Preparing for Distributed Energy · PDF fileManagement System (ADMS) that enables ... ADMS optimizes DER management; grid operations and planning ... Preparing for Distributed Energy

Preparing for Distributed Energy Resources

Executive summaryMany utilities are turning to Smart Grid solutions such as distributed energy resources (DERs)—small-scale renewable energy sources and energy storage—to balance load and capacity without building large-scale generation. This paper explains how successful DER implementation depends upon an Advanced Distribution Management System (ADMS) that enables real-time, software-based network modeling to accurately forecast, monitor, control, and analyze the contribution of distributed energy to the grid.

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Summary

Executive Summary .................................................................................... p 1

Introduction ................................................................................................ p 2

The state of the Smart Grid ......................................................................... p 4

What’s needed to move Smart Grid implementations ahead? ...................... p 5

Distributed energy resources are becoming a ‘new normal’ ......................... p 6

Load transfer with distributed generation .................................................... p 7

Getting ready with software ......................................................................... p 8

ADMS optimizes DER management; grid operations and planning .............. p 9

Conclusion .................................................................................................. p 11

Executive summary


White paper | 01

More and more, as utilities face decreasing margin between system load and

system capacity, they are in need of innovative smart grid solutions that can help

them effectively disperse and store energy and manage load to meet resource

requirements. Many are incorporating Distributed Energy Resources (DERs) to

help fill the gap while, at the same time, meet requirements for reduced emissions

and energy independence; these utilities will require the capability to accurately

forecast and control DER contribution to the network, to assure security and grid

reliability.

Advanced smart grid software designed to support DER management and

optimize grid operations and planning works with a real-time network model,

based on an accurate geodatabase and incorporating data from operational

systems such as a supervisory control and data acquisition (SCADA) system

and outage management system (OMS). Along with real-time visualization and

monitoring of network status, this Advanced Distribution Management System

– ADMS – provides a host of analytical tools that recommend the most optimal

device operations, or optionally automate device operations, to maximize network

efficiency and reliability. For example, the utility can apply Volt/VAR control to

reduce feeder voltage automatically with no effect on the consumer. Detailed load

profiling and load forecasting based on integrated weather feeds yield network

load forecasting for effective renewables integration. Network simulation helps

forecast medium-term and long-term load and supports effective development

and planning.

ADMS functionality and tools are demonstrating that utilities can effectively

manage demand without building large-scale generation.

Introduction

White paper | 02


The deployment of Distributed Energy Resources (DERs) is growing as is

the impact on electric utility distribution networks. While DERs are increasing

renewable energy with their multitude of benefits, there are many concerns

utilities must tackle to assure successful management of a diverse and

distributed energy mix.

Here, we discuss how DERs will contribute to achieving a smart electric grid and

how proper network planning, monitoring, analysis, and control, through ADMS,

can transform distributed generation into an efficient asset.



White paper | 04

The state of the Smart Grid

Up to nowEnergy policies are evolving worldwide, with differing

regulations from country to country and within

countries, helping drive Smart Grid investment

priorities. While the impetus to embark on advanced

Smart Grid initiatives varies, and no two projects are

the same, there are some common drivers:

• Regulations promoting reduced carbon emissions,

renewable technology and energy independence

- Different locations have more advanced

regulations than others

- Wind and solar have become viable energy

sources

- Storage is enabling permanent and on-demand

load shifting

• Stimulus funding helping advance deployment of

advanced technology

• Convergence of traditional generation capacity and

increasing system load

Near term Regional factors are likely to predominate:

• Electric vehicles (EVs) will begin to make an impact

on the distribution system. Their initial effect is

not expected to be system-wide; instead, early

adopters are likely to be localized within specific

areas of a utility’s service territory, impacting the

network at the distribution transformer level. See

sidebar discussion for more about planning for the

deployment of EVs.

• As volatile renewables – those such as solar and

wind that are intermittent sources – see increased

deployment, Information Technology (IT) solutions

will be integral to their success and storage

technology will have to advance.

• Policy concerns – Customer privacy and cyber

security will continue to provide some challenge to

Smart Grid implementation.

Terminology

Here’s how we are using some common industry terms –

Distributed Energy Resources (DERs) – small-scale power generation technology that supplies less than 10 MW and is located throughout the distribution network. Increasingly, DERs consist of renewable energy and energy storage – making DERs a popular component of Smart Grid implementations.

Distributed Generation (DG) – referring to any dispersed generation less than 100 MW. In this paper we are considering DG as a smaller-scale, subset of DER

Electric Vehicles (EV) – serve as a source of significant load but can also serve as a form of virtual generation (storage)

Demand Response (DR) – management of consumption, anywhere along a feeder, in response to supply conditions

Microgrid – a local network of DERs that is a subset of the distribution network. It can operate in an isolated manner or be connected. Microgrid management targets local energy supply and demand.


White paper | 05

What’s needed to move Smart Grid implementations ahead?Many utilities are experiencing a common trend:

the margin between system load and system

capacity is decreasing and is expected to continue

to decrease. The utility can incorporate new power

‘sources’, purchased or generated; improve demand

management; and add storage capability in order to

maintain a healthy margin between load and capacity.

Management of demand is the option least utilized,

yet it poses significant potential because of the

several innovative ways it can be implemented.

Need to fill the gapThe Ontario Power Authority of Canada collected

data identifying the existing power sources that have

been meeting its resource requirements over the past

few years and its forecast of available generation in

the coming years; see Figure 1. This report forecasts

retirement of most existing nuclear facilities, a

decrease in reliance on existing oil and gas and coal

sources and continuation of existing renewables.

What power sources, including ‘virtual sources’, are

to be added to meet the increasing annual peak

forecasts? What is going to fill the gap? Many utilities

will be required to disperse and store energy and

manage load to meet resource requirements.

Figure 1. Expected change in how existing power sources contribute toward resource requirements (effective MW). Source: Ontario Power Authority

Electric vehicles

Utility thought leaders concur that penetration of EVs will initially be concentrated in localized areas (early adopter neighborhoods) – impacting secondary networks of the distribution system.

Nevertheless, penetration of EVs will require planning:

• Battery-charging scenarios vary: the higher the charging level, the faster the charge and the greater the energy demand.

• Permitting processes should be defined to identify where EVs will reside.

• Rate structures are needed to help control charging.

• Real-time monitoring can help model demand accurately.

• Network planning can preemptively address potential issues.

• Promotion by the utility can help encourage desired charging habits.

The utility armed with mitigation strategies will be best prepared to meet the demand and supply challenges, and the environmental and commercial benefits, of EVs.


White paper | 06

Distributed energy resources are becoming a ‘new normal’Regulatory driver While some utility customers are installing renewable

generation on their own initiative, the primary drive

is coming from regulations that push for reduced

emissions and energy independence. For example –

The Canadian province of Ontario has implemented

an aggressive feed-in tariff (FIT) that supports

penetration of DER (http://fit.powerauthority.on.ca/).

California’s general strategy of cutting GHG

emissions and creating green jobs includes these

2020 targets: 33 percent of energy sourced from

renewables; installation of one million solar rooftops;

and stimulation of EV deployment and battery storage

implementation

(http://www.energy.ca.gov/energypolicy/index.html)

New business modelUtilities incorporating DER will have to plan for

new connections and ways to achieve accurate

forecasting and the control needed for grid reliability

and security.

For these utilities, distributed energy resources will

become a major factor in the new utility business

model; see Figure 2. At the heart of the new model

is the centralized intelligence system that integrates

and manages devices, with intelligence moving out

to provide more comprehensive management and

collect more data.

Figure 2. Distributing energy resources is expected to be the new paradigm in utility management. Source: Progress Energy.


White paper | 07

Load transfer with distributed generationFigure 3 illustrates, very simply, the existence of DG

in the event of a feeder trip. The DG, along with the

neighboring feeder, might help back-feed the feeder

in question. Real-time data and accurate network

representation are needed to facilitate the response

decisions required for safe and reliable transfer of

load. The presence of DG will benefit from adaptive

relay protection to properly deal with the initial fault

and manage increasing load following restoration.

Figure 3. Managing load with distributed generation.


White paper | 08

Getting ready with software

The next logical question: how do utilities manage

load – to maintain the margin between load and

system capacity – and plan for and leverage DER,

to meet increasing demand?

Operating the electric distribution network

with a growing number of distributed energy

devices (DERs) is simply not feasible without

the deployment of advanced software analytics

– specifically, a real-time network model that

will support operations management, network

optimization and comprehensive planning. This

model resides at the centralized control center

illustrated in Figure 2 and is created and maintained

by advanced Smart Grid software. With this

software, utilities can integrate DER to defer capital

expenditures for new generation sources; see

Figure 4.

Figure 4. Distribution network load is expected to continue to increase, in large part due to population growth and the proliferation of consumer technology. A smart IT control system enables network management that will, in effect, increase system capacity and maintain the margin between load and capacity without investment in new and costly traditional generation facilities.


White paper | 9

ADMS optimizes DER management; grid operations and planningADMS is the large-scale IT control system that can

serve as the brain of the distribution network and

support network operating decisions. It leverages the

GIS as-built network model and integrates with many

operational systems such as supervisory control

and data acquisition (SCADA) systems and outage

management systems (OMS), to create a real-time

network model; see Figure 5.

Utilities minimize losses and maximize reliability and

safety by applying ADMS functionality to manage the

distribution network throughout the service territory in

a real-time manner. The ideal ADMS approach offers

three operating approaches to best meet reliability

and efficiency goals:

• Provide users with the solution’s advanced tools

and visual context

• Prompt users with recommended switching

operations

• Fully automate network management with closed

loop control functionality

The ADMS model delivers the information needed

across the utility enterprise for:

• Monitoring, analysis and control of network

operations

• Managing load and adjusting the shape of the

demand curve

• Planning analysis: online to evaluate ‘what if’

scenarios and offline to assess historical activity and

plan for future network enhancements

• Preparing for effective and secure deployment of

DER, including storage and microgrids

An ADMS solution can deliver a host of analytical

functions – some of which are identified below – that

will optimize grid efficiency and enable effective and

efficient integration of DERs.

Network operation control – including Fault

Location, Isolation and Service Restoration (FLISR)

with optional closed loop control (automated)

switching, as well as large area restoration and load

shedding to help sustain system stability during

extreme peak periods.

Figure 5. ADMS model provides network visualization via geographic, schematic and station one-line views.


White paper | 10

Network operation optimization – including

Volt/VAR Control to manage load tap changers,

capacitors, and voltage regulators with optional

closed loop control in a self-healing manner. An

ADMS also enables monitoring of renewable energy

through detailed load profiling and, with integrated,

real-time weather data, supports improved near-term

and short-term load forecasting. It also supports

thermal energy storage and evolving battery

technology.

Network operation analysis – including energy

losses, both technical and commercial; relay

protection through settings and device coordination;

reporting of harmonic distortion; and contingency

and security assessment to identify re-supply options

following faults.

Network planning – including simulation that

supports development; minimizing loss and detecting

overload for network reinforcement; medium-term

and long-term load forecasting; and load growth

analysis.

Cutting-edge projects are putting demand management to work

Automate peak load shaving. Using ADMS Volt/VAR Control functionality, one utility is reducing feeder voltage automatically, with no effect on the consumer, and deferring, or eliminating, the need to build large-scale generation. The ADMS model is helping the utility plan for ‘green’ MWs. According to a utility spokesperson, “We see this project as something that could change the power industry.”

Maximize Distributed Generation. This utility serves a large, primarily rural territory and looks to support feed-in tariff regulations and distributed renewable energy. It is deploying ADMS modeling functionality to monitor the high growth of DG and proactively plan for effective dispatch and control of DGs. The utility is doing this in a way that also provides economic benefits, by leveraging network load forecasting based on meter load profiles and integrated weather data.

Optimize network efficiency and reliability. The most common benefit utilities realize with ADMS deployment is enabling efficient and reliable network operations in the face of ever-growing constraints. A utility is deploying ADMS to manage its distribution network in a real-time manner to minimize losses and maximize reliability and safety. ADMS provides three operational approaches this utility can use for device management: availability of advanced tools and visual context; recommendation of the most optimal device operations; and automation of device operations.

Conclusion

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Security is of utmost importance when deploying ADMS in a mission-critical

environment. From a standards perspective, much work remains to be done to

address Smart Grid cyber security. There is significant benefit in developing ADMS

technology that addresses the evolving NERC CIP and NISTIR requirements.

One of the best ways to address security concerns is deploying a single solution

that integrates ADMS with SCADA technology with a proven, high-level of security,

reliability and performance. Of course, the SCADA incorporated in this solution

must:

• Be able to support tens of thousands of intelligent field devices

• Have a robust reporting engine to deliver real-time data for critical business and

operational analysis and decisions

• Support a ‘self-healing’ network architecture

• Perform system-wide health monitoring

• Be designed for standards compliance that will support long-term deployment

A comprehensive ADMS solution applies this combined-technology approach. It

creates a single infrastructure and user interface for enterprise consistency and

efficiency. With its comprehensive set of tools, utilities can perform monitoring,

analysis, control, dispatch, planning and training for their distribution networks,

using real-time, planning, or study modes.

The most-advanced technology supports both three-phase balanced and

unbalanced state estimation. With it, the utility can take advantage of advanced

load management (DSDR), closed-loop control for self-healing automation, and

distributed energy resource modeling that supports economic decisions and

reliability management.

OASyS DNA security

Telvent collaborates with Idaho National Laboratories (INL), the host of the United States Department of Energy’s National SCADA test bed, in joint cyber security testing of Telvent Energy’s OASyS DNA SCADA infrastructure and in developing and documenting best practices.

Schneider Electric USA, Inc.

4701 Royal Vista CircleFort Collins, CO 80528Phone: 1-866-537-1091 + (34) 9-17-14-70-02Fax: 1-970-223-5577www.schneider-electric.com/us

June 2012

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Preparing for Distributed Energy · PDF fileManagement System (ADMS) that enables ... ADMS optimizes DER management; grid operations and planning ... Preparing for Distributed Energy