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 Improved Solar Forecasts on 

Bulk Power System Operations in ISO-NE

4th Solar Integration Workshop

Carlo Brancucci Martinez-Anido, 

Anthony Florita, and 

Bri-Mathias Hodge 

Berlin, Germany

November 10, 2014

NREL/PR-5000-63082
2

Motivation and Scope

• The economic benefits from renewable energy forecasting are largely 

unquantified in the power community

o Current renewable energy penetration levels in the United States are often too low to 

appreciably quantify the value of improving renewable energy forecasting

o The power system is so complex that it is often difficult to assign costs or benefits to a single 

generator

• Solar power installations are rapidly growing

o Future penetration levels will soon require increased attention to the value of forecasting

• Scope: To study the impact of improved solar forecasts on bulk power 

system operations

• Case Study: Independent System Operator New England (ISO-NE)

o Future scenario with 25% solar power penetration
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 solar)

• DA/4HA/RT (load and solar forecasts)

• Contingency and regulation reserves

Year 

2006

Max

(MW)

Total 

(TWh)

Load 28,130 132.1

Interconnections: 

($3/MWh wheeling cost)

• New Brunswick

• Hydro Quebec

• New York

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

Installed Capacity (MW)
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

Solar Power Data

NREL Solar Power Data for Integration Studies 

(also used within the Eastern Renewable Generation Integration Study)

4,874 MW installed capacity in ISO-NE:

• 68 utility-scale solar power plants (x4)

• 76 distributed solar power plants (x8)

Both utility-scale and distributed solar power plants are already well distributed 

throughout the ISO-NE power system. The solar output smoothing for high solar 

penetrations is almost the same in the case with additional solar sites as in our case, in 

which we multiply the units included in the database.

Solar Penetration

Level (%)

Solar Capacity 

(MW)

Normalized Hour-to-Hour

Solar Variability (%)

0.54 584 6.85

1.08 1,180 6.78

2.08 2,246 6.77

2.5 2,424 6.81

4.5 4,874 6.73

12.5 13,824 6.73

25 27,648 6.73

Solar Power Forecasts

• 4HA included in the database

• DA derived from state-of-the-art 

numerical weather prediction, the 

Weather Research and Forecasting 

Model (National Center for 

Atmospheric Research)
6

Seven Scenarios

• No solar power

• No solar power forecasting

• Solar power forecasting

• Solar power forecasting—25% uniform improvement

• Solar power forecasting—50% uniform improvement

• Solar power forecasting—75% uniform improvement

• Perfect solar power forecasting—100% uniform improvement
7

Net Generation Costs

Net Generation Costs = Fuel Costs + Variable Operations and Maintenance 

Costs + Start-Up and Shutdown Costs + Import Costs – Export Revenues
8

Solar Power Curtailment
9

Electricity Generation Mix
10

Mean Electricity Price
11

Hourly Electricity Price Variability
12

Conclusions—Generation Costs

• Integrating 25% solar power penetration in ISO-NE with DA and 4HA 

forecasts reduces net generation costs by 22.9%

• Without solar power forecasts, the reduction in net generation costs is only 

12.3%

o Overcommitment of generation

o Higher solar power curtailment

• If solar power forecasts are uniformly improved by 25%, net generation costs 

are further reduced by 1.56% ($46.5 M)

• There are no significant differences if solar power forecasts are further 

improved

o Very large share of gas-fired generators

o Relatively small share of “base load” power plants

• However, better solar power forecasts at the HA or subhourly timescale could 

still provide additional savings
13

Conclusions—Prices

• Integrating 25% solar power penetration reduces the mean electricity price in 

ISO-NE by 31% when solar power forecasts are not considered

• If solar power forecasts are used, the reduction is only 7%

• Integrating 25% solar power penetration increases the hourly electricity price 

variability by 116% when solar power forecasts are considered

• If solar power forecasts are not used, the increase is only 40%

o Overcommitment of generation

o System is less flexible when integrating variable and uncertain solar power (higher 

curtailment)

• Solar power forecasting improvements show small reduction in electricity 

prices and their variability
14

Future Work

• Analyze the impact and value of solar power forecasting improvements when 

solar curtailment is not allowed

• Study interactions among load and solar power uncertainties

• Study the economic benefits of DA solar power forecasts without assuming 

any 4HA market

• Study the impact and value of solar power forecasts at the HA or subhourly 

timescale
Thank you!

carlo.brancuccimartinez-anido@nrel.gov
16

“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) -
17

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

Solar

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
18

Reserves

Contingency 

(Spin)

Up 

Regulation

Down 

Regulation

On Yes Yes Yes

Time Frame 

(seconds) 600 300 300

Minimum

Provision 824 MW 1% load 1% load

Available

Generation All (except for nuclear and solar)