Advanced Distribution

Management System

Integration of Renewables

and Storage Analyse, control, and optimise renewables and energy

storage systems within the distribution network

John Dirkman, PE

Sr. Product Manager, Schneider Electric

john.dirkman@schneider-electric.com

http://www.linkedin.com/in/dirkman

23 October 2013

Key Learning Objectives

●Learn how renewables and distributed energy resources can impact an

electric distribution system

●Discover ways to manage and optimise renewables and distributed

energy resources using ADMS

●Maximize benefits from renewables by leveraging integration of an

accurate weather forecasting system with ADMS

●Learn how microgrids, with distributed energy resource and demand

response components, are managed and optimized by ADMS

A global company

$31 billion sales in 2012

41% of sales in new economies

140,000+ people in 100+ countries

committed to innovation

4-5% of sales devoted to R&D

~$1.5 billion devoted to R&D

Residential 9%

Utilities & Infrastructure 25%

Industrial & machines 22%

Data Centers 15%

Non-residential buildings 29%

Delivering Solutions for End Users

the global specialist

in energy management

Some of the world class brands that we have built or acquired in our 175 year history

EPS,

Serbia

ACTEW, Canberra

Australia

Energoprom, Novocheboksary

Russia

ENEL,

Italy

Light Services de Electricitade,

Rio de Janeiro, Brazil

Abu Dhabi,

UAE Tunisia PT-PLN, Banda Aceh,

Indonesia

ANDE, Asuncion,

Paraguay

Murcia, Spain

EDENOR, Buenos Aires,

Argentina

NIH, Washington DC, USA

EDELNOR,

Lima, Peru

CNFL, San Jose,

Costa Rica

Petroproduccion,

Ecuador

EMCALI, Cali,

Columbia

ELECTRA, Panama City,

Panama

Duke/Progress Enrgy,

North Carolina

UofM, Michigan

EMASZ / ELMU, Budapest,

Hungary Guizhou Electric

Corporation, China

IDGC Center Russia, Moscow,

Russia

Maharashtra,

India

Electrica, Cluj,

Romania

Elektro Celje,

Slovenia

Hydro One,

ON, Canada

Railway project,

STEG,

EVN,

Macedonia

PECO,

Philadelphia

EDEN, Buenos Aires province,

Argentina

PT-PLN, Bandung,

Indonesia

Austin Energy,

Texas

EPS

Serbia

EPRS

B&H

EPCG

Montenegro

CFE, Zona Puebla City,

Mexico

Burbank W&P,

California

BC Hydro,

BC, Canada

Medina,

Saudi Arabia

Irkutsk,

Russia

Dong Energy,

Denmark

ETSA, Adelaide

Australia

Unison,

New Zealand

Guangxi Power,

China

Bihar,

India

MEER,

Ecuador

NS Power,

NS, Canada

EPCOR,

AB, Canada

ADMS/PCS Projects Worldwide

Over 180 control centers and 88M meters

Utility Transformation

How do you expect utility business models to be in 2030 compared to

today in your market?

Utility Transformation

Which energy market transformation vision most closely matches your

expectations of your market?

Definitions

●Distributed Generation (DG)

● Dispersed generation, typically less than 10 MW, in the distribution network

● Controllable DG: Combined Heat and Power, Generators, ~Hydro

● Non-controllable DG: Wind and Solar

●Energy Storage Systems (ES)

● Battery Banks, Compressed Air Systems, Thermal Storage Systems

●Distributed Energy Resources (DERs)

● Combination of DG and ES, located throughout the distribution network

Power Resource Type* Controllable?

Generators Supply Yes

Wind Supply No

Solar Supply No

Interties Supply/Demand Yes

Battery Banks Supply/Demand Yes

Electric Vehicles Supply/Demand Yes

Compressed Air Systems Supply/Demand Yes

Thermal Storage Systems Demand Yes

Demand Response Demand Yes

* Supply-side provides power, Demand-side consumes power or affects consumption

Poll Question 1 – Preparedness

●How prepared is your utility for integration and optimization of

renewables and storage?

●Please select one:

1. Just getting started [38%]

2. Somewhat prepared [15%]

3. Fairly well prepared [15%]

4. Completely prepared but not yet fully integrated and optimized [1%]

5. We are already integrating and optimizing renewables and storage [7%]

6. Unknown [24%]

Energy Storage in the Network

●Storage provides benefits in the distribution network:

● Storing of active power

● Flattening of load profile: smaller nighttime valley and reduced daytime peak

● Storage can be considered as source of active power during peak hours

(energy storage as peak generation unit)

● In combination with intermittent operation of renewables (e.g. solar), ES can

provide continual power supply even during night hours

● Combination of renewables + ES can reduce fluctuation of power injection

caused from variation of solar/wind input. Stored energy can mitigate

sudden injections or drops of power from renewables.

Impact on Profile ● Impact on profile (left lower corner, gray area is stored energy, while

gray area in peak hours denote discharged energy):

Definitions Continued

●Demand Response (DR)

● Management of consumption, anywhere along a feeder, in response to

supply conditions

●Network Reconfiguration

●Voltage Reduction

●Volt/VAR Optimization

●DG/ES/DER Management

●Load Shedding/Curtailment

●Microgrid

● A local network of DERs and consumers that is a subset of the distribution

network

● Can operate in an isolated manner or be always connected

● May include multiple DR components

● Microgrid management targets local energy supply and demand

The Advanced DMS

Convergence of DMS, OMS, and

SCADA

Monitoring, analysis, control,

optimization, planning, and

training

Management of Demand and Distributed

Energy Resources

Network automation with

closed-loop control

Incident, fault, and crew

management with field mobility

Common User Experience, Data Model, Integration, Secure Infrastructure

ADMS Functionality

Train

Plan

Optimize

Operate

Analyze

Monitor

Load Flow

State Estimation

Energy Losses

Fault Calculation

Reliability Analysis

Relay Protection

Device Capability

Contingency Analysis

Fault Management

Switch Management

Crew Management

Under-load Switching

Large Area Restoration

Load Shedding

Telemetry

Alarming

Tagging

Trending

Reporting

Volt/VAR Optimization

Network Reconfiguration

Near and Short-term Load

Forecasting

Demand Response

Distributed Energy Mgmt.

Medium and Long-term

Load Forecasting

Network Automation

Network Reinforcement

Optimal Device Placement

Real-time Simulation

Off-line Simulation

What-if Analysis

Historical Playback

ADMS Benefits

Safety

Reliability

Efficiency

Standardized Training

Unified Interface

Detailed Equipment Usage History

EPS,

Serbia

ACTEW, Canberra

Australia

Energoprom, Novocheboksary

Russia

ENEL,

Italy

Light Services de Electricitade,

Rio de Janeiro, Brazil

Abu Dhabi,

UAE Tunisia PT-PLN, Banda Aceh,

Indonesia

ANDE, Asuncion,

Paraguay

Murcia, Spain

EDENOR, Buenos Aires,

Argentina

NIH, Washington DC, USA

EDELNOR,

Lima, Peru

CNFL, San Jose,

Costa Rica

Petroproduccion,

Ecuador

EMCALI, Cali,

Columbia

ELECTRA, Panama City,

Panama

Duke/Progress Enrgy,

North Carolina

UofM, Michigan

EMASZ / ELMU, Budapest,

Hungary Guizhou Electric

Corporation, China

IDGC Center Russia, Moscow,

Russia

Maharashtra,

India

Electrica, Cluj,

Romania

Elektro Celje,

Slovenia

Hydro One,

ON, Canada

Railway project,

STEG,

EVN,

Macedonia

PECO,

Philadelphia

EDEN, Buenos Aires province,

Argentina

PT-PLN, Bandung,

Indonesia

Austin Energy,

Texas

EPS

Serbia

EPRS

B&H

EPCG

Montenegro

CFE, Zona Puebla City,

Mexico

Burbank W&P,

California

BC Hydro,

BC, Canada

Medina,

Saudi Arabia

Irkutsk,

Russia

Dong Energy,

Denmark

ETSA, Adelaide

Australia

Unison,

New Zealand

Guangxi Power,

China

Bihar,

India

MEER,

Ecuador

NS Power,

NS, Canada

EPCOR,

AB, Canada

ADMS/PCS Projects Worldwide

Over 180 control centers and 88M meters

Renewable Resource Commitment

● In June 2007, the Burbank City

Council adopted BWP's

recommendation that 33% of

electricity be procured from

renewable resources by 2020

●Burbank was the first city in the

United States to step up to this

ambitious goal

●Burbank now seeks to obtain

66% of electricity from

renewable resources by 2025

●Renewables will be a

combination of primarily wind,

solar, and compressed air

storage systems

Renewable Resource Variability

185 MW

20 MW

170 MW

10 MW

Integrated ADS Business Objectives

● Integrate Demand and Supply resources into the realtime and

day-ahead operations at Burbank Water and Power

●Automate and Optimize dispatch of resources:

● Generation

● Renewable energy resources

(solar and wind)

● Energy purchases and sales

● Demand response and load

control (ADR)

● Energy storage and EV

● Distributed generation and PV

● Centralized Control Center

Integrated Automatic Dispatch System

(iADS)

18

PCS/SCADA

(LF, RF, AGC)

(Schneider Elec)

GIS/OMS

(Schneider Elec) ADS/AGC

(OATI)

Wholesale &

Market

Operations

(OATI)

AMI (Trilliant)

MDMS (eMeter)

CIS

(Oracle CC&B)

Balancing Authority Trading Partners

Wholesale Markets

Fiber/wireless networks/Internet

Customer

Portal

Distributed

Generation Energy

Storage

Demand

Response

Ice Bear

TES units

Building

Mgmt

System

Weather Service

(Schneider Elec)

Poll Question 2 – Main Drivers

●At your utility, what are the main drivers for integration and

optimization of renewables and storage?

●Please select all applicable replies:

1. Required for reliability (create alternative sources of distributed energy

in the event of outages) [8%]

2. Required for reliability (reduce load on sections of feeders) [15%]

3. Required for efficiency (e.g. peak shifting, peak shaving, balance

supply and demand) [18%]

4. Required for environmental reasons (cleaner energy) [20%]

5. Required due to regulatory/governmental requirements [25%]

6. Other (please email John with your drivers) [1%]

7. Unknown [13%]

The DG/DER Challenge

● Integration of renewables and storage is a challenge for networks

designed to operate in the “classical” way

(one way: transmission –> distribution -> consumer)

●Renewables in the distribution system completely change the

philosophy of network operation:

● reverse power flow

● impact on voltage profile

● protection schemes

●Distribution network starts to look more like the transmission network

Problems Created By DG and DER in

the Network ●Without ADMS, DG/DER’s in the network introduce several dilemmas

for engineering and operations:

● No visibility of network state with DG/DER’s

● Not clear if operating problems like high/low voltages are caused by

DG/DER’s or normal loading conditions

● Not clear how to select the optimal location for connecting large DG/DER

resources to the network

● No clear direction on how to maximize the operation and value of “green”

energy provided by renewables

●Result is operating problems such as high/low feeder voltage and

reverse power flows may go unseen until customers are affected

Current Situation

Smart Field

Devices

???

Buildings

Houses + Electrical Vehicles

Weather

Stations

Wind

Generation

Smart

Devices

Solar

Panels Distribution utilities face new challenges

CHP Plants

DG/DER Visualization and Monitoring

●Visualization

● Geographic, schematic, substation views

● Filtering by and search by resource type, voltage level, size, affiliation, etc.

●Monitoring

● Real-time awareness of DG/DER activity

● Visualization and reports for active/reactive (over/under) generation

● Condition-based monitoring for maintenance

DG/DER Analysis and Forecasting

●Over generation

● Violation of upper limits for active/reactive power generation

● Predictive alarming, phase balancing

●Harmonic penetration

● Harmonic analysis in presence of DG/DERs

● DG/DER contribution to harmonic levels

●History of operations

● Historical trending and reporting

● Identify periods of operational violations

●Near-term and short-term forecasting

● Load and solar/wind generation forecasting

● Historical behavior with current and forecasted weather (wind

speed, solar irradiance, temperature, humidity)

Load Forecasting 90% of demand variation

due to weather

Wind Power Highly variable, difficult to predict.

Causes increases in spinning reserve

generation and risk of grid instability

● Weather imposes the largest external impact on your Smart Grid

● Demand, renewable energy supply, and outages are heavily influenced by weather

● Intelligent weather integration is the key factor in efficient Smart Grid management

Transmission Temperature,

humidity and wind

impact line capacity

Distribution Weather is largest cause of

outages (lightning, high winds,

ice, transformer failures due to

high load, etc.)

Distributed Generation Home solar contributions can cause

system instability due to rapid cloud

cover changes

Trading Improved prediction of load

and renewable energy

contribution improves trading

decisions

WeatherSentry

WindPower Forecasts Solar Power Forecasts

Schneider Electric – Dominant Weather

Provider to the Energy Industry in North

America

● #1 for transmission and distribution

crew management

● Weather integrated into OMS & DMS

SmartGrid systems

● Renewable energy services:

● 73% of US wind farms use Schneider

Electric lightning safety alerting

● Advanced wind power and solar

forecasting

● 70% of generation in U.S.

electric industry uses

Schneider Electric weather

forecasts for load modeling

● Largest energy weather provider

in U.S.

● A $30 billion global energy leader

● Rapid growth internationally

● Schneider Electric is an ADMS

leader

Forecasting Accuracy Results

Typical results for a single wind plant

Forecast Horizon MAPE* of Rated

Capacity

Hour-ahead to next 12 hours 6-12%

Day-ahead (hour 30) 12-18%

Days 3-7 18-20%

What accuracy are you

currently receiving?

MAPE = Mean Absolute Percentage Error

Improved Accuracy Gives Large ROI

A Customer Perspective of Wind Power Forecast Value

● Day Ahead Forecasting Error Theory when using WindLogics forecasts

● Ideal Revenue = “generate exactly to the forecast”

● Deviation to Ideal = “Forecast Error”

● Forecast Error is comprised of

• Availability error

• Curtailments

• Wind forecast error: Timing & magnitude

● Customer view:

• Assuming 15% MAPE, each 1% equates to $65K, or nearly

$1M annually (400MW wind portfolio)

● Ongoing WindLogics forecast training yields between 3-5%

improvement in accuracy, or $195K-$325K annually

1/3 of Forecast Error

Forecasting of Ramp Events

● Uses an ensemble approach to ramp probability

● The WindLogics forecasting system outputs predictive intervals

(P20/P50/P80), which provide a valuable assessment of the

possible impact of a ramp event (timing & magnitude)

Ramp events

were well-

forecasted

days in

advance

P20 Forecast Power

Actual Power

P50 Forecast Power

P80 Forecast Power

DTN Solar Forecasting Experience

Utility-scale solar irradiance forecasting

● PV (Photovoltaic) and

● CSP (Concentrated Solar Power),

including Abengoa Solar

Distributed solar projects,

for utilities

Providing solar irradiance

forecasts to many utilities

for load forecasting

Schneider Electric’s Solar Capabilities

●Schneider Electric provides a leading inverter solution, and is a solar

integrator

●Schneider Electric has SCADA systems for solar plants (monitoring &

control), used by Abengoa Solar and others

●Schneider Electric’s ADMS (Advanced Distribution Management

System) manages distributed solar generation challenges for utilities

●Schneider Electric is participating in a major US Department of Energy

3-year research project with the US National Center for Atmospheric

Research (NCAR) to improve solar forecasting, as part of the US

Department of Energy’s “SunShot” Initiative)

Benefits of Solar Forecasting System

●Integrate solar successfully

●Schedule power and maintain system reliability

●Utilize more of the generated solar power

●Minimize reserve costs

●Reliably make unit commitments, reduce risk

●Improve power marketing

DTN Solar Benefits

●Provides outstanding irradiance accuracy

●Reliable delivery

●Energy weather experts, with the resources of

Schneider Electric, committed to solar energy

●Also, we will be introducing solar power forecasting in

Q4 2013

● Irradiance forecasting now

●Adding generated power forecasting

ADMS Operation & Optimization of DER

●Dispatch (reliability, economic)

● Dispatch entire network or localized areas

● Increase or decrease generation (automatically/manually)

●Operation Validation

● What-if analysis in simulation mode

● Prevent operation on adjacent feeders

●Volt/VAR Optimization

● Manage VVO in the presence of DG/DERs

● Utilize DG/DERs as VVO resource

●Relay Protection Coordination

● Adaptive relay protection and transfer trip settings

●Microgrid Islanding

● Maintaining reliable service with islanded networks

Steps to Solving the DG/DER Problems

1. Provide full visibility of network state with DG/DER; to increase

network awareness

2. Evaluate the impacts of new DG/DER;

● What will happen if we add a new unit,

● Simulate and study impacts before unit goes on line (planning)

3. Optimize DG/DER operation (including microgrids)

1. Full visibility of network state

●A comprehensive task which requires modeling of DG/DER with

appropriate models:

● Load flow model

● Short circuit model

● Models which can be used for forecasting purposes

●ADMS software package provides modeling

● For real-time visualization and operations

● For off-line simulation and study

●Following are some illustrations of the main effects of DG/DER in the

distribution network

Full Network State Visibility

Voltage Profiles – no DG (open)

Voltage Profiles – with DG (closed)

Short Circuit Current

Near Term Operation Planning

supported by Weather Forecast Inputs

2. DG/DER Planning

●What will happen if we add a new unit

●Run analysis before adding unit in the network

● One possibility is to add DG/DER in the selected network configuration and

state (e.g. the worst case)

● Better possibility is to check several typical cases, e.g.:

● Maximum DG production/minimum Load (voltage problems?)

● Minimum DG production/maximum Load (overloading?)

● Etc.

Overload problem

S4.2 Load Management + Reconfiguration

S4.4 Energy Storage

No problem

Load

DG

S1.0 - DGmaxLoadmax

No problem

S3.0 - DGmaxLoadmin

S4.0 - DGminLoadmax

S2.0 - DGminLoadmin

S3.1 Volt/VAR Optimization (VVO)

Voltage problem

S4.3 Demand Response

S4.1 Cable Reinforcement S0.0 S0.1

Planning Variants

DG Influence on Network Design State with DGmax, Lmin – Voltage Problem

State with DGmax, Lmin – VVO Solution

DG Influence on Network Design

DG Influence on Network Design State with DGmin, Lmax – Overload Problem

DG Influence on Network Design State with DGmin, Lmax – NR Solution

DG Influence on Network Design State with DGmin, Lmax – Energy Storage Solution

3. Microgrid Optimization

WIND UNITS

CONVENTIONAL

GENERATION

(Hydro, gas, CHP)

MV BUSBAR

HV BUSBAR

LOAD CONSUMPTION STORAGE UNITS

SUPPLY TRANSFORMER

OR

TIE LINE

Weather

Information + Forecast

SOLAR UNITS

Microgrid Management with ADMS

● Provide monitoring of microgrid level resources

● Identify capabilities of generators; especially renewables

● Determine historical behavior of renewables (vs. weather input)

● Provide monitoring of interchange through supply transformer or tie line

● Provide forecast of load and renewable production (weather monitoring

plus weather forecast)

● Calculate costs/benefits of microgrid operation, including forecasting

● Optimize operation of utility resources (“regional islanding”)

MV BUSBAR

WIND UNITS

CONVENTIONAL

GENERATION

(Hydro, gas, CHP)

LOAD CONSUMPTION STORAGE UNITS SOLAR UNITS

Island Operation?

●Real islanding (no connection with main grid) is typically forbidden

●Possible, but not primary goal

● Islanding requires much more investment and tuning

● Load shedding to balance island production and consumption at the

moment of islanding

● Is stable frequency required? If yes, effective and efficient under frequency

protection is required to align imbalance at any moment

● Regulating unit capable of keeping stable frequency

● e.g. CHP of 10 MW has ramp up about 50 kW/sec; economic threshold

for e.g. CHP is above 4000h/year

● hydro unit can have even greater ramp up, but ramp down can be a

problem

Application Support for Microgrids

●Applications:

● Automatic Generation Control – AGC

● Economic Dispatching – ED

● Unit Commitment – UC

● Load Forecasts – LF

● Renewable Production Forecast – RPF

● Load Shedding – LS

● Interchange Transaction Scheduler – ITS

●Additionally, ADMS applications can be

added for monitoring/control when the full

network model is used

●Product Focus

● ADMS for Distribution

● EMS for Transmission

● PCS for Generation

● Convergence of Systems

Managing and Optimizing DG with ADMS

●Complete, real-time and off-line model of the distribution grid

● Insight into grid state in the presence of DGs and DERs

● Conditions during reverse power flow

● Support operations and planning

●Capacity planning

● Load growth

● New DG/DER connections (what-if analysis)

●Load and power forecasting

● Near-term (hours) and short-term (days) forecasting

●DER operations and optimization

● Network simulations

● Relay protection coordination

● DER to shape the daily load curve

●Advanced DMS operations

● Volt/VAR Optimization

● Fault Location, Isolation, Supply Restoration

ADMS provides insight

into all areas of grid

operations

Summary

●Schneider Electric has a long history of applying technology

to solve complex problems for utilities

●Advanced systems like those provided by Schneider Electric

can balance and optimize supply and demand and provide

reliable, safe, and affordable power in the presence of highly

variable renewable resources

●Integrations between applications are an integral part of

these advanced systems

●Sophisticated Load Forecast and Renewable Forecast

algorithms based on input from Weather Systems are a

critical component of renewable optimization

Thank You!

John Dirkman, PE

Sr. Product Manager

Schneider Electric

john.dirkman@schneider-electric.com

http://www.linkedin.com/in/dirkman

23 October 2013