PREPARED FOR:

The National Renewable Energy Laboratory

A national laboratory of the U.S. Department of Energy

PREPARED BY:

GE Energy

MAY 2010 

WESTERN WIND AND SOLAR 

INTEGRATION STUDY:

EXECUTIVE SUMMARY
NOTICE 

This report was prepared as an account of work sponsored by an agency of the 

United States government. Neither the United States government nor any agency 

thereof, nor any of their employees, makes any warranty, express or implied, 

or assumes any legal liability or responsibility for the accuracy, completeness, 

or usefulness of any information, apparatus, product, or process disclosed, or 

represents that its use would not infringe privately owned rights. Reference 

herein to any specific commercial product, process, or service by trade name, 

trademark, manufacturer, or otherwise does not necessarily constitute or imply 

its endorsement, recommendation, or favoring by the United States government 

or any agency thereof. The views and opinions of authors expressed herein do 

not necessarily state or reflect those of the United States government or any 

agency thereof. 

Available electronically at http://www.osti.gov/bridge

Available for a processing fee to U.S. Department of Energy 

and its contractors, in paper, from: 

U.S. Department of Energy 

Office of Scientific and Technical Information 

P.O. Box 62 

Oak Ridge, TN 37831-0062 

phone: 865.576.8401 

fax: 865.576.5728 

email: mailto:reports@adonis.osti.gov 

Available for sale to the public, in paper, from: 

U.S. Department of Commerce 

National Technical Information Service 

5285 Port Royal Road 

Springfield, VA 22161 

phone: 800.553.6847 

fax: 703.605.6900 

email: orders@ntis.fedworld.gov 

online ordering: http://www.ntis.gov/ordering.htm 

Printed on paper containing at least 50% wastepaper, including 20% 

postconsumer waste
WESTERN WIND AND SOLAR 

INTEGRATION STUDY:

EXECUTIVE SUMMARY

May 2010

Prepared for NREL by GE Energy

1 River Road

Schenectady, New York 12345

Technical Monitor: Debra Lew

Prepared under Subcontract No. AAM-8-77557-01

Subcontract Report

NREL/SR-550-47781

National Renewable Energy Laboratory 

1617 Cole Boulevard, Golden, Colorado 80401 

303-275-3000 • www.nrel.gov 

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 

Contract No. DE-AC36-08GO28308

Cover photos (from left to right): PIX # 15996, 08604, 10927 and 14898
ACKNOWLEDGMENTS

The National Renewable Energy Laboratory (NREL) thanks the U.S. Department 

of Energy (DOE) for sponsoring the Western Wind and Solar Integration Study. 

Contributors include:

PROJECT MANAGERS

Debra Lew NREL

Richard Piwko GE Energy

STUDY TEAM

GE Nicholas Miller, Kara Clark, Gary Jordan, Lavelle Freeman, Zhi Gao, 

Shakeer Meeran, Ekrem Gursoy, Miaolei Shao, Ryan Konopinski, 

Amanvir Chahal, Glenn Haringa, David Burnham, Kristen Bleyman

NREL Michael Milligan, Brian Parsons, Yih-Huei Wan, Erik Ela, Donna 

Heimiller, George Scott, Kirsten Orwig, Ray George, Nate Blair, Mark 

Mehos, Craig Turchi, Paul Denholm, Marc Schwartz, Dennis Elliott, 

Steve Haymes, Dave Corbus, Tony Markel

3TIER Group Cameron Potter, Bart Nijssen

Exeter Associates Kevin Porter, Sari Fink

Northern Arizona University Tom Acker, Karin Wadsack, Carson Pete,

Jason Kemper and Mark Bielecki

State University of New York at Richard Perez, Tom Hoff

Albany and Clean Power Research

WESTCONNECT Charlie Reinhold

TECHNICAL REVIEW COMMITTEE

Arizona Public Service Ron Flood

El Paso Electric Dennis Malone

NV Energy Vladimir Chadliev

Public Service of New Mexico Jeff Mechenbier, Tom Duane

Salt River Project Rob Kondziolka, Maria Denton

Tri-State Generation and Transmission Mark Graham, Eric Williams

Tucson Electric Power Gary Trent, Tom Hansen

Western Area Power Administration Bob Easton, Joe Liberatore

Xcel Energy Steve Beuning, Keith Parks, 

Tom Ferguson, Brett Oakleaf

American Wind Energy Association Ron Lehr

Consultant Brendan Kirby

Enernex Corporation Bob Zavadil

Lawrence Berkeley National Laboratory Andrew Mills

Renewable Energy Consulting Ed DeMeo

Sandia National Laboratory Abraham Ellis

University College Dublin Mark O’Malley

U.S. Department of Energy Charlton Clark and Larry Mansueti

Utility Wind Integration Group Charlie Smith

Western Electricity Coordinating Council Bradley Nickell

Western Interstate Energy Board Doug Larson, Tom Carr

WindLogics Mark Ahlstrom

Finally, we thank Bruce Green (NREL) and Mark Schroder (Purple Sage Design) for 

designing this Executive Summary and the full report.
INTRODUCTION

The focus of the Western Wind and Solar Integration Study (WWSIS) is to investigate the 

operational impact of up to 35% energy penetration of wind, photovoltaics (PVs), and 

concentrating solar power (CSP) on the power system operated by the WestConnect group 

of utilities in Arizona, Colorado, Nevada, New Mexico, and Wyoming1. WWSIS was 

conducted over two and a half years by a team of researchers in wind power, solar power, 

and utility operations, with oversight from technical experts in these fields. This report 

discusses the development of data inputs, the design of scenarios to address key issues, 

and the analysis and sensitivity studies that were conducted to answer questions about the 

integration of wind and solar power on the grid. 

The technical analysis performed in 

this study shows that it is operationally 

feasible for WestConnect to accommodate 

30% wind and 5% solar energy penetration, 

assuming the following changes to current 

practice could be made over time:

• Substantially increase balancing 

area cooperation or consolidation, 

real or virtual;

• Increase the use of sub-hourly 

scheduling for generation and 

interchanges;

• Increase utilization of transmission;

• Enable coordinated commitment 

and economic dispatch of generation 

over wider regions;

• Incorporate state-of-the-art wind and 

solar forecasts in unit commitment 

and grid operations;

• Increase the flexibility of dispatchable generation where appropriate (e.g., reduce 

minimum generation levels, increase ramp rates, reduce start/stop costs or minimum 

down time);

• Commit additional operating reserves as appropriate;

• Build transmission as appropriate to accommodate renewable energy expansion;

• Target new or existing demand response programs (load participation) to 

accommodate increased variability and uncertainty;

• Require wind plants to provide down reserves.

In addition, suggestions for follow-on work to further explore these and additional 

mitigation options are listed in the Conclusions and Next Steps section. 

WESTCONNECT

WestConnect is a group of transmission providers that are 

working collaboratively on initiatives to improve wholesale 

electricity markets in the West. Participants include Arizona 

Public Service, El Paso Electric Co., NV Energy, Public Service 

of New Mexico, Salt River Project, Tri-State Generation and 

Transmission Cooperative, Tucson Electric Power, Western 

Area Power Administration, and Xcel Energy.

1 WestConnect also includes utilities in California, but these were not included in WWSIS because California had already completed a renewable energy integration study for the state.

3
4

BACKGROUND

WWSIS and its sister study, the Eastern Wind Integration and Transmission Study 

(EWITS), follow the U.S. Department of Energy’s (DOE) 20% Wind Energy by 2030 

Study that considered the benefits, 

costs, and challenges associated 

with sourcing 20% of the nation’s 

energy from wind power by 2030 

[1, 2]. The study found that while 

proactive measures were required, 

no insurmountable barriers to 

reaching 20% wind were identified. Thus, DOE and the National Renewable Energy 

Laboratory (NREL) embarked upon WWSIS and EWITS to examine, in much greater 

depth, whether there were technical or physical barriers in operating the grid with 

20% wind. Solar power was included in WWSIS due to the significant solar resources 

and solar development in the West.

Four of the five states in WestConnect have Renewables Portfolio Standards (RPS) that 

require 15-30% of annual electricity sales to come from renewable sources by 2020-

2025. Additionally, WWSIS models the entire western interconnection, examining the 

operating impact of up to 23% penetration of wind and solar in the rest of the Western 

Electricity Coordinating Council (WECC). Most of the states in WECC have similar 

RPS requirements and renewable energy growth in the region has been significant.

The study was designed to answer questions that utilities, Public Utility 

Commissions, developers, and regional planning organizations had about renewable 

energy use in the West:

• What is the operating impact of up to 35% renewable energy penetration and 

how can this be accommodated?

• How does geographic diversity help to mitigate variability?

• How do local resources compare to remote, higher quality resources delivered 

by long distance transmission?

• Can balancing area cooperation mitigate variability?

• How should reserve requirements be modified to account for the variability in 

wind and solar?

• What is the benefit of integrating wind and solar forecasting into grid 

operations?

• How can hydro generation help with integration of renewables?

WWSIS and its sister study EWITS build upon a large body of work on wind 

integration [3-9]. Previous studies examined specific utilities or states, looking at the 

impact of wind on operations in the regulation (seconds to minutes), load following 

(minutes to hours), and unit commitment (hours to days) time frames. In these 

studies, hypothetical wind and transmission build-outs were typically added to 

the existing system, which was simulated or statistically analyzed over these time 

BALANCING AREAS 

Balancing areas are responsible for balancing load and 

generation within a defined area and maintaining 

scheduled interchanges with other balancing areas. 
5

frames. These studies generally consider the impact of the variability of wind (due 

to varying weather) and the uncertainty of wind (due to our inability to perfectly 

forecast the weather). Even if the weather and the wind could be perfectly forecast, 

STUDY ASSUMPTIONS

SCENARIO DEVELOPMENT:

• Specific energy targets for each of three technologies: wind, PV, and CSP were fixed. For example, wind sites could not be traded out for CSP sites.

• A number of capital cost assumptions in 2008 dollars were used in determining the different geographic scenarios: wind at $2000/kW, PV at $4000/kW, CSP with thermal storage at 

$4000/kW, transmission at $1600/MW-mile, and transmission losses at 1% per 100 miles. No 

tax credits are assumed or included.

• The geographic scenarios considered different interstate transmission build-outs and included these costs in the scenarios. Incremental intra-state transmission build-outs were not 

specified in this analysis. Existing transmission capacity is assumed to be unavailable for new 

renewable energy generation only for the scenario development process. 

• New transmission was undersized: 0.7 MW of new transmission was added for each 1.0 MW 

of remote generation.

PRODUCTION SIMULATION ANALYSIS:

• All study results are in 2017 nominal dollars with 2% escalation per year.

• $2/MBTU coal; $9.50/MBTU natural gas.

• Carbon dioxide costs were assumed to be $30/metric ton of CO2.

• Except in cases where specified, extensive balancing area cooperation is assumed (see box 

on page 19).

• The production simulation analysis assumes that all units are economically committed and 

dispatched while respecting existing and new transmission limits and generator cycling capabilities and minimum turndowns.

• Existing available transmission capacity is accessible to renewable generation.

• Generation equivalent to 6% of load is held as contingency reserves – half is spinning and 

half is non-spinning.

• The balance of generation was not optimized for renewables. Rather, a business-as-usual capacity expansion met projected load growth in 2017. Renewable energy capacity was added 

to this mix, so the system analyzed is overbuilt by the amount of capacity value of the renewable plants.

• Increased O&M of conventional generators due to increased ramping and cycling was not 

included due to lack of data.

• Renewable energy plant O&M costs are not included. Wind and solar are considered pricetakers.

• The hydro modeling did not reflect the specific climatic patterns of 2004, 2005, and 2006, but 

rather a 10-year long term average flow per month.

• The sub-hourly modeling assumes a 5-minute economic dispatch.
6

grid operators would still have to accommodate wind’s variability. It is important to 

note that operators already manage variability and uncertainty in the load; wind and 

solar add to that variability and uncertainty.

WWSIS was funded by DOE and was managed by NREL. The main partner in this 

study was WestConnect. The project team included 3TIER Group (wind power 

dataset, and wind and solar forecasts), State University of New York at Albany/Clean 

Power Research (solar radiation dataset), Exeter Associates (data collection), Northern 

Arizona University (wind validation and hydro), NREL (wind validation, and PV and 

CSP power datasets), and GE (scenarios, and main technical/economic analysis). A 

Technical Review Committee (TRC), composed of members of WestConnect utilities, 

western utility organizations, and industry and technical experts, met eight times to 

review technical results and progress. A broader stakeholder group, open to the public, 

met five times to ensure study direction and results were relevant to western grid 

issues. Interim and final results of this study have been vetted in approximately 30 

public forums.

The study examined grid operation for the year 2017. That is, system loads and 

generation expansion were projected to represent year 2017. While 35% renewable 

energy penetration was not expected by 2017, this year was selected in order to start 

with a realistic model of the transmission grid. The study examined inter-annual 

operability by modeling operations for year 2017 three times, using historical load 

and weather patterns from years 2004, 2005, and 2006.

WHAT THIS STUDY DOES AND DOES NOT COVER

While this study undertakes detailed analysis and modeling of the power system, it 

was meant to be a complement to other in-depth studies: 

• WWSIS is an operations study, not a transmission planning study, although 

different scenarios model different interstate transmission expansion options. 

• WWSIS is not a cost-benefit analysis, even though wind and solar capital costs 

were incorporated in scenario development. Rather WWSIS focuses on the 

variable operational costs and savings due to fuel and emissions. 

• WWSIS is not a reliability study, although analysis of the capacity value of wind 

and solar was conducted to assess their contributions to resource adequacy. 

A full complement of planning and operational electrical studies would be 

required to more accurately understand and identify system impacts.

• WWSIS does not address dynamic stability issues.

• WWSIS does not attempt to optimize the balance between wind and solar 

resources. Wind and solar levels were fixed independently.

In 2017, it is anticipated that WestConnect and WECC will operate differently 

from current practice. WWSIS assumed the following changes from current 

operational practice:
7

• Production simulations of WECC grid operations assume least-cost 

economic dispatch in which all generation resources are shared equally and 

not committed to specific loads. Except for California and Alberta, WECC 

currently utilizes a bilateral contract market with long and short-term 

contracts in which resources are contracted out to meet specific loads. 

• Other than California and Alberta, WECC currently operates as 37 separate 

balancing areas that utilize these bilateral contracts to balance their areas. 

Except where specified, this study assumes five regional balancing areas in 

WECC (Arizona-New Mexico, Rocky Mountain, Pacific Northwest, Canada 

and California). WWSIS does not consider any power purchase agreements, 

including those for renewables2. 

• Except for California and Alberta, transmission in WECC is primarily 

contractually obligated and utilized. Existing available transmission capacity 

may be contractually obligated and not accessible to other generation. This 

study assumes that existing available transmission capacity is accessible to 

other generation on a short-term, non-firm basis. 

• Pricing developed by production cost modeling can vary widely from 

bilateral contract prices, and was not aligned or calibrated with current 

bilateral contract prices. The incremental operations and maintenance (O&M) 

costs in the report do not necessarily replicate escalated current costs in the 

Western Interconnection. 

In addition to these caveats, there are reasons that the study results tend toward the 

conservative: 

• WWSIS did not model a more flexible non-renewable balance of generation 

than what exists and is planned in WECC today. If 20-35% variable generation 

were to be planned in WECC, more flexible generation would be likely 

planned as well, reducing the challenge that wind and solar place on 

operation in this study. 

• This study modeled the grid for the year 2017. If WWSIS were conducted for a 

later year when 35% renewables would be more plausible, the power system 

would likely have a larger load, more flexible balance of generation, and more 

transmission, all of which would help to accommodate the renewables. 

• The wind dataset used was conservative in terms of overestimating the actual 

variability found in measured wind plant output. 

• The base assumption of $9.50/MBTU for gas means that gas is displaced, 

which leaves coal (which in the West, is less flexible than gas) to accommodate 

the variability of the renewables. 

2 Thus, throughout this work, costs specifically and solely refer only to variable costs, i.e., fuel plus O&M plus carbon tax, that are 

incurred during operation. Prices paid to individual generators are not reported.
8

SCENARIOS

WIND, SOLAR, AND LOAD DATA

About 75 GW of wind generation sites were required for the study scenarios. Because 

there are not adequate measurements of wind speed or wind power to model this 

amount of wind generation, 3TIER Group employed a mesoscale Numerical Weather 

Prediction (NWP) Model to essentially recreate the weather in a 3-dimensional physical 

representation of the atmosphere in the western U.S. for the years 2004-2006. They 

then sampled this model at a 2-km, 10-minute resolution and modeled wind plants 

throughout this region, based on a Vestas V90 3-MW turbine. 3TIER Group also 

developed day-ahead wind forecasts for each hour. Over 960 GW of wind sites were 

modeled. The wind dataset is publicly available [10, 11].

Similarly, a lack of solar irradiance or power measurements led to the use of a satellite 

cloud cover model to simulate the United States at a 10-km, hourly resolution [12]. 

Day-ahead hourly solar forecasts were also developed [10]. PV was modeled in 100-

MW blocks as distributed generation on rooftops because modeling information for 

large, central station PV plants was not available at the time of the study. Over 15 GW 

of PV plants were included in the dataset. Ten-minute variability was subsequently 

added to the aggregate hourly outputs to create the 10-minute PV data. 

CSP was modeled as 100-MW blocks of parabolic trough plants with six hours of 

thermal storage. Over 200 GW of CSP plants were modeled in the dataset. Because the 

CSP with thermal storage produces a very stable output, the 10-minute dataset was 

created simply by interpolating the hourly dataset.

Hourly load-profile data for all operating areas in WECC were obtained from a Ventyx 

database, and 10-minute load data were derived by interpolating the hourly data.
9

SCENARIO DESCRIPTION

The WWSIS used a multidimensional scenario-based study approach to evaluate:

• Different levels of energy penetration for wind and solar generation, ranging 

from 11% to 35%;

• Different geographic locations for the wind and solar resources;

• A wide array of sensitivities to assess issues such as fuel costs, operating 

reserve levels, unit commitment strategies, storage alternatives, balancing 

area size, etc.

Table 1 shows the four levels of wind and solar energy penetration assumed for the 

study scenarios. The Preselected case includes that wind and solar capacity which 

was installed by the end of 2008. The 10% case includes 10% wind energy (relative to 

total annual load energy) and 1% solar energy (solar consisted of 70% CSP and 30% 

PV) in the study footprint, as well as the rest of WECC. The 20% case includes 20% 

wind energy and 3% solar energy in the study footprint, with 10% wind energy and 

1% solar energy in the rest of WECC. The 20/20% case includes 20% wind energy 

and 3% solar energy in the study footprint, as well as the rest of WECC. The 30% 

case included 30% wind energy and 5% solar energy in the study footprint, with 20% 

wind energy and 3% solar energy in the rest of WECC.

* Existing solar embedded in load

Three geographic scenarios were developed to examine the tradeoff between: 1) 

local resources that are closer to load, but have lower capacity factors and 2) remote 

resources that have higher capacity factors, but require long distance transmission 

to access loads. An algorithm was developed to select sites based on energy value, 

capacity value, and geographic diversity according to criteria developed for 

each scenario. Figure 1 shows maps of the study scenarios for the 30% case. Total 

nameplate ratings of wind generation for each state are shown in blue; solar MW 

ratings are shown in red. New transmission lines to increase interstate transfer 

capability are shown in black. Significant intra-state transmission also needs to be 

built to bring the renewable resources to the existing bulk transmission grid, but 

WWSIS did not examine intra-state transmission.

TABLE 1 − WIND AND SOLAR ENERGY PENETRATIONS FOR WWSIS CASES WITH NAMING CONVENTION IN BLUE.

CASE NAME IN FOOTPRINT REST OF WECC

NAME WIND + 

SOLAR

WIND SOLAR WIND SOLAR

PRE-SELECTED CASE 3%* 3% * 2% *

10% CASE 11% 10% 1% 10% 1%

20% CASE 23% 20% 3% 10% 1%

20/20% CASE 23% 20% 3% 20% 3%

30% CASE 35% 30% 5% 20% 3%
10

Figure 1 − Three geographic 

scenarios developed for siting of 

wind and solar plants in the 30% 

case, with appropriate interstate 

transmission included to bring 

resources to load.

In Area Scenario: Each state in the study footprint met its wind and solar energy 

targets using the best available wind and solar generation resources within its state 

boundary. No additional interstate transmission was added.

Local Priority Scenario: This scenario used the best wind and solar sites within the 

entire footprint, but included a 10% capital cost advantage to resources within each 

state. The result was a scenario that was about halfway between the In Area and 

Mega Project Scenarios. This scenario includes new interstate transmission, but not as 

much as the Mega Project Scenario.

Mega Project Scenario: The study footprint met its wind and solar energy targets by 

using the best available wind and solar resources within the study footprint. Given 

that many of the best wind resources are in Wyoming, this scenario includes a large 

penetration of wind generation in Wyoming (and other wind-rich areas), with new 

transmission lines to deliver the energy to load centers.

For all three of these scenarios, the rest-of-WECC scenario remains constant: each 

state in the rest of WECC meets its renewable energy target using the best available 

resources within the state boundary. 

Table 2 shows a summary of the total wind and solar MW ratings by state for the three 

study scenarios. Table 3 summarizes the capital costs for the three study scenarios.
11

TABLE 2 − SUMMARY OF AGGREGATED WIND AND SOLAR MW RATINGS BY STATE FOR WWSIS SCENARIOS

IN AREA

10% 1% 20% 3% 30% 5%

AREA LOAD MIN. 

(MW)

LOAD MAX. 

(MW)

WIND

(MW)

SOLAR

(MW)

WIND

(MW)

SOLAR

(MW)

WIND

(MW)

SOLAR

(MW)

ARIZONA 6,995 23,051 3,600 400 7,350 1,200 11,220 2,000

COLORADO EAST 4,493 11,589 2,040 300 3,780 800 5,640 1,400

COLORADO WEST 712 1,526 300 0 600 200 900 300

NEW MEXICO 2,571 5,320 1,080 200 1,920 400 2,790 700

NEVADA 3,863 12,584 2,340 200 4,680 700 7,050 1,100

WYOMING 2,369 4,016 930 100 1,620 100 2,340 300

IN FOOTPRINT 21,249 58,087 10,290 1,200 19,950 3,400 29,940 5,800

LOCAL PRIORITY

10% 1% 20% 3% 30% 5%

AREA LOAD MIN.

(MW)

LOAD MAX. 

(MW)

WIND

(MW)

SOLAR

(MW)

WIND

(MW)

SOLAR

(MW)

WIND

(MW)

SOLAR

(MW)

ARIZONA 6,995 23,051 2,850 400 5,2550 1,200 7,710 2,000

COLORADO EAST 4,493 11,589 2,190 300 3,870 800 4,650 1,400

COLORADO WEST 712 1,526 210 0 450 200 570 300

NEW MEXICO 2,571 5,320 1,350 200 2,100 400 2,970 700

NEVADA 3,863 12,584 1,350 200 2,490 700 3,450 1,100

WYOMING 2,369 4,016 1,650 100 4,020 100 7,410 300

IN FOOTPRINT 21,249 58,087 9,600 1,200 18,180 3,400 26,760 5,800

MEGA PROJECT

10% 1% 20% 3% 30% 5%

AREA LOAD MIN. 

(MW)

LOAD MAX. 

(MW)

WIND 

(MW)

SOLAR

(MW)

WIND 

(MW)

SOLAR

(MW)

WIND 

(MW)

SOLAR 

(MW)

ARIZONA 6,995 23,051 810 400 1,260 1,200 1,890 2,600

COLORADO EAST 4,493 11,589 2,010 300 2,400 800 2,490 1,200

COLORADO WEST 712 1,526 60 0 90 200 90 200

NEW MEXICO 2,571 5,320 1,860 200 2,700 400 4,350 1,000

NEVADA 3,863 12,584 570 200 1,020 700 1,440 600

WYOMING 2,369 4,016 3,390 100 8,790 100 13,770 100

IN FOOTPRINT 21,249 58,087 8,700 1,200 16,260 3,400 24,030 5,700

10% 1% 20% 3% 30% 5%

OUT OF FOOTPRINT

46,328 119,696 22,950 2,500 22,950 2,500 45,450 7,500

TABLE 3 − CAPITAL COSTS (IN US2008$) FOR STUDY SCENARIOS WITH 30% WIND ENERGY AND 5% SOLAR ENERGY 

IN THE STUDY FOOTPRINT.

SCENARIO WIND

(MW)

SOLAR

(MW)

TRANSMISSION

(GW-MI)

WIND

($B)

SOLAR

($B)

INTERSTATE 

TRANSMISSION ($B)

TOTAL

($B)

IN-AREA 29,940 5,800 0 59.9 23.2 0 83.1

LOCAL PRIORITY 26,760 5,800 2,100 53.5 23.2 3.4 80.1

MEGA PROJECT 24,030 5,700 6,900 48.1 22.8 11.0 81.9
12

The rest of WECC includes 45,450 MW of wind ($91 billion), 4000 MW of PV ($16 billion), and 3500 

MW of CSP ($14 billion). Intrastate transmission is not included in any of these scenario costs.

ANALYTICAL METHODS

Four primary analytical methods were used to evaluate the performance of the 

system with high penetrations of wind and solar generation: statistical analysis, 

hourly production simulation analysis, sub-hourly analysis using minute-to-minute 

simulations, and resource adequacy analysis.

Statistical analysis was used to quantify variability due to system load, as well as 

wind and solar generation over multiple time frames (annual, seasonal, daily, hourly, 

and 10-minute). The statistical analysis quantified the grid variability due to load 

alone over several time scales, using the interpolated hourly load data. The changes 

in grid variability due to wind and solar generation were also quantified for each 

scenario at various levels of aggregation. The statistical analysis also examined the 

forecast accuracy for wind generation.

Production simulation analysis with GE’s MAPS (Multi-Area Production Simulation) 

program was used to evaluate hour-by-hour grid operation of each scenario for 3 years 

with different wind, solar, and load profiles. WECC was represented as a set of 106 

zones, each with its own load profile, portfolio of generating plants, and transmission 

capacity with neighboring areas. The zones were grouped into 20 transmission 

areas. The production simulation results quantified numerous impacts of additional 

renewable generation on grid operation including:

• Amount of flexible generation on-line during a given hour, including its 

available ramp-up and ramp-down capability;

• Effects of day-ahead wind forecast alternatives in unit commitment;

• Changes in conventional generation dispatch;

• Changes in emissions (NOx, SOx, and CO2) due to renewable generation;

• Changes in grid operation costs, revenues, and net cost of energy;

• Changes in transmission path loadings;

• Changes in use of hydro resources;

• Changes in use and economic value of energy storage.

Minute-to-minute simulation analysis was used to quantify grid performance trends 

and to investigate potential mitigation measures during challenging situations, such 

as large 1-hour, 3-hour and 6-hour changes in net load, high levels of wind and solar 

penetration, low load levels with minimal maneuverable generation on-line, and/

or high wind forecast errors. Minute-to-minute analysis simulated the operation of 

dispatchable generation resources as well as variable wind and solar generation in the 

study footprint using one-minute time steps, while enforcing constraints related to 

unit maximum, minimum, ramp rate, intertie flow schedule, and regional Automatic 

Generator Control (AGC) functions. 
13

Resource adequacy analysis involved loss-of-load-expectation (LOLE) calculations 

for the study footprint using the Multi-Area Reliability Simulation program, MARS. 

The analysis quantified the impact of wind and solar generation on overall reliability 

measures, as well as the capacity values of the wind and solar generation resources.

Impacts on system-level operating reserves were also analyzed using a variety 

of techniques including statistics, production simulation, and minute-to-minute 

simulation. This analysis quantified the effects of variability and uncertainty, and 

related that information to the system’s increased need for operating reserves to 

maintain reliability and security.

The results from these analytical methods complemented each other, and provided a 

basis for developing observations, conclusions, and recommendations with respect to 

the successful integration of wind and solar generation into the WestConnect grid.

OPERATIONS WITH 

35% RENEWABLES

The power system is designed to handle variability in load. With wind and solar, 

the power system is called on to handle variability in the net load (load minus wind 

minus solar), which can be considerable during certain periods of the year. Figure 

2 shows the load, wind, solar, and net load profiles for the 30% case during two 

selected weeks in July and April. 

In the July week, (top plot), the net 

load (blue line at bottom edge) is 

not significantly impacted by wind 

and solar variation. However, in the 

April week (bottom plot), the high, 

variable wind output dominates the 

net load, especially during low load 

hours, leading to several hours of negative net load during the week. This week in 

April was the worst week in terms of operational challenges of the three years.

As an example of how the system would operate under less severe operating 

conditions, Figure 3 shows the generation dispatch for the same July week shown 

in Figure 2 for the In-Area Scenario. The left figure is without renewable generation 

and the right is the 30% case. Although the wind and solar generation are definitely 

noticeable, they primarily displace combined cycle and gas turbine generation, and 

have minimal impact on the steam coal units.

WWSIS finds that 35% renewable energy penetration 

is operationally feasible provided significant changes 

to current operating practice are made, including 

balancing area cooperation and sub-hourly generation 

and interchange schedule.
14

 

Figure 2 − With 35% renewables, system operators must now balance generation against the 

net load (blue) line. This may be straightforward (top, July) or challenging (bottom, April). 

Figure 4 shows similar information for the April week shown in Figure 2. Here, 

operating the system with renewable generation is much more challenging. The 

combined cycle generation has been almost completely displaced, as have significant 

levels of coal generation. Nonetheless, the system can operate with balancing area 

cooperation. Without balancing area cooperation, operations during this week would 

be extremely difficult, if not impossible, for individual balancing areas. 

How much renewable generation can the system handle? All three geographic 

scenarios show significant benefits with no negative effects in the 10% case. No 

significant adverse impacts were observed up to the 20% case in WestConnect, given 

balancing area cooperation. Increased renewable generation in the rest of WECC 

3 WECC requires 6% of load to be held as contingency reserves, half of which is required to be spinning (i.e., synchronized to the 

grid) reserves.
15

(20/20% case) led to increased stress on system operations within WestConnect, with 

some instances of insufficient reserves3

 due to wind and solar forecast error. These can 

be addressed, but the system has to work harder to absorb the renewables. Operations 

become more challenging for the 30% case in which load and contingency reserves 

are met only if the wind/solar forecasts are perfect. With imperfect forecasts, load is 

served but there are contingency reserve shortfalls. Extra spinning reserves can be held 

every hour of the year to meet those contingency reserve requirements, but the cost to 

hold enough to eliminate all contingency reserve shortfalls is very high. A more costeffective alternative is to establish a demand response program or develop strategies 

to more accurately predict when these shortfalls occur and schedule more reserves 

during those hours or add additional quick start generation where needed. In the 20% 

and 30% cases, decreased flexibility of either the coal or hydro facilities made operation 

more difficult and increased the costs of integrating renewable generation.

Figure 3 − 35% renewables have a minor impact on other generators during an easy week 

in July, 2006. WestConnect dispatch - no renewables (left) and 30% case (right)

Figure 4 − 35% renewables have a significant impact on other generation during the 

hardest week of the three years (mid-April 2006). WestConnect dispatch - no renewables (left) 

and 30% case (right)
16

BENEFITS OF 35% RENEWABLES

Wind and solar generation primarily displace gas resources nearly all hours of the year, 

given the fuel prices and carbon tax assumed for this study ($2/MBTU coal, $9.50/

MBTU gas, $30/ton CO2). Since gas-fired generation is typically more flexible than coal 

generation, the natural economic displacement of gas generation by wind and solar 

generation makes the balance of dispatchable generation on-line less flexible (fewer 

gas units, more coal units). Across WECC, operating costs drop by $20 billion/yr ($17 

billion/yr in 2009$) from approx $50 billion/yr ($43 billion/yr in 2009$), resulting in 

a 40% savings due to offset fuel and 

emissions. This savings does not 

account for the capital or operating 

costs associated with the wind, 

solar, or transmission facilities, nor 

does it include any of the costs that 

would be required to implement the operational reforms needed to accommodate the 

renewables including balancing area cooperation or sub-hourly scheduling, although 

presumably some of this savings would be used to recover the capital costs of building 

this scenario, including payments to wind and solar generators. Figure 5 (left plot) 

shows the overall impact on the operating costs of WECC for the various penetration 

levels under the In-Area Scenario with a state-of-the-art (SOA) forecast. The 30% case 

shows WECC operating cost savings of $20 billion/yr ($17 billion/yr in 2009$) due 

to the wind and solar generation resources. Figure 5 (right plot) divides these values 

by the corresponding amount of renewable energy provided. In the 30% case, this 

equates to $80/MWh ($60/MWh in 2009$) of wind and solar energy produced. Lower 

penetrations of renewables showed values up to $88/MWh ($75/MWh in 2009$) of 

renewable energy produced (see Section 6.2). These operating cost savings would 

be applied toward the costs of the wind and solar energy, and depending on the 

magnitude of these costs, may or may not be sufficient to cover them.

Figure 5 − WECC saves $20 billion ($17 billion in 2009$), or 40%, in annual operating costs 

in the 30% case, which is equivalent to $80 ($60 in 2009$) per MWh of wind and solar 

energy produced. Note: Chart on right starts at $70/MWh.

The 30% case reduced fuel and emissions costs by 

40% and CO2

 emissions by 25-45% across WECC.
17

At a $3.50/MBTU gas price, wind and solar primarily displace coal generation, leaving 

the more flexible gas generation resources to operate together with the wind and solar 

generation. With lower gas price assumptions, operating costs are reduced by 

about 40%, to $46/MWh ($39/MWh in 2009$), but emissions reductions are higher.

Figure 6 − Assuming $9.50/MBTU gas, renewable energy displaces gas (orange). At lower gas 

prices ($3.50/MBTU), coal is displaced instead, resulting in greater emissions reductions (blue).

Figure 6 shows the total WECC reductions in emissions for the 30% case. CO2

emissions would be reduced by nearly 120 million tons/year, or approximately 25%, 

for the 30% case. SOx emissions would be reduced by approximately 45,000 tons/

year (~5%) and NOx would be reduced nearly 100,000 tons/year (~15%) (see Section 

6.2.1). At a $3.50/MBTU gas price, CO2 emissions are reduced by nearly 200 million 

tons/year (45%), and NOx and SOx by 300,000 tons/year (50%) and 220,000 tons/year 

(30%), respectively.

BALANCING AREA COOPERATION IS ESSENTIAL 

There are three key benefits of balancing area cooperation: 1) aggregating diverse 

renewable resources over larger geographic areas reduces the overall variability of 

the renewables, 2) aggregating the load reduces the overall variability of the load, and 

3) aggregating the non-renewable 

balance of generation provides 

access to more balancing (and 

more flexible) resources. Figure 

7 shows the reduced-variability 

benefit arising from aggregating 

smaller transmission areas into the 

WestConnect footprint. Variability for 

small areas such as Colorado-West (CO-W) or Wyoming (WY) increases significantly 

as renewable penetrations increase from the 10% to the 30% case This effect becomes 

even more extreme at a more granular level, e.g., for specific balancing areas within 

The technical analysis performed in this study 

shows that it is feasible for the WestConnect region 

to accommodate 30% wind and 5% solar energy 

penetration, but it would require extensive balancing 

area cooperation or consolidation, real or virtual. 
18

a state (see Section 7.1). However, when the balancing areas across WestConnect are 

aggregated, there is only a slight increase in variability with increased renewables 

penetrations, and even a slight decrease in variability WECC-wide.

Figure 7 − The variability of the net load increases with increasing renewable energy penetration. 

Aggregating several transmission areas over the WestConnect footprint results in reduced 

variability. Percent increase in the standard deviation of the hourly changes of the net load in all 

areas for In-Area Scenario.

Figure 8 − WECC can save $2 billion ($1.7 billion in 2009$) by holding spinning reserves as 5 

large regions (right) rather than many smaller zones (left).

From an operational perspective, balancing area cooperation can lead to cost savings 

because reserves can be pooled. A sensitivity analysis was performed, running WECC 

as 106 zones (which are roughly equivalent to balancing areas in the southwest, but 

there are multiple zones per balancing area in the northwest) versus 5 large regions. 
19

Figure 8 shows the $2 billion ($1.7 

billion in 2009$) savings in WECC 

operating costs in the 10% case. 

There are significant savings from 

sharing reserves over larger regions, 

irrespective of the renewables on 

the system.

SUB-HOURLY SCHEDULING 

IS CRITICAL

The current practice of scheduling 

both the generation and interstate 

exchange only once each hour 

has a significant impact on the 

regulation duty. At high penetration 

levels, such hourly schedule 

changes can use most, if not all, of 

the available regulation capability 

to compensate for Area Control 

Error (ACE) excursions during 

large scheduled ramps. This can 

leave no regulation capability for 

the sub-hourly variability. 

The minute-to-minute simulations 

showed that the current practice of 

hourly scheduling has a greater impact on the regulation requirements than does the 

wind and solar variability. 

Sub-hourly scheduling can substantially reduce the maneuvering duty imposed on 

the units providing load following. In the 30% case, the fast maneuvering of combined 

cycle plants with sub-hourly 

scheduling is about half of that with 

hourly scheduling, as shown in 

Figure 9. Sub-hourly scheduling in 

the 30% case is roughly equivalent 

to the 20/20% case with hourly 

scheduling. Improvements in plant efficiency and reductions in O&M costs, while 

difficult to quantify, are expected from this smoother operation.

Balancing area (BA) cooperation can take many forms 

and means different things to different people. In WWSIS, 

cooperation is modeled by assuming:

• All generation resources, across all BAs, are committed 

from a common regional generation stack on a leastcost basis

• Generation commitments assume physical 

transmission capability is available for import or export 

of power transfers between BAs

• All generation dispatches are made on a least–

marginal-cost basis

• All regional reserves are shared across BAs; i.e., the 

most economic resources for reserves are used

• Day-ahead generation dispatch and inter-area 

transmission schedules can be modified during 

operation to enable sharing of load-following, 

regulation, and reserves

Mechanisms to enable these aspects of cooperation are 

numerous, and include facets currently used or proposed in 

WECC such as the ACE diversity interchange (ADI), dynamic 

scheduling, an energy imbalance service, and other 

means of consolidating BA services. Many technical and 

institutional barriers will need to be addressed to achieve 

the level of cooperation of the work presented here.

Sub-hourly scheduling will be required to successfully 

operate the system at high penetration levels without 

significantly increased regulating reserves.
20

Figure 9 – Fast maneuvering duty of combined cycle units can be cut in half by moving from 

hourly to sub-hourly scheduling. 

UNCERTAINTY (FORECAST ERROR) RESULTS 

IN THE BIGGEST IMPACT ON THE SYSTEM

Integrating day-ahead wind and solar forecasts into the unit commitment process is 

essential to help mitigate the uncertainty of wind and solar generation. Even though 

SOA wind and solar forecasts are imperfect and sometimes result in reserve shortfalls 

due to missed forecasts, it is still 

beneficial to incorporate them into 

the day-ahead scheduling process, 

because this will reduce the amount 

of shortfalls. Over the course of the 

year, use of these forecasts reduces 

WECC operating costs by up to 14%, 

or $5 billion/yr ($4 billion/yr in 

2009$), which is $12-20/MWh ($10-

17/MWh in 2009$) of wind and solar 

generation. The left side of Figure 

10 shows the WECC-wide operating 

cost savings for using SOA forecasts compared to ignoring wind in the day-ahead 

commitment. The right side shows the incremental cost savings for perfect wind and 

solar day-ahead forecasts, which would reduce WECC operating costs by another 

$500 million/yr ($425 million/yr in 2009$) in the 30% case (see Section 6.2.1), or $1-2/

MWh ($0.9-1.7/MWh in 2009$) of wind and solar generation.

Using state-of-the-art wind and solar forecasts in 

day-ahead unit commitment is essential and would 

reduce annual WECC operating costs by up to $5 

billion ($4 billion in 2009$) or $12-20/MWh ($10-17/

MWh in 2009$) of renewable energy, compared to 

ignoring renewables in the unit commitment process. 

Perfect forecasts would reduce annual costs by 

another $500 million ($425 million in 2009$) or $1-2/

MWh ($0.9-$1.7/MWh in 2009$) of renewable energy.
21

Figure 10 − WECC saves $1-5 billion ($1-4 billion in 2009$) in annual operating costs just by 

using a SOA day-ahead forecast in the unit commitment process (left). Incremental savings 

for perfect forecasts are an order of magnitude less (right).

THE IMPACTS OF EXTREME FORECAST ERRORS 

ON CONTINGENCY RESERVE SHORTFALLS

While on average, wind forecast error is not very large (8% mean absolute error 

across WestConnect), there are hours when wind forecast errors can be extreme, 

ranging up to over 11,000 MW of over- or under-forecast in WestConnect. Severe 

over-forecasts can result in contingency reserve shortfalls; severe under-forecasts can 

result in curtailment of wind.

Operating rules dictate that systems must carry contingency reserves to cover system 

events, such as tripping of a large generator. In WECC, the spinning portion of these 

contingency reserves is equivalent to 3% of the system load. Applying these WECC 

rules, severe over-forecasts can lead to under-commitment of generation units, which 

can result in contingency reserve shortfalls if insufficient quick-start capacity is 

available. 

If the forecast is perfect, there are no contingency reserve shortfalls, even in the 30% 

case. With a SOA forecast, Figure 11 shows that these contingency reserve shortfalls 

become an issue in the 30% case. It should be noted, however, that even these 

shortfalls represent only a tiny percentage (~0.005%) of the total load energy.
22

Figure 11 − Contingency reserve shortfalls start to become an issue in the 30% case. 

Increasing spinning reserve can reduce the shortfalls but even increasing spinning reserves 

by 25% of the day-ahead wind forecast does not completely eliminate reserve shortfalls. 

Hourly production simulation analysis shows spilled energy, or curtailment, on the left axis and 

contingency reserve shortfalls on the right axis for the In-Area Scenario with no wind/solar, the 

10, 20, and 30% case for a SOA forecast. The five bars on the right show the effect of increasing 

spinning reserve by 5, 10, 15, 20, and 25% of the day-ahead wind forecast.

Spinning reserves can be increased to cover these contingency reserve shortfalls, but 

at a cost. Figure 11 shows the impact of increasing spinning reserves by 5, 10, 15, 20 

and 25% of the day-ahead wind forecast. However, each additional 5% increment of 

committed spinning reserve is increasingly expensive, as shown in Figure 12, and 

even with a 25% increase in committed spinning reserves, not all contingency reserve 

shortfalls are eliminated. 

The average cost of increasing reserves is shown in Figure 12. Increasing the committed 

spinning reserve by 5% of the wind forecast increases WECC operating costs by over 

$3,000 per MWh ($2,550/MWh in 

2009$) of reduced reserve shortfall. 

Expressed another way, it would be 

comparable to pay some of the load 

$3,000/MWh ($2,550/MWh in 2009$) 

to drop off rather than increasing the 

spinning reserve by 5% of the forecast. 

At the other extreme, if spinning 

reserve is increased by 25%, it would 

cost an average of roughly $13,600/MWh ($11,600/MWh in 2009$) of reserve shortfall. 

The incremental reduction achieved by increasing the spinning reserve from 20% to 

25% of the forecast would cost over $100,000/MWh ($85,000/MWh in 2009$). It should 

It is more cost-effective to have demand response 

address the 89 hours of contingency reserve 

shortfalls rather than increase spin for 8760 hours of 

the year. Demand response can save up to $600M/

yr ($510M/yr in 2009$) in operating costs versus 

committing additional spinning reserves.
23

be more economic to use load participation (i.e., demand response) than to increase the 

spinning reserves to achieve the same objectives. Using load participation instead of 

committing additional generation for operating reserves would save up to $600 million 

($510 million in 2009$) in operating costs per year (see Sections 5.4, 7.2, and 6.2.2). 

Figure 12 − The cost of increasing spinning reserves increases with higher percentages of 

spin. The incremental cost increases sharply at higher percentages of spin, indicating that 

the cost of reducing those final reserve shortfalls is prohibitively high. The five bars show the 

effect of increasing spinning reserve by 5, 10, 15, 20, and 25% of the day-ahead wind forecast.

Figure 13 − A demand response program which requires load to participate in the 89 hours of 

the year that there are contingency reserve shortfalls is more cost-effective than increasing 

spin for each of the 8760 hours of the year. Hourly contingency reserve-shortfall duration curves 

for the In-Area 30% case with a SOA forecast with no additional spinning reserves, and then with 

spinning reserves increased by 5, 10, 15, 20, and 25% of the day-ahead wind forecast.
24

While the need for variability reserves doubles in the 

30% wind case, the backing down of conventional 

units results in more available up-reserves. Therefore, 

commitment of additional reserves is not needed to 

cover the increased variability.

Instead of holding additional spinning reserve for each of the 8760 hours of the year, 

Figure 13 shows that a demand response program could address those 89 hours of 

the year when there is a contingency reserve shortfall and have a total participation of 

approximately 1300 MW of load. The contingency reserve shortfalls could also be met by a 

combination of increased spinning reserves and a smaller demand response program. An 

alternative to demand response or increased spinning reserve for every hour of the year 

could be dynamic allocation of spinning reserves based on better forecasting, improved 

reserve policies, and more accurate prediction of when shortfalls are likely to occur.

HOW OFTEN IS WIND CURTAILED?

Uncertainty drives both curtailment and reserve shortfalls. With a perfect forecast, 

no wind or solar curtailment was necessary in any of the scenarios. Even in the few 

hours when the renewable generation exceeded the load in WestConnect, there was 

sufficient flexibility within WECC to absorb all of the generation. With a SOA forecast, 

no curtailment occurred up through the 20% case (see Figure 11). The hourly production 

simulations showed about 800 GWh of wind curtailment in the 30% case, representing less 

than 0.5% of the total wind energy production. In addition, the minute-to-minute analysis 

indicated that more wind curtailment may be required under some combinations of low 

load and high wind. Altogether, wind curtailment in the 30% case is estimated to be on the 

order of 1% or less of the total wind energy. Curtailment is also affected by flexibility of the 

balance of generation, e.g., raising the minimum operating point of the coal units to 70% 

increased the wind curtailment slightly (see Sections 6.2 and 6.4.4). 

THE EFFECT OF VARIABILITY – 

ARE ADDITIONAL RESERVES NECESSARY?

In addition to contingency reserves, utilities are required to hold variability or load 

following reserves to cover 10-minute load variability 95% of the time. Typically, 

utilities do not commit additional variability reserves because the existing dispatchable 

generating fleet can adequately cover this variability reserve requirement. With wind 

and solar, the net load variability increases and in the 30% case, the average variability 

reserve requirement doubles. However, when wind and solar are added to the system, 

thermal units are backed down because it is sometimes more economical to back down 

a unit rather than to decommit it. 

This results in more up-reserves 

available than in the case when there 

is no wind and solar, as shown in 

Figure 14. Therefore, commitment 

of additional reserves is not 

needed to cover variability in the 

study footprint. Figure 14 shows a 

duration curve of the total amount of up-reserves in the committed generation after the 

contingency reserve requirement is subtracted out, showing that 95% of the time, there 

are adequate up-reserves in the 30% Local Priority case.
25

Figure 14 − There are more up-reserves available in the 30% case than in the no wind/solar 

case because the additional renewable energy generation causes many conventional units to 

be backed down. Variability Up-Reserve Margin – Local Priority 30% vs. No Wind or Solar Case.

Regulating reserves are a subset of the fast variability requirement, but are held 

separately from the 10-minute variability reserves. Regulating reserves are required 

to be automatically controlled through AGC. While WWSIS did not evaluate which 

units were on AGC, the minute-to-minute analysis showed that sufficient regulating 

reserve capability was available in WestConnect.

Down reserves can be handled through wind curtailment when other resources are 

depleted. A wind plant can reduce its output very quickly in response to a command 

signal. Simulations in this study 

show that down reserves can be 

implemented through command 

signals (ACE signals) from system 

operators. With extensive balancing 

area cooperation, WestConnect can 

accommodate large amounts of 

renewables, and curtailment of wind is expected to be on the order of 1% or less in 

the 30% case. 

WHAT IS THE EFFECT OF DIFFERENT TRANSMISSION 

AND GEOGRAPHIC SCENARIOS?

The In-Area, Local Priority, and Mega Project Scenarios showed similar overall 

performance and economics for a given penetration level. This indicates that the 

specific locations of the wind and solar resources within WestConnect are not critical, 

provided there is adequate transmission infrastructure and access, and balancing area 

cooperation (see Sections 4.2.3, 5.5, 6.4.1, 6.4.6, 7.3.1). The assumption that existing 

transmission capacity can be fully utilized is an important change from present 

practice underpinning these results.

Wind plants can be curtailed to provide down 

regulating reserves instead of moving regulating units. 

Even so, curtailment is estimated to be on the order of 

1% or less of total wind energy in the 30% case.
26

Up to 20% renewable penetration could be achieved 

with little or no new long distance, interstate 

transmission additions, assuming full utilization of 

existing transmission capacity.

Figure 15 shows the study footprint’s monthly wind and solar energy as a percentage 

of load energy for all three scenarios in the 30% case in 2006.

Figure 15 − The month-to-month variation of wind and solar penetration is greater than the 

scenario-to-scenario variation.

The plots clearly illustrate that 1) despite the month-to-month variation, there is 

relatively little difference among scenarios at the footprint resolution and 2) there is 

significant month–to-month variation in energy across the year. In fact, there is more 

interannual variation in each month’s penetration levels than there is inter-scenario 

variation (see Section 4.1.1-4.1.2)

The total WECC operating cost savings per MWh of renewable energy for the different 

scenarios was also very similar across the three geographic scenarios, with only a slight 

increase in value as the wind plant locations were shifted to the higher capacity factor 

sites in the Local Priority and Mega Project Scenarios (see Section 6.4.1)

IS NEW LONG DISTANCE TRANSMISSION NEEDED?

Sufficient intra-area transmission within each state or transmission area for renewable 

energy generation to access load or bulk transmission is needed. However, the InArea Scenario, which included no 

additional long distance, interstate 

transmission, worked just as well 

operationally as the other scenarios. 

A sensitivity case examined the 

impact of the interstate transmission 

build-outs in the Local Priority 

and Mega Project Scenarios (which required $3.4 and $11 billion dollars, in 2008$, of 

interstate transmission respectively). Figure 16 shows the increased annual operating 
27

costs for the cases in which the new interstate transmission build-outs associated 

with the Local Priority and Mega Project Scenarios were eliminated. These increased 

costs are modest because renewables have displaced other generation and freed up 

transmission capacity. Assuming renewables have full access to this newly opened 

up capacity, there is less need for new transmission.

Assuming a 15% fixed charge rate, the 30% Local Priority Scenario would justify 

about $2 billion ($1.7 billion in 2009$) in transmission investments and the Mega 

Project Scenario would justify a little over $10 billion ($8.5 billion in 2009$). This rough 

estimate suggests that the full-scale transmission build-out might be justified in the 

30% Mega Project Scenario, but not at lower penetrations in the Mega Project or for 

any of the other scenarios. A more limited transmission build-out may be justified for 

the Local Priority Scenario. Of course, these estimates do not include any reliability 

benefits that would be realized from adding more transmission. All scenarios could be 

built out to the 10% case without any new interstate transmission (see Section 6.4.6). 

Figure 16 − Building the Local Priority and Mega Project Scenarios without the 

accompanying interstate transmission, increases costs at high penetrations in the 

Mega Project Scenario. 

IS ADDITIONAL STORAGE NEEDED?

Storage can provide many benefits to the system, including price arbitrage (charging 

when spot prices are low and discharging when prices are high), reliability, and 

ancillary services. Pumped storage hydro (PSH), solar thermal storage, and plug-in 

hybrid electric vehicles (PHEVs) were examined in WWSIS, with the largest focus 

on PSH (see Chapter 8). WWSIS evaluated only the price arbitrage part of the value 

proposition for PSH and found it much less than sufficient to economically justify 

additional storage facilities.
28

In the 10% and 20% wind penetration scenarios, gas generation is always on the 

margin (meaning that there are only small spot price variations during most days). 

As a result, there is no apparent opportunity to economically justify energy storage 

based on price arbitrage. Spot price variations increase in the 30% wind penetration 

scenarios, primarily due to errors in day-ahead wind energy forecasts. Occasionally, 

the price swings are very large. However, because this is driven by forecast 

uncertainty, it is not possible to strategically schedule the use of storage resources 

to take advantage of the price variations (and subsequently help eliminate the 

operational problems due to wind forecast errors). 

Figure 17 − A new 100-MW PSH plant with perfect pricing foresight would earn 

approximately $4 million/yr ($3.4million/yr in 2009$) from price arbitrage in the 30% case.

To examine a best-case scenario for storage, a new 100-MW PSH plant was added to 

the system and given perfect foresight of spot prices so that it could be dispatched to 

optimize revenue. The results in Figure 17 show the resulting number of operating 

hours and value. With no renewables, the PSH unit would run about 2200 hours (total 

pumping and generating time) and have an operating value of about $2.6 million 

($2.2 million in 2009$) for the year. With a perfect forecast, the value of the PSH unit 

decreased as the renewable penetration increased, due to decreased spot prices. With 

30% penetration and a perfect forecast the 100-MW PSH plant only had an annual 

operating value of $0.5 million ($0.4 million in 2009$) which would only yield a 

capitalized value of about $35/kW ($30/kW in 2009$). With an SOA forecast, spot 

prices are higher due to forecast error, and the 30% case increased the PSH annual 

operating value to $3.8 M ($3.2M in 2009$). However, this is several times less than 

would be required to recover costs for a new PSH plant4

 (see Section 8).
29

WHAT IS THE BENEFIT OF FLEXIBILITY IN 

THE REST OF THE GENERATION FLEET?

System flexibility is the key to accommodating increased renewable generation. WWSIS 

finds that at higher (30% case) penetration levels, decreased flexibility of either the coal or 

hydro facilities made operation more difficult and increased the costs of integrating the 

renewable generation. 

ALLOWING HYDRO TO PROVIDE LOAD FOLLOWING 

FOR WIND/SOLAR VARIABILITY IS HELPFUL

Hydro generation is capable of quick start/stop cycling and fast ramping, which makes it a 

good partner for variable wind and solar generation. Sensitivity analyses were conducted 

to examine the effects of hydro constraints on operating costs (see Section 6.4.2).

Figure 18 − Decreasing the flexibility of the hydro system increases costs. Operating cost savings 

for hydro dispatch to net load (left), and operating cost increase for constant output hydro operation 

(right), WECC.

This study assumed that hydro generation is normally committed and dispatched to 

serve daily peak net-load periods, while respecting the minimum operating points 

on the hydro units. The left side of Figure 18 shows the impact of adjusting the hydro 

schedules to account for the day-ahead renewable forecasts. Although the impact 

is relatively small at low levels of penetration, the WECC operating costs would be 

reduced by $200 million/yr ($170 million/yr in 2009$) at the 30% case, increasing the 

value of wind and solar energy by about $1/MWh ($0.9/MWh in 2009$). 

The right side of Figure 18 examines the impact if hydro operation were severely 

constrained, such as a requirement to maintain constant river flow. In this case, the 

WECC operating costs would increase by up to $1 billion/yr ($0.9 billion/yr in 2009$). 

Clearly it is important to maintain as much operational flexibility as possible with the 

hydro generation (see Section 6.4.2).

4 Assuming $1200-2000/kW capital cost and a fixed charge rate of 15% for a new PSH, $18-30 million annually would be needed 

to recover capital costs.
30

CONSTRAINTS ON COAL PLANTS RESULT 

IN HIGHER OPERATING COSTS

In WWSIS, coal plants were assumed to be able to operate down to minimum 

generation levels of 40% of nameplate capacity. WWSIS finds that higher minimum 

generation levels result in increased operating costs. 

A sensitivity case explored the impact of varying coal plant minimum loading on 

system operating costs. Increasing the minimum loading had minimal impact with 

wind penetrations less than 20%. At the 30% scenario, the impact becomes more 

noticeable, as shown in Figure 19. If coal plants are allowed to only operate above 

70% load, then WECC operating costs would increase by nearly $160 million/yr ($136 

million/yr in 2009$). See Section 6.4.4.

Figure 19 − Decreasing the flexibility of the coal fleet by increasing minimum generation 

levels on coal plants increases costs. Increased WECC operating costs over 40% minimum 

ratings on coal plants, 30% case.

WHAT IS THE CONTRIBUTION OF 

RENEWABLES TO RESOURCE ADEQUACY?

Variable resources such as wind and solar PV are primarily energy resources rather 

than capacity resources. However, they provide some contribution to reliability 

(resource adequacy). A range of capacity valuation techniques based on traditional lossof-load-expectation (LOLE) data were evaluated to consider the variability inherent 

with the renewable generation. This was conducted for WestConnect assuming no 

transmission constraints within the study footprint and no interconnections with the 

rest of WECC, so that the capacity value characteristics of the renewable generation 

could be isolated. 
31

Table 4 shows capacity values of wind based on daily LOLE which were typical of 

the overall analysis. Wind generation resources selected for this study were found to 

have capacity values in the range of 10% to 15%. Wind plant energy output tends to 

be higher during winter and spring 

seasons, and during nighttime 

hours, which is contrary to system 

peak load periods. Hence, the 

capacity value is low relative to the 

plant rating. PV solar plants have 

capacity values in the range of 25% to 30%. Although PV solar produces its energy 

during the daytime, output tends to decline in the late afternoon and early evening 

when peak load hours often occur. The PV output was based on the DC rating of the 

system; it would be 23% higher if based on the AC rating and included inverter and 

other losses from the outset. Concentrating solar plants with thermal energy storage 

have capacity values in the range of 90% to 95%, similar to thermal generating plants. 

Their maximum energy production tends to be during the long summer days, and 

the storage capability extends the energy output through the late afternoon and early 

evening hours, when peak loads occur (see Sections 4.2, 4.3, and 9.2 through 9.7).

TABLE 4 − CAPACITY VALUES FOR 2004-2006. 

CASE WIND ONLY PV ONLY CSP ONLY WIND+PV+CSP

10% 13.5% 35.0% 94.5% 18.2%

20% 12.8% 29.3% 94.8% 19.7%

30% 12.3% 27.7% 95.3% 19.8%

Wind was found to have capacity values of 10-15%; 

PV was 25-30%; and CSP with 6 hours of thermal 

energy storage was 90-95%.
32

CONCLUSIONS AND NEXT STEPS

The technical analysis performed in this study shows that it is feasible for the 

WestConnect region to accommodate 30% wind and 5% solar energy penetration. 

This requires key changes to current practice, including substantial balancing area 

cooperation, sub-hourly scheduling, and access to underutilized transmission capacity.

WWSIS finds that both variability and uncertainty of wind and solar generation 

impacts grid operations. However, the uncertainty (due to imperfect forecasts) leads to 

a greater impact on operations and results in some contingency reserve shortfalls and 

some curtailment, both of which are relatively small. The variability leads to a greater 

sub-hourly variability reserve requirement, but because conventional units are backed 

down, the system naturally has extra reserve margins.

This study has established both the potential and the challenges of large scale 

integration of wind and solar generation in WestConnect and, more broadly, in WECC. 

However, changes of this magnitude warrant further investigation. The project team 

regards the following as valuable topics for exploration:

• Characterization of the capabilities of the non-renewable generation portfolio 

in greater detail (e.g., minimum turndown, ramp rates, cost of additional wear 

and tear);

• Changes in non-renewable generation portfolio (e.g., impact of retirements, 

characteristics, and value of possible fleet additions or upgrades);

• Reserve requirements and strategies (e.g., off-line reserves, reserves from nongeneration resources);

• Load participation or demand response (e.g., functionality, market structures, 

PHEV);

• Fuel sensitivities (e.g., price, carbon taxes, gas contracts and storage, hydro 

constraints and strategies);

• Forecasting (e.g., calibration of forecasting using field experience, strategies for 

use of short-term forecasting);

• Rolling unit commitment (e.g., scheduling units more frequently than once on a 

day-ahead basis);

• Transmission planning and reliability analyses (e.g., transient stability, voltage 

stability, protection and control, intra-area constraints and challenges);

• Hydro flexibility (e.g., calibration of hydro models with plant performance).
33

REFERENCES

[1] EERE (U.S. DOE Office of Energy Efficiency and Renewable Energy). July 2008. 20% 

Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electric Supply. 

DOE/GO-102008-2567. Washington: EERE. www1.eere.energy. gov/windandhydro/

pdfs/41869.pdf.

[2] Enernex Corporation. January 2010. “Eastern Wind Integration and Transmission 

Study”, NREL Report No. SR-550-47078, www.nrel.gov/wind/systemsintegration/

pdfs/2010/ewits_final_report.pdf.

[3] New York State Energy Research and Development Authority. March 2005. “The 

Effects of Integrating Wind Power on Transmission System Planning, Reliability, and 

Operations,” www.nyserda.org/publications/wind_integration_report.pdf. 

[4] California Energy Commission. July 2007. Intermittency Analysis Project Study. 

“Appendix B - Impact of Intermittent Generation on Operation of California Power 

Grid,” www.energy.ca.gov/2007publications/CEC-500-2007-081/CEC-500-2007-081-

APB.PDF.

[5] Ontario Power Authority. October 2006. Independent Electricity System Operator, 

Canadian Wind Energy Association’s “Ontario Wind Integration Study,” www.

powerauthority.on.ca/Storage/28/2321_OPA_Report_final.pdf.

[6] GE Energy. March 2008. Attachment A: Analysis of Wind Generation Impact on 

ERCOT Ancillary Services Requirements. Prepared for Electric Reliability Council 

of Texas. Schenectady, NY: GE Energy. http://www.ercot.com/content/news/ 

presentations/2008/Wind_Generation_Impact_on_Ancillary_Services_-_GE_ Study.zip. 

[7] Smith, C., et al. August 2007. “Utility Wind Integration and Operating Impact State 

of the Art”, IEEE Power and Energy, Vol 22, No. 3, pp 900-908, www.nrel.gov/wind/

systemsintegration/pdfs/2007/milligan_wind_integration.pdf.

[8] DeMeo, E., et al. Nov/Dec 2007. “Accommodating Wind’s Natural Behavior”, 

IEEE Power & Energy Magazine, pp 59-67 http://ieeexplore.ieee.org/

iel5/8014/4382976/04383124.pdf.

[9] Corbus, D., D. Lew, G. Jordan, W. Winters, F. Van Hull, J. Manobianco, and R. 

Zavadil. November/December 2009. “Up with Wind: Studying the Integration and 

Transmission of Higher Levels of Wind Power.” IEEE Power and Energy, 7(6): 36–46. 

[10] 3TIER. March 2010. Development of Regional Wind Resource and Wind Plant 

Output Datasets, NREL SR-550-47676, http://www.nrel.gov/docs/fy10osti/47676.pdf.

[11] NREL. Wind Integration Datasets. www.nrel.gov/wind/integrationdatasets.

[12] Wilcox, S., April 2007. “National Solar Radiation Database, 1999 – 2005: User’s 

Manual,” NREL Report TP-581-41364, http://www.nrel.gov/docs/fy07osti/41364.pdf.
34
35
36