1

Grid Integration of Distributed Generation and StorageGeneration and Storage

Tom Key Technical Executive EPRITom Key, Technical Executive EPRI tkey@epri.com

Tuesday, July 29, 2014 National Harbor MDNational Harbor, MD 

The Electric Power System y

Variable solar and wind generationVariable solar and wind generation

A US Future ofA US Future of Generation in Germany Generation in Germany A US Future of A US Future of 302 GW PV 302 GW PV by 2030?by 2030?

Week Week -- April 14April 14--20, 201420, 2014

60 GWGW

DOE “SunShot” Vision St d R l d F b

Mo Tu We Th Fr Sa Su

Study, Released February 2012

Is the grid ready?Is the grid ready?

Steps for Integrating DG?Steps for Integrating DG?

Understanding Determine F d DeployDevelopg

PV Plant Performance 

Feeder Hosting 

Capabilities

Deploy Inverter‐Grid Support

pFast ‐Track  Screening 

Current Research Activities

EPRI SolarTAC Testing 1.2

1.4Normalized I‐V Curves

EPRI SolarTAC Testing

0 2

0.4

0.6

0.8

1.0

Curren

t (A)

1

0.0

0.2

0 20 40 60 80 100Voltage (V)0.5

rmal

ized

Out

put

60 1.1Seasonal Performance Factors for SolarTAC

Weighted Average Module Temperature (°C) for Suntech

SuntechTrina

(Dec 09, 2013)... 12:00 15:000

No

Local Time

Poly1 Poly2 Mono CdTe CIGS1 CIGS2 HIT

30

40

50

erat

ure

(°C)

0.9

1

man

ce F

acto

r

Weighted Average Module Temperature ( C) for SuntechTrinaHeliosFirst SolarSolar FrontierStionPanasonic

0

10

20 Tem

pe

Q1(Jan-Mar) 2013 Q2(Apr-Jun) 2013 Q3(Jul-Sep) 2013 Q4(Oct-Dec) 2013

0.6

0.7

0.8

Perfo

rm

Season

Seasonal PV Daily Output Profile Shows max, min, median, and middle 50% range for a Georgia Site

0 68 0 18

0.4

0.6

0.8

1 Winter (Jan-Mar)

0.4

0.6

0.8

1 Spring (Apr-Jun)0.68 span

0.18 span

10 15 200

0.2

10 15 200

0.2

NormalizedPower

0 4

0.6

0.8

1 Summer (Jul-Sep)

0 4

0.6

0.8

1 Fall (Oct-Dec)Power

0.3 span

0.58 span

10 15 200

0.2

0.4

10 15 200

0.2

0.4

Hour of DayHour of Day

Solar Resource Calendar – 1MWAC Output PowerSolar Resource Calendar  1MWAC Output Power

1 2 3Thu Fri SatSun Mon Tue Wed

December 2011: Tennessee 1MW PV System Power

1 2 3

4 5 6 7 8 9 10

11 12 13 14 15 16 17

18 19 20 21 22 23 24

25 26 27 28 29 30 31

Calendar profiles are 1‐minute averages derived from 1‐sec data

Categories for Daily Variability ConditionsSandia’s variability index (VI) and clearness index (CI) to classify daysSandia s variability index (VI) and clearness index (CI) to classify days

Clear Sky POA IrradianceMeasured POA Irradiance

VI > 10

HighHighHighHigh

ModerateModerateClearClear

VI < 2CI ≥ 0.5

5 ≤ VI < 10

VI < 2 2 ≤ VI < 5MildMildOvercastOvercastVI < 2CI ≤ 0.5

2 ≤ VI < 5

Geographical and Seasonal PV Variability Variability Conditions: NM

Variability Conditions: NJ

60

80

100

f Day

s (%

)

80

100

Day

s (%

)

Q2 2012 Q3 2012 Q4 2012 Q1 20130

20

40

60

Perc

enta

ge o

f

Season

Q2 2012 Q3 2012 Q4 2012 Q1 20130

20

40

60

Perc

enta

ge o

f D

Season

Variability Conditions: AZ

Variability Conditions: TN

80

100s

(%)

20

40

60

80

100

Perc

enta

ge o

f Day

s (%

)

Q2 2012 Q3 2012 Q4 2012 Q1 20130

20

40

60

80Pe

rcen

tage

of D

ays

Season

Q2 2012 Q3 2012 Q4 2012 Q1 20130

P

Season

Season

EPRI High‐resolution PV MonitoringConcentrated areas include Southeast, Atlantic Coast, and California

Clusters PVPlants

Planned

InstalledRecent Install

Main map: © 2012 Microsoft Corporation. Imagery © Microsoft – available exclusively by DigitalGlobe (Bing Maps Terms of Use: http://go.microsoft.com/?linkid=9710837). Inset map: Map data © 2012 Google

SiteLocations,September2013

Example of Variability on a Feeder in Rome, GAExample of Variability on a Feeder in Rome, GA= DPV Site= DPV Site

SubstationSubstation

1 km2 grid

© Google – Map data © Google0.0 mi.0.0 mi. 0.5 mi.0.5 mi. 1.0 mi.1.0 mi.

Monitoring PV Output Variability g p yFeederss

Monitoring solar variability and power quality events throughout the feeder

1 2 3

8 9 10

Thu Fri Sat

6

8

10

12

400

500

600

700

800

900

ility Inde

x (Avg by Wee

k)

or To

tal Tap

 Cou

nts b

y Wee

k

Reg Tap Counts (total by week)

Average Variability  Index (by week)

-100

0

100

200

300

400

500

ve P

ower

(kVA

R)

8 9 10

0

2

4

0

100

200

300

Apr '12 May '12 Jun '12 Jul '12 Aug '12 Sep '12 Oct '12 Nov '12 Dec '12 Jan '13 Feb '13

Variabi

Regulato

01/13/2013 01/14 01/15 01/16 01/17 01/18 01/19-500

-400

-300

-200

-100

Rea

ctiv

Using the high resolution data for modeling analysisUsing the high resolution data for modeling analysis

Applying Measured PV Data to Feeder ModelApplying Measured PV Data to Feeder Model 

Solar Data• Collect high‐res 1 sec solar data to use in model simulations

F d M d li

Birmingham, AL (May 14, 2010)

200

400

600

800

1000

Pow

er P

rodu

ctio

n (W

)

Birmingham, AL (May 14, 2010)

200

400

600

800

1000

Pow

er P

rodu

ctio

n (W

)

Feeder Modeling• Develop feeder 

d l ith i t

0

200

8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pmLocal Time (h)

0

200

8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pmLocal Time (h)

8976897789768977

models with input from utilities

Analysis ApproachAnalysis ApproachUniqueness from other research efforts

– Large sample of feeders/characteristics considered1000’ f t ti l d l t ( i /l ti ) l d– 1000’s of potential deployments (size/location) analyzed

– Range in hosting capacity reported for each issueMinimum Hosting Capacity

Maximum Hosting CapacityDetails on analysis method:

1.065

1.07A B C

h

A – All penetrations in this region are

acceptable, regardless

Stochastic Analysis to Determine Feeder Hosting Capacity for Distributed Solar PV.EPRI, Palo Alto, CA: 2012. 1026640.

1.05

1.055

1.06

e R

esul

t for

Eac

V D

eplo

ymen

t of location

B – Some penetrations in this region are

acceptable, site specific

1.035

1.04

1.045

Wor

st-C

ase

Uni

que

PV

Threshold of violationC – No penetrations in

this region are acceptable, regardless

of location

0 0.5 1 1.5 2

Increasing penetration (MW)

Sample Analysis – Spatial &Time Based3D Visualization of PV Measurement Feeder Voltage Profile

PV Production Time Series Regulator/Capacitor Operations

Smart Inverter is a Key Integration TechnologySmart Inverter is a Key Integration TechnologyDC Power AC Power

Traditional Inverter FunctionalitySmart Inverter FunctionalitySmart Inverter Functionality

• Matching PV output with grid voltage and frequency

• Providing safety by providing unintentional islanding

• Voltage Support• Frequency Support

F lt Rid Th h (FRT)unintentional islanding protection

• Disconnect from grid based on over/under voltage/frequency

• Fault Ride Through (FRT)• Communication with grid

over/under voltage/frequency

What is a Smart‐Grid Ready Inverter?What is a Smart Grid Ready Inverter?Link to distributed PV and Storage Systems that becomeStorage Systems that become BeneficialBeneficial distribution system assets

Improving Efficiency

I i

Reliability

Enabling Higher

Penetration of Improving Power Quality

Asset Life

Deferred Costs

Penetration of Renewables

Hosting Capacity with Inverter Support FunctionPV at Unity Power Factor PV with Volt/var Control

Minimum Hosting CapacityMaximum Hosting Capacity

Minimum Hosting CapacityMax Hosting Capacity

ANSI voltage limit

olta

ge (p

u)

tage

s (p

u)

ANSI voltage limit

um F

eede

r Vo

m F

eede

r Vol

t

2500 cases shownEach point = highest primary voltage M

axim

u

Max

imum

( ) Increasing penetration (kW)Increasing penetration (kW)

No observable violations regardless of PV size/location

Possible violations based upon PV size/locationPossible violations based upon PV size/location

Observable violations occur regardless of size/location

Hosting Impact of Smart Inverter Functions 19

and Set Points

Power

Active Power

95%pf

Volt‐Watt 1

Volt‐Watt 2Reactive P

Volt‐Var 1

Volt‐Var 2

98% pf

95% pf

ailable Vars

% voltage

100%

0.951.0V

0 2000 4000 6000 8000 10000

Baseline

Increasing PV Penetration ‐‐‐> 

% Av 1.05

‐100%

All penetrations in this region are acceptable,

Some penetrations in this region are

No penetrations in this region are acceptable, %

 Available Vars

% voltage

Unity Power Factor

regardless of locationg

acceptable, site specificg p

regardless of location

Understanding Potential Benefits of StorageUnderstanding Potential Benefits of Storage

Power SupplyEnergy and load Power Delivery End Use

• Energy and load shifting

• Regulating services

y• Asset utilization• Investment deferral• Power quality and

• Photovoltaic Energy Shifting

• Demand Peak• Contingency

reserve

• Power quality and reliability

• Demand Peak Reduction

The Energy Storage Value ConceptThe Energy Storage Value ConceptPhotovoltaicPeak Shift Customer Side

For Illustration Only

P El t i

Balance of Plant

Regulation Services

Demand Peak Reduction

Peak Shift Customer SideApplications

Power Electronics

P Q lit d

Regulation Services

Voltage Support

Inertia Support

MarketApplications

Power Electronics

Balance of Plant

Battery Cost

T&D Upgrade Deferral

Power Quality and Reliability Rate Based

ApplicationsBattery Cost

Power Electronics

Costs of Storage

Benefits of Storage

The Value of Storage RealitiesThe Value of Storage RealitiesFor Illustration Only

P El t i

Balance of Plant

Demand Peak Reduction

PhotovoltaicPeak Shift Customer Side

ApplicationsBalance of PlantPower Electronics

Regulation ServicesVoltage SupportInertia Support

MarketApplications

Reduction

Power Electronics

Balance of Plant

Battery Cost

T&D Upgrade Deferral

Power Quality and Reliability Rate Based

ApplicationsBattery Cost

Costs of Storage

Benefits of Storage

Various Sources of FlexibilityVarious Sources of Flexibility

• Conventional Resources– Peaking and cycling units

• Emerging Resources– Demand response Conventional Genp– Energy storage– Plug‐in electric vehicles

• VG Power Managementg– Control VG output

• Institution/Market Flexibility– Coordination among Balancing 

Emerging Resources

g gAuthorities (BAs)

– Shorter scheduling

• More TransmissionVG P M tVG Power Management

Smart Grid Ready Inverter: Objectives1. Make Inverter Ready and Demo in Field

– Develop, test, field demo at utility sites

Smart Grid Ready Inverter: Objectives

*p, , y– Define and incorporate standard grid 

support functions (500 kVA level)*– Use feeder/PV modeling for scale up

2. Revisit Feeder Level Anti‐Islanding Identify utility‐controlled trip options

– Conduct laboratory side‐by‐side tests

3. Model DMS‐DERMS Level Integration– Characterize and model support functions– Evaluate voltage control strategies and 

coordination with traditional devices

DMS

coordination with traditional devices

Success depends on utility engagement and site learning

Who areHydro One

GRE

Who are Project 

DTE Energy National GridXcel Energy

KCP&LAEP Pepco

Partners?

SDG&EKCP&L

Southern Co.DOE ProjectEPRI Cost Share

Demonstration Sites

225kW(DC) PV1.7MW (DC) PV1.7MW (DC) PV300kVA300kVA Inverters

Ann Arbor, MI18 18 –– 95kW Inverters95kW InvertersCedarville, NJCedarville, NJ

1MW (DC) PV1MW (DC) PV2 2 –– 500kW Inverters500kW Inverters

Haverhill MAHaverhill MA

605kW (DC) PV605kW (DC) PV330kW & 250kW Inverters330kW & 250kW InvertersEverett MAEverett MA Haverhill, MAHaverhill, MAEverett, MAEverett, MA

1 Make Inverter Ready1. Make Inverter Ready 

Utility resource or

Markets-drive or

Utility resource or customer owned?

grid-code required?

What functions and how to initiate them?Standards

and testing?SettingsSettings

Performance and reliability?SettingsSettings

Benefits Demonstrated at Different SitesBenefits Demonstrated at Different Sites  

Benefits Derived from Functions

Testing at ESIF ‐ NREL’s Energy System Integration FacilityTesting at ESIF  NRELs Energy System Integration Facility

2. Revisit Anti‐Islanding2. Revisit Anti Islanding

Enabling Voltage Sag Ride-Through

Impacts on DER Hosting Capacity

U d t t d d

Need for feeder level anti-

Compare different methods in laboratory

Update standards for anti-islanding

islanding solutions

laboratory

Side by Side comparisons of different technologiesy p g

• Direct transfer trip (DTT) via di ll iradio, cell or wire

• Power line carrier communications (PLCC) low or high frequencyg q y

• Shorting switch• Integration of DG into the 

utility SCADA S h h b d• Synchrophasor‐based methods

• Research Prior Art• Develop Functional Requirements• Select Suitable Technology for EvaluationE l t T h l i i L b d Fi ld

• Research Prior Art• Develop Functional Requirements• Select Suitable Technology for EvaluationE l t T h l i i L b d Fi ld• Evaluate Technologies in Lab and Field• Evaluate Technologies in Lab and Field

Power‐Line Carrier Signal for DER – Concept

Substation Power Line Tone

DX3 Pulsar Transmitter

Generator Island Controller

Island

GridGrid

Island

X XX

XX

3. Model DMS‐Level Integration3. Model DMS Level Integration

Define functional requirements for DMS-DERMS

Address gaps in feeder operational

t l

New Types of DERManaging grid

t l t th d

control

New Types of DER autonomous or controllable

control at the edge of the grid Coordinating with

traditional voltage control devices

DER Enterprise Integration

GISMDMS OMS • DER representation

• Creation of groups and sharing of group

pin system model

Enterprise Integration

DMS DERMS

and sharing of group definitions

• Monitoring of group status

Enterprise Integration

DMS

Sensors Switches

DERMS status

• Dispatch of real and reactive power

Sensors, Switches, Capacitors, Regulators

SOLAR BATTERY PEV

• Forecasting of group capabilities

Project Resources36

Project Resourceshttps://solarhighpen.energy.gov/segis/electric‐power‐

h i iresearch‐institute

Public Reports: Integrating Smart Distributed Energy Resources with Distribution Management Systems, 1024360y

Collaborative Initiative to Advance Enterprise Integration of DER, 1026789

Common Functions for Smart Inverters Version 2 1026809Common Functions for Smart Inverters, Version 2, 1026809

Enterprise Integration Functions for Distributed Energy Resources: Phase 1, 3002001249

ConclusionsConclusions1. Smart inverter functions are defined and

i ll il blcommercially available.2. Demonstration in various system feeders,

d hi l ti d dand geographic locations needed.3. There are many lessons to learn and share.4. Challenges: settings, anti-islanding and

integration with utility DMS.

Thank you!Thank you! tkey@epri.comtkey@epri.comThank you! Thank you! tkey@epri.comtkey@epri.com