Management

best-in-class for secure

integration of distributed

generation

16.11.2016



STORAGE SUPPORT

16.11.2016



Energy Storage for very different purposes

SIESTORAGE

Decentralized

generation

Min

ute

s

Seconds

Hours

D

ays

Weeks

Distribution grid Transmission grid

Reserve capacity

Variable generation

(PV, Wind) Consumer /

Prosumer

Conventional power

plants

Application Segmentation

• Response to emergencies

• Residential/

commercial

selfsupply

• Industrial peak

shaving

• On-grid + grid

upgrade deferral

• Remote areas/ off-

grid

• Avoid curtailment

• Rules for grid

integration

• Energy arbitrage

(time shifting)

• Increase flexibility

/ load optimization

• Ensure stability

• Load optimization

• Ensure power

system

stability

1 kW Power 100 kW 1 MW 10 MW 20 MW

Reserves

Time shifting

Firming

System

stability

16.11.2016



Applications and use cases

APPLICATIONS USE CASES

Electricity supply for

microgrids/stand-alone grids

• Black start

• Ramping control

• Time shifting

• Capacity firming

• Diesel offset

• Frequency regulation (Primary Control Reserve)

• Peak load management

Electricity supply for industry

• Black start

• Backup energy

• Diesel offset

• Peak load management

Integration of renewable

energy

• Ramping control

• Time shifting

• Capacity firming

T&D upgrade deferral • Peak load management

• Ramping control

• Frequency regulation

16.11.2016



Large penetration of PV

Regulation driven grid implementation

time [h]

Features • Controlled feed to grid

using battery energy

storage system for

ramping

• Peak shaving

• Peak shifting

Logic • Applications

time [h]

16.11.2016



STORAGE APPLICATIONS

SIESTORAGE – What is it ?

16.11.2016



SIESTORAGE energy storage system VEO (Vulkan Energie Oderbrücke GmbH),

Eisenhüttenstadt, Germany

• Power output: 2.8 MVA / 1.2 MW, Capacity: 720

kWh

• Supply security for the AMEH steel works even

when the local 110 kV integrated power grid is

interrupted

• Supply dependency of the VEO industrial power

plant on through:

a) Switchover to a standalone grid in the event of

a malfunction and

b) Black start of a gas turbine (if switchover is

unsuccessful)

• Grid stabilization (frequency, voltage)

• Intelligent load peak management (energy

management system)

SIESTORAGE

1 Modular battery storage system

2 Starting motor of the gas turbine

3 Natural gas turbine

4 Standalone grid/plant grid

5 Public grid

6 Integrated steel works

7 Power failure/blackout in the local grid

16.11.2016



SIESTORAGE energy storage system

Enel Distribuzione S.p.A., Italy

• 1 MVA /500 kWh SIESTORAGE system

• Used for storing electricity in a smart grid environment

• Network stabilization with infeed of power generated from

decentralized, renewable sources

• Testing of black start suitability for smaller grid sections

• Fast source of energy with controllable system

perturbations

Paola Petroni

Head of Network Technologies,

Infrastructure and Networks Division

We need better ways to store energy for

our pilot projects, and because Siemens

was strongly committed to investing its

expertise and efforts into the new

energy storage system, we chose

Siemens from among seven bidders.

Cus-

tomer

logo

Container solution for decentralized setup for renewable energy

producers or in neural network nodes

16.11.2016



MICROGRIDS

16.11.2016



Renewable Integration => Microgrids

No clear direction of

power flow

Violation of voltage limits

Overload situations

Increasing installation of

renewable energies

Observability

improvement

Volt-/VAR management

Capacity management

Critical Infrastructures / Military

Institutions

Campuses Remote Locations and Islands

Industries with critical

Processes

• Reliable network operation

in diverse scenarios

• Inclusion of all network

assets, distributed

generation, storage systems

and loads

• Modular, allowing a flexible

and scalable structure

• Forecasting and planning of

generation and loads

• Load Frequency Control

• Real-time optimization

16.11.2016



Components and Structure of a Microgrid

16.11.2016



Microgrid – Entire Spectrum

Features

• Distributed generator

control also for

renewables

• Network synchronisation

• Load Control

• Storage control

• Online control via HMI

• Grid monitoring and

control

• Generation forecast

• Load forecast

• Schedule optimization

• Enhanced SCADA

functionality

• Dynamic grid constraint

consideration using state

estimator function

What can be achieved with

this type of configuration:

• Load Balancing

• Peak Shaving

• Diesel Offset

• Simple integration of

renewables

• Grid Independence (Island

Mode) - depending on

generation set

• Interactive operator control for

grid generation, storage and

load

• Archiving and post event

analysis

• Portfolio optimization

• Integration and optimal

commercial use of renewable

energy

• Export of excess energy

• e-Car integration

16.11.2016



Functionality of a fully integrated Microgrid solution

• Reliable network

operation in diverse

scenarios

• Inclusion of all network

assets, distributed

generation, storage

systems and loads

• Modular, allowing a

flexible and scalable

structure

• Forecasting and

planning of generation

and loads

• Load Frequency Control

• Real-time optimization

16.11.2016



Landscape of Microgrids / Renewable Integration

Applications

Reliability Optimisation Market Integration

$ $

Value

Proposition

Portfolio

Element

Preferred

Reduction of power supply

interruptions OPEX savings Additional revenue

Microgrid Controller Microgrid Manager Microgrid Management System

• Spectrum Power 5

• Spectrum Power 7 MGMS

• SICAM TM

• SICAM TM + SCC

• SICAM SCC

+ DEMS

• Spectrum Power 5

• Spectrum Power

ANM

Business

Allocation DG SYS DG SWS

16.11.2016



Spectrum Power MGMS Architecture

Spectrum Power 7 SCADA Platform

Current Operating

Plan

Generation Management

Load Shed

Voltage

Control

Generation

Control

Microgrid

Optimization

Module

Load and

Generation

Forecast

Information Model

Manager

Historical

Information

System

16.11.2016



MGMS Dashboard

16.11.2016



Blue Lake Rancheria - Microgrid Project

• Demonstrate a low carbon-based

microgrid for a critical community facility

• Install a microgrid that is capable of

powering a Red Cross shelter in an

emergency

• Integrate renewable photovoltaic and

biomass power, battery storage, diesel

generation, and controllable demands

into an microgrid island.

• Siemens Spectrum Power Microgrid

Management System (MGMS), an advanced

software control solution based on a powerful

utility distribution SCADA platform, will be

installed to integrate and automate:

• 700 kW Load includes Casino, Hotel,

Tribal Offices

• 1 MW Diesel generator for base

generation

• Renewable generation sources

including:

• 175 kW Fuel cell + biomass

• 500 kW Solar PV & 800 kWh

Battery

• Economic dispatch of solar/battery

system

• Siemens PTI Electrical System Stability and

Grid Impact Study

• Provides the ability to island and supply

uninterrupted electric power for at least 7

days during a real or simulated grid outage

• Achieves renewable energy generation >

40% of annual production

• Enables participation in one or more PG&E

demand response programs

• Reduces annual electrical consumption from

the grid of at least 680 MWh

• Achieves at least 25% energy cost savings

over 1 year of operation

• Reduces annual greenhouse gas emissions

by at least 195 metric tons CO2

Challenge Solution Benefits

Project Profile

Blue Lake Rancheria - Blue Lake,

CA

Native American Reservation

Estimated Peak Load: ~700KW

Project Partners: PG&E, Idaho

National Lab, Tesla, REC solar,

Humboldt University Schatz Energy

Research Center, California Energy

Commission

Project started August 2015

16.11.2016



Algonquin College

• Optimize campus energy costs through

the lowest cost generation mix

• Achieve campus-level energy efficiency

leveraging existing building automation

• Enable advanced Microgrid functionality

such as islanding from the grid, and

ancillary programs such as demand

response

Project Profile

Algonquin College, Ottawa, Ontario,

Canada

Educational Institution

Peak demand: 4,656 kW

• Siemens Spectrum Power Microgrid

Management System (MGMS) will be

installed to integrate, control and optimize 4

MW Co-Gen, 10 kw solar, battery, Electric

Vehicles, utility metered electricity, and more

• MGMS enables use of the most cost

efficient energy mix creating savings

for the end customer

• Islanding mode including load

shedding and management

• Interface with Siemens’ Building

Automation system enabling BAS

optimization in Microgrid controller

decisions

• Integration and optimization of

renewables

• Enable student research and

learning

• Provides resilience through black start

capability

• Enables potential savings of $850k* per

year for 20 years (microgrid energy

center)

*Note: Based on Siemens value estimation tool

Challenge Proposed Solution Benefits

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRxqFQoTCNrAnouKs8cCFUc9Ggod9gAFSQ&url=http://www.algonquincollege.com/future-students/programs/&ei=52DTVZqxK8f6aPaBlMgE&bvm=bv.99804247,d.d2s&psig=AFQjCNH40mSFXqxaI5AVFmW3kqq3gKWDsA&ust=1440002660139206

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRxqFQoTCLLlhrO-tccCFUk6GgodtF4OXQ&url=http://www.algonquincollege.com/public-relations/algonquin-college-history/&ei=MaTUVfKIFMn0aLS9uegF&bvm=bv.99804247,d.d2s&psig=AFQjCNFLcErtq_5cpy7p5nVq7CNqGho1AA&ust=1440085363053832

16.11.2016



Smart Polygeneration Microgrid for Savona

Campus

University of Genoa, Italy

• Low efficiency of the campus grid due to

static manual operation

• Campus is entirely dependent on main

utility grid for energy supply

• Variation in seasonal demand

Project Profile

University of Genoa - Savona, Italy

Institution

Duration: 9 months

Electric Load: 250kW

Thermal Load: 300kW

• 3-phase low voltage (400 V line-to-line)

“intelligent” distribution system inside the campus

• Siemens Microgrid Management System

integrates and automates:

• 3 mCHP Nat gas turbines (160 kWe,

284 kWth)

• 1 PV field (80 kWp);

• 3 CSP equipped with Stirling engines (3

kWe;

9 kWth);

• 1 absorption chiller (H2O/LiBr) with a

storage tank;

• 1 electrical storage: NaNiCl2 batteries

(140 kWh)

• 2 PEV charging stations

• Total capacity: 250kW electricity + 300 kW

thermal

(for heating)

• High degree of efficiency in power

generation

• Optimizes across different energy

sources

• Better management of renewable energy

sources

• Reductions in emissions by a total of 120

metric tons CO2 per year

• Increases system resiliency

• Research future and advanced

technologies using microgrid

Challenge Solution Benefits

16.11.2016



Anand Menon

CTO & Head of Engineering

Energy Management Division

ASEAN region

Siemens Malaysia Sdn. Bhd.

Phone: +60 17 6938269

E-mail:

[email protected]

Thank You!

16.11.2016



Network Expansions

RE Integration

16.11.2016



Smart Grid Applications

MV and LV - Sensors and Controllers

110KV 20kV

63MVA 20KV / 2000A / 20KA

20kV 400/230V

630KVA

20kV 400/230V

240KVA

20kV 400/230V

240KVA

PV PV

PV PV PV

PV

G2

G1

G2 G2 Last

Last

Last

Last

Last

G1

G2

Grid Controller Middlevoltage

Grid Controller Lowvoltage

Sensor Middlevoltage

Sensor / Meter Lowvoltage

Sensors / Controllers

Meters are geographically in an

optimal position, in order to

deliver data from the low voltage

network

Simeas P55 in the transformer statation

variable transformer

16.11.2016



2.) Express Grid Data Access (EGDA)

How to connect Sensors and FITformer

400V

PLC

rogowski

device

smart

meter IEC

data point

U[V]

l

voltage - band

tra

nsfo

rmer

sta

tion

smart sensor

modbus

RTU

sla

ve

maste

r

controller

U local

U end of

feeder(s)

(sensor)

Data from EGDA is available

via protocol firmware SGAP00

on CPC30 as

IEC-60870-5-101

Type36 (short floating point) RS232 RS485

converter

modbus

RTU

master slave

IEC-60870-5-101

Documents

Paving the way for Grid Modernisationieeepes-thailand.org/files/DinnerTalk2016/Siemens... · Spectrum Power ANM - Active Network Management Foster renewable generation and keep the