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

0

2000

4000

6000

8000

10000

12000

14000

Installed Capacity (MW)

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

Generation (TWh)

Imports

Nuclear

Coal

Gas

Oil

Biomass

Hydro

Pumped H.

Wind

Solar

 

ISO-NE Published Data Model Results 0

20

40

60

80

100

120

140

Demand (TWh)

Load

Exports

Pumping

8050 8100 8150 8200 8250 8300 20

40

60

80

100

120

140

160

hour

Real-Time Price ($/MWh)

ISO-NE Published Data

Model Results

1250 1300 1350 1400 1450 1500 20

40

60

80

100

120

140

160

180

hour

Real-Time Price ($/MWh)

ISO-NE Published Data

Model Results

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 0

50

100

150

200

250

300

350

400

450

500

hours

Real-Time Price ($/MWh)

ISO-NE Published Data

Model 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
6

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 21.2 0

5

10

15x 104

Generation (GWh)

Wind Penetration (%)

Imports Nuclear Coal Gas Oil Biomass Hydro Wind
8

Gas GT and IC Electricity Generation

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

200

400

600

Gas GT Generation (GWh)

Wind Penetration (%)

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

5

10

15

Gas IC Generation (GWh)
9

Oil-Fired Electricity Generation

0.00 1.95 4.96 6.96 8.62 10.4 15.6 18.9 21.2 0

50

100

150

200

250

Oil Generation (GWh)

Wind Penetration (%)

Oil GT Oil IC Oil ST
10

Electricity Exchanges

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

2000

4000

6000

8000

10000

12000

Electricity Exchanges (GWh)

Wind Penetration (%)

Imports

Exports

Net Interchange
11

Ramping of Electricity Generators

0 5 10 15 20 0

0.5

1

1.5

2

2.5 x 105

Upward Ramping / Generation (MW / GWh)

Wind Penetration (%)

Nuclear

Coal

Biomass

CC

Gas ST

Hydro

Pumped

Hydro

0 5 10 15 20 0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Upward Ramping / Generation (MW / GWh)

Wind Penetration (%)

Nuclear

Coal

Biomass

CC

Gas ST

Hydro
12

Wind Power Curtailment

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

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Wind Curtailment (%)

Wind Penetration (%)
13

Electricity Generation Costs

0 2 4 6 8 10 12 14 16 18 20 2.5

3

3.5

4 x 106

Total Generation Cost ($000)

Wind Penetration (%)

0 2 4 6 8 10 12 14 16 18 20 1.5

2

2.5

3

x 104 Start-up & Shutdown Cost ($000)
14

CO2 Emissions

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

0.5

1

1.5

2

2.5

3

3.5

4 x 107

CO2 Emissions (ton)

Wind Penetration (%)
15

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 Electricity Imports (GWh)

A - Forecast & Curtailment

B - Forecast & NO Curtailment

C - NO Forecast & NO Curtailment

D - 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 20 0

1000

2000

3000

4000

5000

6000

Wind Penetration (%)

5-minute time-steps with negative ISO-NE mean electricity prices

A - Forecast & Curtailment

B - Forecast & NO Curtailment

C - NO Forecast & NO Curtailment

D - 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
20

“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) -
21

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
22

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
24

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