The Western Wind and Solar Integration Study (WWSIS) is one of the largest regional wind and solar integration studies 

to date. It was initiated in 2007 to examine the operational impact of up to 35% penetration of wind, photovoltaic (PV), and 

concentrating solar power (CSP) energy on the power system. The goal of the Western Wind and Solar Integration Study is 

to understand the costs and operating impacts caused by the variability and uncertainty of wind, PV, and CSP on the grid.

Wear-and-Tear Cost Data

Intertek-APTECH provided the following wear-and-tear cost data for seven categories of fossil-fueled plants: 

Data inputs include:

• Costs of hot, warm, and cold starts

• Costs of ramping down to minimum output

• Forced outage rate impacts

• Long-term heat rate degradation.

Ceiling on Wear-and-Tear Costs

GE Energy applied these wear-and-tear 

data to the original dispatch results from 

WWSIS1. Because these wear-and-tear 

costs were not explicitly modeled in WWSIS1 

but will be in WWSIS2, the revised dispatch 

of WWSIS2 is likely to show less ramping 

and cycling. Therefore, GE Energy’s analysis 

gives a ceiling on wear-and-tear impacts.

Results (right) show that cycling costs in the 

high-renewable scenario have a ceiling of 

$0.55–$1.90/MWh of renewables produced, 

which is a reduction in the value of the 

renewables of up to 2.4%.

Emissions Data

NREL used the Environmental Protection Agency’s Continuous Emissions Monitoring (CEM) data set to analyze hourly 

emissions from nearly every fossil-fi red plant in the U.S. NREL determined incremental emissions of CO2, NOx, and SO2

caused by startups, ramping, and partial loading.

Emissions Re-Analysis for WWSIS1

NREL applied these detailed startup, ramping, and part-loading emissions of NOx and CO2 to the dispatch results

of WWSIS1. In this re-analysis, generic emission rates, not plant-specifi c rates, were used for simplicity. The impact

of the startup, ramping, and part-loading emissions was relatively small and not always a negative benefi t. Avoided

CO2 emissions are 1.7% less, considering the detailed impacts, with the largest impact coming from the part-loading.

Avoided NOx emissions, on the other hand, were 3.3% better because of the lower NOx rates at part-loading.

Production Simulation Modeling

These refi ned wear-and-tear cost and emissions data are being used in the WWSIS2 production simulations of the 

Western Interconnection using the PLEXOS security-constrained unit commitment and 5-minute economic dispatch model.

Scenarios and Transmission

Four scenarios will be run for WWSIS2 in PLEXOS: 

• High solar (15% PV, 10% CSP, 8% wind)

• High mix (16.5% solar, 16.5% wind)

• High wind (4.8% PV, 3.2% CSP, 25% wind)

• Reference (8% wind, 3% solar).

NREL sited the scenarios and ran PLEXOS to 

expand transmission to bring resources to load.

Statistical Analysis

Extensive statistical analysis was conducted on the variability of the load, net load, and solar and wind data for each scenario. 

As the upper left plot shows, geographical aggregation reduces PV variability. The other three plots on the right are scatter plots 

showing the hourly change in load versus the hourly change in variable generation (VG). The points in the bottom right quadrants, 

where the load is increasing and the VG is decreasing, are the challenging hours for system operators. 

Next Steps

NREL is currently running PLEXOS simulations for each of the four scenarios. GE Energy will help identify and design 

mitigation options, which will be run subsequently. A report on these results will be produced by the end of FY12. 

WWSIS2 Input Data

Objective

WWSIS2 Preliminary Results

Wind 

Coal 

Nuclear 

Hydro 

Combined Cycle 

ydro

Gas Turbine 

PV 

CSP

0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1 

6:00 8:00 10:00 12:00 14:00 16:00 18:00 

Normalized output 

One Plant 

Two plants 

Six Plants 

25 plants 

So. Calif. 

Increasing PV plant aggregation in

southern CA for a partly cloudy day

Source: Jack King, 

under NREL subcontract

High-solar scenario High solar scenario

Wind Capacity (MW)

710 to 1,650

250 to 710

140 to 250

70 to 140

10 to 70

PV Capacity (MW)

104 to 200

64 to 104

36 to 64

12 to 36

0 to 12

CSP Capacity (MW)

186 to 200

142 to 186

105 to 142

84 to 105

64 to 84

Transmission expansion

for high-solar scenario

The Western Wind and Solar Integration Study Phase 2

New techniques allow the Western Wind and Solar Integration Study Phase 2 (WWSIS2) to include high 

penetrations of solar—not only CSP and rooftop PV but also utility-scale PV plants. WWSIS2 examines:

• What are the wear-and-tear costs of cycling and ramping of coal and gas plants?

• What are the emissions impacts of cycling and ramping of coal and gas plants?

• How should operators re-optimize unit commitment and economic dispatch with

these impacts taken into account?

• How do solar impacts compare with those of wind?

• What mitigation options are available?

In the Western Wind and Solar Integration Study Phase 1 

(WWSIS1), solar penetration was limited to 5%. Utility-scale 

PV was not included because of limited capability to model 

sub-hourly utility-scale PV output. System dispatch for the 

worst week of the 3 years analyzed is shown at right. High wind 

and solar output cause coal and other generators to cycle on 

and off and ramp more frequently. Utilities and policymakers 

have asked NREL to delve into the details of the impacts of 

cycling and ramping on wear-and-tear costs and emissions.

The Western Wind and Solar Integration Study Phase 1

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High Solar Scenario – Footprint VG

Variability (No CSP)

25000

15000

5000

-5000

-15000

-25000

Winter

Spring

Summer

Fall

Load Delta (MW/hr)

VG Delta (MW/hr)

-15000

-5000

5000

-10000

0

1000015000

25000

15000

5000

-5000

-15000

-25000

Load Delta (MW/hr)

VG Delta (MW/hr)

Intermediate Scenario – Footprint VG

Variability (No CSP)

Winter

Spring

Summer

Fall

-15000

-5000

5000

-10000

0

1000015000

25000

15000

5000

-5000

-15000

-25000

Load Delta (MW/hr)

VG Delta (MW/hr)

High Wind Scenario – Footprint VG

Variability (No CSP)

Winter

Spring

Summer

Fall

-15000

-5000

5000

-10000

0

1000015000

NREL/PO-5500-55392

Presented at the SunShot Grand Challenge Summit and Technology Forum • June 13-14, 2012 • Denver, Colorado

NREL is a national laboratory of the U.S. Department of Energy, Offi ce of Energy Effi ciency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.