NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

The Impact of Distributed Wind on Bulk Power System Operations in ISO-NE

13th Wind Integration Workshop

Carlo Brancucci Martinez-Anido, Bri-Mathias Hodge, and David Palchak (NREL); and Jari Miettinen (VTT)

Berlin, Germany November 11, 2014

NREL/PR-5D00-63083

2

Motivation and Scope

• Wind integration is hindered in the U.S. power system o The best wind resources are far from the main load centers o There are difficult regulatory and legal hurdles and substantial investments are required to

develop new transmission

• One possibility is to develop utility-scale wind turbines connected to existing distribution networks (assuming no transmission investment)

• Scope: To study the impact of a range of distributed wind penetration levels on bulk power system operations

• Case Study: Independent System Operator New England (ISO-NE) o 1.37% wind penetration in 2013 o Theoretical potential for 215 GW of onshore and offshore wind generation

3

ISO-NE PLEXOS Model • 3,314 nodes (1,862 above 69 kV) • 2,485 lines (2,085 above 69 kV) • 1,830 transformers • 468 generators (excluding wind) • DA/4HA/RT (load and wind forecasts) • Contingency and regulation reserves

Year 2010

Max (MW)

Total (TWh)

Load 27,102 130.8

Exports 3,018 7.2

Imports 3,195 12.8

02000400060008000

100001200014000

Inst

alle

d C

apac

ity (M

W)

Interconnections: ($3/MWh wheeling cost) • New Brunswick • Hydro Quebec • New York

4

ISO-NE PLEXOS Model—Validation

ISO-NE Published Data Model Results 0

20

40

60

80

100

120

140

Gen

erat

ion

(TW

h)

ImportsNuclearCoalGasOilBiomassHydroPumped H.WindSolar

ISO-NE Published Data Model Results 0

20

40

60

80

100

120

140

Dem

and

(TW

h)

LoadExportsPumping

8050 8100 8150 8200 8250 830020

40

60

80

100

120

140

160

hour

Rea

l-Tim

e Pr

ice

($/M

Wh)

ISO-NE Published DataModel Results

1250 1300 1350 1400 1450 150020

40

60

80

100

120

140

160

180

hour

Rea

l-Tim

e Pr

ice

($/M

Wh)

ISO-NE Published DataModel Results

0 1000 2000 3000 4000 5000 6000 7000 8000 90000

50

100

150

200

250

300

350

400

450

500

hours

Rea

l-Tim

e Pr

ice

($/M

Wh)

ISO-NE Published DataModel Results

5

Distributed Wind Scenarios Scenario Distance (lat-long degrees) Ratio

Penetration Level (%)

Number of Wind Sites

Installed Wind Capacity (MW)

Mean Wind Capacity Factor

1 0.025 (approx. 2.8 km) 1 1.95 87 690 0.432

2 0.050 (approx. 5.6 km) 1 4.96 201 1,718 0.439

3 0.075 (approx. 8.3 km) 1 6.96 269 2,398 0.441

4 0.100 (approx. 11.1 km) 1 8.62 325 2,978 0.441

5 0.125 (approx. 13.9 km) 1 10.40 373 3,556 0.444

6 0.125 (approx. 13.9 km) 2 15.61 506 5,264 0.448

7 0.125 (approx. 13.9 km) 3 18.90 590 6,336 0.450

8 0.125 (approx. 13.9 km) 4 21.21 641 7,074 0.451

Distance: Maximum distance between a wind site and the transmission node to which it is connected Ratio: Maximum ratio between the sum of the capacities of the wind sites connected to a node and the peak load at the node Wind Data: WIND Toolkit

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Distributed Wind Scenarios 4.95% 8.62%

15.6% 21.2%

Nodes Wind Sites

7

Electricity Generation Mix

0.00 1.95 4.96 6.96 8.62 10.4 15.6 18.9 21.20

5

10

15x 104

Gen

erat

ion

(GW

h)

Wind Penetration (%)

Imports Nuclear Coal Gas Oil Biomass Hydro Wind

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Gas GT and IC Electricity Generation

0 2 4 6 8 10 12 14 16 18 200

200

400

600

Gas

GT

Gen

erat

ion

(GW

h)

Wind Penetration (%)0 2 4 6 8 10 12 14 16 18 20 0

5

10

15

Gas

IC G

ener

atio

n (G

Wh)

9

Oil-Fired Electricity Generation

0.00 1.95 4.96 6.96 8.62 10.4 15.6 18.9 21.20

50

100

150

200

250

Oil

Gen

erat

ion

(GW

h)

Wind Penetration (%)

Oil GT Oil IC Oil ST

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Electricity Exchanges

0 2 4 6 8 10 12 14 16 18 200

2000

4000

6000

8000

10000

12000

Elec

tric

ity E

xcha

nges

(GW

h)

Wind Penetration (%)

ImportsExportsNet Interchange

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Ramping of Electricity Generators

0 5 10 15 200

0.5

1

1.5

2

2.5 x 105

Upw

ard

Ram

ping

/ G

ener

atio

n (M

W /

GW

h)

Wind Penetration (%)

NuclearCoalBiomassCCGas STHydroPumpedHydro

0 5 10 15 200

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Upw

ard

Ram

ping

/ G

ener

atio

n (M

W /

GW

h)

Wind Penetration (%)

NuclearCoalBiomassCCGas STHydro

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Wind Power Curtailment

0 2 4 6 8 10 12 14 16 18 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Win

d C

urta

ilmen

t (%

)

Wind Penetration (%)

13

Electricity Generation Costs

0 2 4 6 8 10 12 14 16 18 202.5

3

3.5

4 x 106

Tota

l Gen

erat

ion

Cos

t ($0

00)

Wind Penetration (%)0 2 4 6 8 10 12 14 16 18 20 1.5

2

2.5

3x 104

Star

t-up

& S

hutd

own

Cos

t ($0

00)

14

CO2 Emissions

0 2 4 6 8 10 12 14 16 18 200

0.5

1

1.5

2

2.5

3

3.5

4 x 107

CO

2 Em

issio

ns (t

on)

Wind Penetration (%)

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Source: CAISO

Different Wind Integration Approaches How would the presented results vary if no or perfect wind power forecasts would be assumed and if wind power curtailment would not be allowed?

Brancucci Martínez-Anido, C.; Hodge, B.-M. (2014). Impact of Utility-Scale Distributed Wind on Transmission-Level System Operations. NREL/TP-5D00-61824. Golden, CO: NREL, September.

Source: GE Energy / Purdue University Energy Center

16

Electricity Exchanges

0 2 4 6 8 10 12 14 16 18 20-12000

-10000

-8000

-6000

-4000

-2000

0

2000

4000

Wind Penetration (%)

Net

Ele

ctri

city

Impo

rts (

GW

h)

A - Forecast & CurtailmentB - Forecast & NO CurtailmentC - NO Forecast & NO CurtailmentD - Perfect Forecast & NO Curtailment

Brancucci Martínez-Anido, C.; Hodge, B.-M. (2014). Impact of Utility-Scale Distributed Wind on Transmission-Level System Operations. NREL/TP-5D00-61824. Golden, CO: NREL, September.

17

Negative Electricity Prices

0 2 4 6 8 10 12 14 16 18 200

1000

2000

3000

4000

5000

6000

Wind Penetration (%)

5-m

inut

e tim

e-st

eps w

ith n

egat

ive

ISO

-NE

mea

n el

ectr

icity

pri

ces

A - Forecast & CurtailmentB - Forecast & NO CurtailmentC - NO Forecast & NO CurtailmentD - Perfect Forecast & NO Curtailment

Brancucci Martínez-Anido, C.; Hodge, B.-M. (2014). Impact of Utility-Scale Distributed Wind on Transmission-Level System Operations. NREL/TP-5D00-61824. Golden, CO: NREL, September.

18

Conclusions Higher penetrations of distributed wind reduce: • Coal- and gas-fired electricity generation • CO2 emissions • Electricity imports • Total variable electricity generation costs The variability and uncertainty of wind power also increase: • Start-up and shutdown costs • Gas GT & IC and oil-fired electricity generation • Ramping of most conventional generators • Wind curtailment

The impact of distributed wind on bulk power system operations depends on the knowledge and control that the system operator has, therefore on wind power forecasts and curtailment.

Thank you! carlo.brancuccimartinez-anido@nrel.gov

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“Markets”

DA 4HA RT Horizon 1 year 1 year 1 year

Time Step 1 hour 1 hour 5 minutes Optimization

Window 1 day 4 hours 5 minutes

Look-Ahead (Resolution)

1 day (4 hours)

10 hours (2 hour) -

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Generators’ Commitment

DA: Nuclear Coal_ST Biomass

4HA: CC

Gas_ST Oil_ST

RT: Gas_GT Gas_IC

Jet_Oil_GT Oil_GT Oil_IC Wind

Hydro: DA generation is passed on to 4HA and RT Pumped Storage: Special commitment based on pumped load, available capacity, and price received in previous market

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Reserves

Contingency (Spin)

Up Regulation

Down Regulation Flexibility

On Yes Yes Yes ? Time Frame

(seconds) 600 300 300 3,600 (?)

Minimum Provision 824 MW

1% load + 95%

10-minute wind ramps

1% load + 95%

10-minute wind ramps

?

Available Generation All (except for nuclear and wind)

23

Regulation Reserves

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WIND Toolkit • The Weather Research and

Forecasting Model V.3.4.1 • 6-km nest for forecasts, 2-km for

re-analysis • Model output: 1 hour for

forecasts, 5 minutes for re-analysis

• 100+ TB model output: Parallel asynchronous I/O to improve output speed 50:1

• Power Data Set: • Power output at 126,000 sites • Onshore and offshore for CONUS • 2-km by 2-km spatial resolution • 5-minute temporal resolution • Years: 2007–2013

• Meteorological Data Set • Wind speed and direction • Temperature • Atmospheric pressure

• Forecast Data Set • Day-ahead forecasts • 6-hour-ahead forecasts • 4-hour-ahead forecasts • 1-hour-ahead forecasts

The Impact of Distributed Wind on Buld Power System Operations in ISO-NEMotivation and ScopeISO-NE PLEXOS ModelISO-NE PLEXOS Model—ValidationDistributed Wind ScenariosDistributed Wind ScenariosElectricity Generation MixGas GT and IC Electricity GenerationOil-Fired Electricity GenerationElectricity ExchangesRamping of Electricity GeneratorsWind Power CurtailmentElectricity Generation CostsCO2 EmissionsDifferent Wind Integration ApproachesElectricity ExchangesNegative Electricity PricesConclusionsThank you.“Markets”Generators’ CommitmentReservesRegulation ReservesWIND Toolkit