Grid Integration of Distributed

(1)

1

Grid

Integration

of

Distributed

Generation and Storage

Generation

and

Storage

Tom Key Technical Executive EPRI

Tom

Key,

Technical

Executive

EPRI

[email protected]

Tuesday,

July

29,

2014

National Harbor MD

National

Harbor,

MD

(2)

(3)

Variable solar and wind generation

Variable

solar

and

wind

generation

A US Future of

Generation in Germany

A US Future of

302 GW PV

by 2030?

Week

Week -- April 14

April 14--20, 2014

20, 2014

60 GW GW

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?

(4)

Steps for Integrating DG?

Steps

for

Integrating

DG?

Understanding

Determine

F d

Develop

Deploy

g

PV

Plant

Performance

Feeder

Hosting

Capabilities

Deploy

Inverter

‐

Grid

Support

p

Fast

‐

Track

Screening

(5)

EPRI SolarTAC Testing

1.2

1.4 Normalized I‐V Curves

EPRI

SolarTAC Testing

0 2 0.4 0.6 0.8 1.0 Curr en t (A) 1 0.0 0.2

0 20 40 60 80 100

Voltage (V)

0.5 rm aliz e d O u tp u t 60

1.1 Seasonal Performance Factors for SolarTAC

Weighted Average Module Temperature (°C) for Suntech Suntech

Trina

(Dec 09, 2013)... 12:00 15:00 0

No

Local Time

Poly1 Poly2 Mono CdTe CIGS1 CIGS2 HIT

30 40 50 e ra tu re ( °C ) 0.9 1 m an ce F act o r

Weighted Average Module Temperature ( C) for Suntech Trina Helios First Solar Solar Frontier Stion Panasonic 0 10 20 Te m p e

Q1(Jan-Mar) 2013 Q2(Apr-Jun) 2013 Q3(Jul-Sep) 2013 Q4(Oct-Dec) 2013 0.6 0.7 0.8 Pe rf o rm Season

(6)

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 20

0 0.2

10 15 20

0 0.2 Normalized Power 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 20

0 0.2 0.4

10 15 20

0 0.2 0.4

Hour of Day Hour of Day

(7)

Solar Resource Calendar – 1MW

_AC

Output Power

Solar

Resource

Calendar

1MW

_AC

Output

Power

1 2 3

Thu Fri Sat

Sun 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

(8)

for

Daily

Variability

Conditions

Sandia’s variability index (VI) and clearness index (CI) to classify days Sandia s variability index (VI) and clearness index (CI) to classify days

Clear Sky POA Irradiance Measured POA Irradiance

VI > 10

High High High High

Moderate Moderate Clear

Clear

VI < 2 CI ≥ 0.5

5 ≤ VI < 10

VI < 2 _Overcast_Overcast _Mild_Mild 2 ≤ VI < 5 VI < 2

CI ≤ 0.5

(9)

Geographical

and

Seasonal

PV

Variability

Variability Conditions: NM Variability Conditions: NJ

60 80 100 f Da y s ( % ) 80 100 D ays ( % )

Q2 2012 Q3 2012 Q4 2012 Q1 2013 0 20 40 60 P e rcen ta g e o f Season

Q2 2012 Q3 2012 Q4 2012 Q1 2013 0 20 40 60 P e rc e n ta ge of D Season

Variability Conditions: AZ

Variability Conditions: TN

80 100 s (% ) 20 40 60 80 100 P er c e n tag e o f D ays ( % )

Q2 2012 Q3 2012 Q4 2012 Q1 2013 0 20 40 60 80 Pe rc e n ta g e o f D a y s Season

Q2 2012 Q3 2012 Q4 2012 Q1 2013 0

P

Season

(10)

EPRI

High

‐

resolution

PV

Monitoring

Concentrated areas include Southeast, Atlantic Coast, and California

Clusters PV Plants

Planned Installed Recent Install

(11)

Example of Variability on a Feeder in Rome, GA

Example

of

Variability

on

a

Feeder

in

Rome,

GA

= DPV Site

Substation Substation

1 km2 _grid

© Google – Map data © Google

0.0 mi.

(12)

Monitoring

g

PV

Output

p

Variability

y

F e e d er ss

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 ilit y Ind e x (A vg by We e k) o r To ta l Ta p Co u n ts by We e k

Reg Tap Counts (total by week) Average Variability Index (by week)

-100 0 100 200 300 400 500 v e P o we r ( k V A 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

Va ri ab i Re gu la to

01/13/2013 01/14 01/15 01/16 01/17 01/18 01/19 -500 -400 -300 -200 -100 R eact iv

Using the high resolution data for modeling analysis

Using

the

high

resolution

data

for

modeling

analysis

(13)

Applying Measured PV Data to Feeder Model

Applying

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 Po w e r Pr od uc ti o n ( W )

Birmingham, AL (May 14, 2010)

200 400 600 800 1000 Po w e r Pr od uc ti o n ( W )

Feeder

Modeling

• Develop

feeder

d l

ith i

t

0 200

8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pm

Local Time (h)

0 200

8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pm

Local Time (h)

8976 8977 8976 8977

models

with

input

(14)

Analysis Approach

Analysis

Approach

Uniqueness

from

other

research

efforts

–

Large

sample

of

feeders/characteristics

considered

1000’

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

issue

Minimum Hosting Capacity

Maximum Hosting Capacity

Details on analysis method:

1.065 1.07

A 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 Re su lt f o r Ea c V D epl oy m en

t of location

B– Some penetrations

in this region are acceptable, site specific

1.035 1.04 1.045 Wo rs t-C a se U n ique P V

Threshold of violation

C– No penetrations in

this region are acceptable, regardless

of location

0 0.5 1 1.5 2

(15)

Sample

Analysis

– Spatial

&Time

Based

3D Visualization of PV Measurement Feeder Voltage Profile

(16)

Smart Inverter is a Key Integration Technology

Smart

Inverter

is

a

Key

Integration

Technology

DC Power AC Power

Traditional Inverter Functionality

Smart 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

(17)

What is a Smart

‐

Grid Ready Inverter?

What

is

a

Smart Grid

Ready

Inverter?

Link to distributed PV and

Storage Systems that become

Beneficial

distribution

system assets

Improving Efficiency

I i

Reliability

Enabling Higher

Penetration of _Improving

Power Quality

Asset Life

Deferred Costs

Penetration of Renewables

(18)

Hosting

Capacity

with

Inverter

Support

Function

PV at Unity Power Factor PV with Volt/var Control

Minimum Hosting Capacity

Maximum Hosting Capacity

Minimum Hosting Capacity Max Hosting Capacity

ANSI voltage limit

oltage (pu)

tages (pu)

ANSI voltage limit

um Feeder V

o

m

Feeder V

ol

t

2500 cases shown

Each point = highest primary voltage _Maxim

u

Maximu

m

( ) _{Increasing penetration (kW)} Increasing penetration (kW)

No observable violations regardless of PV size/location Possible violations based upon PV size/location

Possible violations based upon PV size/location

(19)

Hosting

Impact

of

Smart

Inverter

Functions

19

and

Set

Points

P

owe

r

Active Power

95% pf

Volt‐Watt 1

Volt‐Watt 2

Re ac ti v e P

Volt‐Var 1

Volt‐Var 2

98% pf

95% pf

ailab le Va rs % voltage 100% 0.95 1.0V

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,

% A v ailab le Va rs

% voltage Unity Power Factor

regardless of location

g

acceptable, site specific

g p

(20)

Understanding Potential Benefits of Storage

Understanding

Potential

Benefits

of

Storage

Power Supply

Energy 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

(21)

The Energy Storage Value Concept

The

Energy

Storage

Value

Concept

Photovoltaic

Peak Shift _{Customer Side}

For Illustration Only

P El t i

Balance of Plant

Regulation Services

Demand Peak Reduction

Applications

Power Electronics

P Q lit d

Regulation Services Voltage Support Inertia Support

Market

Applications Power Electronics

Balance of Plant Battery Cost

T&D Upgrade Deferral Power Quality and

Reliability Rate Based

Applications

Battery Cost Power Electronics

Costs of Storage

Benefits of Storage

(22)

The Value of Storage Realities

The

Value

of

Storage

Realities

For Illustration Only

P El t i

Balance of Plant

Demand Peak Reduction

Photovoltaic

Applications

Balance of Plant Power Electronics

Regulation Services Voltage Support

Inertia Support

Market

Applications

Reduction

Power Electronics Balance of Plant

Battery Cost

T&D Upgrade Deferral

Power Quality and

Reliability Rate Based_Applications

Battery Cost

Costs of Storage

Benefits of Storage

(23)

Various Sources of Flexibility

Various

Sources

of

Flexibility

• Conventional

Resources

– Peaking and cycling units

• Emerging

Resources

– Demand response_p Conventional Gen

– Energy storage

– Plug‐in electric vehicles

• VG

Power

Management

g

– Control VG output

• Institution/Market

Flexibility

– Coordination among Balancing

Emerging Resources

g g

Authorities (BAs)

– Shorter scheduling

• More

Transmission

VG P M t

(24)

Smart Grid Ready Inverter: Objectives

1. 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

(25)

Who are

Hydro One GRE

Who

are

Project

DTE Energy _{National Grid} Xcel

Energy

KCP&L

AEP _Pepco

Partners?

SDG&E

KCP&L

Southern Co.

DOE Project

(26)

Demonstration

Sites

225kW(DC) PV 1.7MW (DC) PV

1.7MW (DC) PV

300kVA

300kVA Inverters Ann Arbor, MI 18

18 –– 95kW Inverters95kW Inverters

Cedarville, NJ Cedarville, NJ

1MW (DC) PV 1MW (DC) PV 2

2 –– 500kW Inverters500kW Inverters

Haverhill MA Haverhill MA 605kW (DC) PV

605kW (DC) PV

330kW & 250kW Inverters 330kW & 250kW Inverters Everett MA

Everett MA Haverhill, MAHaverhill, MA

Everett, MA Everett, MA

(27)

1 Make Inverter Ready

1. 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?

Settings

Performance

and reliability?

Settings

(28)

Benefits Demonstrated at Different Sites

(29)

(30)

Testing at ESIF

‐

NREL’s Energy System Integration Facility

(31)

2. Revisit Anti

‐

Islanding

2. 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

(32)

Side

by

y

Side

comparisons

p

of

different

technologies

g

• Direct

transfer

trip

(DTT)

via

di

ll

i

radio,

cell

or

wire

• Power

line

carrier

communications

(PLCC)

low

or

high

g

frequency

q

y

• Shorting

switch

• Integration

of

DG

into

the

utility

SCADA

S

h

b

d

• Synchrophasor

‐

based

methods

• Research Prior Art

• Develop Functional Requirements

• Select Suitable Technology for Evaluation

E l t T h l i i L b d Fi ld

• Research Prior Art

• Develop Functional Requirements

• Select Suitable Technology for Evaluation

E l t T h l i i L b d Fi ld

• Evaluate Technologies in Lab and Field

(33)

Power

‐

Line

Carrier

Signal

for

DER

– Concept

Substation

Power Line Tone DX3 Pulsar _Transmitter

Generator _Island Controller

Island Grid

Grid

Island

X

(34)

3. Model DMS

‐

Level Integration

3. Model

DMS Level

Integration

Define functional requirements

for DMS-DERMS

Address gaps in

feeder operational

t l

New Types of DER

Managing 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

(35)

DER

Enterprise

Integration

GIS

MDMS

OMS

• DER representation

• Creation of groups and sharing of group

p

in 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

(36)

Project Resources

36

Project

Resources

https://solarhighpen.energy.gov/segis/electric

‐

power

‐

h i

i

research

‐

institute

Public Reports:

Integrating Smart Distributed Energy Resources with Distribution Management Systemsy , 1024360

Collaborative Initiative to Advance Enterprise Integration of DER, 1026789

Common Functions for Smart Inverters Version 2 1026809

Common Functions for Smart Inverters, Version 2, 1026809

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