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Tackling Climate Change in the 

United States: The Potential 

Contribution from Wind Power 

Preprint 

M. Milligan, Consultant 

National Renewable Energy Laboratory 

To be presented at Solar 2006 Conference 

Denver, Colorado 

July 7–13, 2006 

Conference Paper 

NREL/CP-500-40230

July 2006 
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Tackling Climate Change in the United States:

The Potential Contribution from Wind Power

Michael Milligan, Consultant

National Renewable Energy Laboratory

National Wind Technology Center 

1617 Cole Blvd. MS 3811 

Golden, CO 80401 

michael_milligan@nrel.gov 

ABSTRACT 

To support the Western Governors’ Association’s (WGA’s)

Clean and Diversified Energy Advisory Committee 

(CDEAC), a Wind Task Force (WTF) was convened to 

assess the feasibility of achieving 30,000 megawatts (MW)

of clean and diversified energy in the West by 2015. The 

WTF examined the near-term potential of wind energy in

the West, using a combination of technical supply curves

based on GIS data, and information from recent utility and

transmission studies. The study results indicate a very large 

potential for wind generation in the West. Supplementing

the GIS analysis is information extracted from utility

integrated resource plans (IRPs) that include wind additions

in the near term, along with estimates of wind development 

that will be induced by state renewable portfolio standards 

(RPSs). However, these results depend on federal and state 

policy support and transmission access. 

In this paper, we briefly discuss the results of the WTF

report and develop expanded wind supply curves for the 

entire United States. Wind potential was estimated using a 

GIS database that contains data on average annual wind

speed and transmission lines. We also develop estimates of

carbon reduction that would result from large-scale 

deployment of wind and find that 2,000-4,000 million

metric tons of carbon could be avoided by 2030. 

1. INTRODUCTION 

Modern wind turbines have evolved significantly in the past

few years. In the United States, the typical modern turbine 

has a generating capacity exceeding 1 MW and a hub height

of 80 meters from the ground. Recent wind power plants

may consist of projects owned by several entities and that 

have aggregate capacity in the hundreds of megawatts.

Energy produced by a wind turbine depends on the wind, 

which is a variable resource over several time scales. This 

variability is cause for concern among power system

operators, who are responsible for maintaining system

balance. During the past several years, several 

comprehensive wind integration studies have been

performed that analyze the power system’s ability to 

incorporate wind. The U.S. studies show a modest cost

ranging up to about $5/MWh for the ancillary service 

impact of wind. This is the additional cost that wind

imposed in the process of maintaining electrical system

balance. Most integration studies involve detailed

chronological power system simulations that mimic the 

overall power system operation with wind. To date, the 

variability of wind does not appear to be a significant

hindrance to its use as an energy resource, although the 

specific impacts and costs would vary from system to 

system and would depend on the size of the wind plant

relative to the balancing authority.

The pattern of wind generation may not match loads on a

seasonal or diurnal basis. Wind is primarily an energy

resource, but it can displace other capacity at a relatively

small fraction of its rated capacity. 

During 2005, approximately 2,500 MW of wind generating

capacity was installed in the United States. According to the 

American Wind Energy Association1

, current U.S. wind

capacity stands at 9,149 MW. The task force used a recent 

analysis2

 to estimate potential wind that would come online

by 2015 in response to state RPSs in the West. According to

the WTF, new wind capacity induced by these RPSs could 

range from about 5,600 MW to about 10,200 MW by 2015. 

Utility IRPs in the West may also result in about 3,600 MW

of new wind capacity by 2015. And recent volatility in

natural gas prices has had a significant impact on utilities 

that burn gas to produce power. In some cases, wind energy

is the cost-effective choice, further stimulating wind

development. 

1
In the United States, a production tax credit (PTC) that 

reduces the effective cost of wind generation has been in

place over the past few years. Unfortunately, the PTC

expired in 2004, causing wind development in the United 

States to nearly cease. When the PTC was renewed, wind

development that had been on hold quickly materialized, 

causing an enormous increase in the demand for turbines. 

Because of this large swing in turbine demand, 

manufacturers have had difficulty providing sufficient

turbines to the market, and prices have increased. Combined

with higher steel prices and unfavorable currency exchange

rates, 2005 and 2006 experienced a significant increase in

turbine costs. Because of the complex interaction of all the 

contributing factors to this cost increase, it is not clear 

whether the current prices represent a temporary condition

or whether turbine costs are on an upward trend. The WTF 

report discusses this issue in more detail. 

2. NOMENCLATURE 

CDEAC – Clean and Diverse Energy Advisory Committee 

GIS – geographical information system

GW – gigawatt

GWh – gigawatt-hour

IRP – integrated resource plan 

LCOE – levelized cost of energy

MISO – Midwest Independent System Operators

MTEP – MISO Transmission Expansion Plan

MW – megawatt 

NREL – National Renewable Energy Laboratory

NTAC – Northwest Transmission Assessment Committee 

PTC – production tax credit 

RMATS – Rocky Mountain Area Transmission Study

RPS – renewable portfolio standard 

SSG-WI – Seams Steering Group of the Western

Interconnection

TWH – terawatt-hour 

WECC – Western Electricity Coordinating Council

WGA – Western Governors’ Association 

WTF – Wind Task Force (of the CDEAC)

3. RESOURCE OVERVIEW 

The National Renewable Energy Laboratory (NREL) has

assembled a comprehensive GIS system for renewable 

generation. The GIS dataset for wind is based on a largescale meteorological simulation that “re-creates” the 

weather, extracting wind speed information from grid points

that cover the area of interest. Mapping processes are not 

always directly comparable among the states, but NREL has

validated maps from approximately 30 states. The wind can

exhibit many different patterns that vary over time and

space. During the fall and spring seasons, it is common to 

observe more wind than during other months. Wind patterns

also may not match load patterns, limiting wind’s capacity

contribution to the grid. Wind shear, the difference in wind

velocity at different elevations from the ground, is

pronounced in many parts of the United States. Because the 

GIS database contains wind speed at 50 m from the ground, 

this creates a mismatch with currently available wind

turbines with a hub height of 80m. In the next few years it is

likely that hub heights will increase further, to 100 m (as is

becoming common in Europe) or even higher. This implies

that the estimates of the wind resource shown by the map 

likely understates the wind resource, perhaps significantly,

resulting in supply curves that also understate the quantity

of wind at various prices. 

Figure 1 shows a low-resolution version of the U.S. wind

resource map3

. Many states have higher quality maps, and 

those were used for this analysis. As can be seen in the map,

the upper Great Plains states and the West generally have a

significant wind resource, and other areas of the country

also have good wind. Although the map shows offshore 

resources, only onshore was considered in the supply curve 

analysis because the offshore technology and costs have not 

matured sufficiently. Alaska and Hawaii were not included

in the analysis. 

Figure 1. Wind resource map for the United States

4. NEAR-TERM DEVELOPMENT 

As part of the CDEAC effort for the WGA, a set of wind

supply curves was developed to estimate the potential for 

wind in the WGA footprint and to analyze the impact of

available transmission on supply and cost.4

 In addition to

the supply curve development for WGA, many regional and 

sub-regional transmission plans were used to get a better 

idea of potential wind development through 2015. Within

the WGA footprint, studies have been performed that cover 

the Western Electricity Coordinating Council (WECC) by

Seams Steering Group of the Western Interconnection

2
(SSG-WI), Rocky Mountain Area Transmission Study

(RMATS), and a project underway in the Northwest 

(Northwest Transmission Assessment Committee, NTAC).

For states outside the WECC, the Midwest Independent 

System Operator (MISO) considered wind development in

the MISO Transmission Expansion Plan (MTEP) in 20035

and has studied other scenarios in more recent MTEP 

analyses6

. Additional work in the West has evaluated new

innovative transmission tariffs that provide long-term

transmission access on a conditional firm or non-firm basis.

The WTF concluded that such transmission tariffs could

speed the development of wind and increase the efficiency

of the transmission system. Three scenarios for 2015 were 

developed: (1) assuming little if any transmission tariff

development, (2) a mid-range of wind development

according to the various transmission studies, and (3) a 

high-end wind development scenario. Figure 2 illustrates the 

range of these scenarios, and Figure 3 shows the 

approximate locations of this wind development in the 

West. 

0

10,000

20,000

30,000

40,000

50,000

60,000

Low Med High

WTF Scenario

Potential Wind Development

(M

W)

Figure 2. WTF wind development scenarios

Figure 3. Wind scenario locations for WTF highdevelopment scenario, 2015

5. SUPPLY CURVE DEVELOPMENT 

Supply curves were developed based on the GIS data

represented in Figure 1. Not all land can be used for wind

plant development, even though there may be a viable 

resource. Exclusions for urban areas, national parks and 

preserves, wilderness areas, and water were applied to the 

GIS data. The analysis converts wind speed to potential 

wind power using modern wind turbine characteristics and 

an average shear factor to account for the difference 

between the mapped wind speed and the assumed turbine 

hub height. An area with a high average wind speed would 

have a lower energy cost than an area with a low wind

speed. It is likely that the mapping database misses some

high-quality wind locations, which would result in more 

supply of wind at a lower cost than what is shown in this

paper. Table 1 shows the base data for the supply curve 

development. Costs do not include the PTC, which would

reduce the effective cost of energy. 

Table 1: Wind Levelized Cost of Energy and Capacity 

Factor by Wind Power Class 

Wind 

Power 

Class 

Wind 

Speed @ 

50 m

Capacity

Factor 

Nominal 

LCOE 

3 6.4-7.0 30.0 .0744

4 7.0-7.5 33.8 .0659

5 7.5-8.0 39.8 .0537

6 8.0-8.8 43.6 .0490

7 8.8-11.1 49.6 .0431

For this analysis, several sets of supply curves were 

developed for each state and then combined for the entire 

country. Each supply curve is based on an assumption

concerning how much of the existing transmission grid is 

available to transport wind. The first assumption is that no

existing transmission is available, requiring wind to pay to

build all of its own transmission. The subsequent cases

assume that 10%, 20%, 30%, or 40% of the existing grid is

available to transport wind. If the wind generation uses up

all the available transmission capacity, new transmission is

“built” to the nearest load center(s). Because the GIS 

database includes transmission locations and line ratings, it 

was possible to simulate building new transmission to

connect the wind plant to the existing grid. For each load 

center, wind energy as a percent of the total was limited to

20%. Once this limit was reached, additional transmission

was built to the next nearby load center at a cost of

$1,000/MW-mile. 

Figure 4 shows the supply curves for the entire United 

States. The supply curve on the far left is the case of no

available transmission for wind, and the supply curve on the 

3
far right is the wind supply assuming 40% of existing

transmission is available for wind. 

Impact of TransmissionAvailability on WindSupply

0

10

20

30

40

50

60

70

80

0 200,000 400,000 600,000 800,000

Wind Capacity (MW)

Cost $/MWh

0% Trans. Avail.

10%

20%

30%

40%

Figure 4. Supply curves with alternative assumptions for 

the percentage of existing transmission that is available 

to transport wind to load

Because some of the detail is difficult to discern in the 

graph, Figure 5 shows an inverted supply curve as discrete 

points. To further expand the view over the lower wind

costs, Figure 6 zooms in further. 

Impact of Transmission Availability on Wind Supply

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

45 50 55 60 65 70

Cost of Wind ($/MWh)

Wind Capacity (MW)

0% Trans. Avail.

10%

20%

30%

40%

Figure 5. Impact of transmission on wind supply

Impact of Transmission Availability on Wind Supply

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

45 50 55

Cost of Wind ($/MWh)

Wind Capacity (MW)

0% Trans. Avail.

10%

20%

30%

40%

Figure 6. Zoom of Figure 5 at lower wind cost of energy 

6. MARKET SIMULATIONS

The U.S. Department of Energy Wind Program has

developed a set of cost goals for technology development.

For wind Class 6, the levelized cost of energy targets from

2010 to 2050 are shown in Figure 7. The cost of wind

energy in lower wind speed locations is also expected to 

improve, and the Wind Program is developing low wind

speed technology that is expected to allow the use of less

energetic sites that are closer to transmission and load 

centers. Because the supply curves shown above are based 

on current technology and wind speed at 50 meters, these 

supply curves underestimate the potential for wind. 

Class 6 COE

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

2010 2015 2020 2025 2030 2035 2040 2045 2050

2002 $/MWh

AEO2005

Onshore Base

Onshore Program

Figure 7. Projected wind energy cost decline from 2010 

to 2050 for Class 6 wind sites

A high-penetration market simulation was developed based 

on the Wind Deployment System model, currently under 

development at NREL.

7 8 This model represents the U.S. 

power grid by control area (balancing authority), uses

projected wind costs shown in Figure 7, and GIS 

representations of wind and transmission. The model 

contains generation from all generation technologies along

with price forecasts, and competes resources based on cost

to determine the least-cost national generation portfolio that 

4
will successfully meet demand and energy requirements. A

key assumption used for this scenario is that the PTC is 

renewed until 2010, followed by a smooth phase-out until 

2030. The results of the simulation are shown in Figure 8. 

Wind Market Penetration

0

100

200

300

400

500

600

2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

Year

Wind Capacity (GW)

Year Capacity (GW)

2015 280

2030 507

Figure 8. Results of wind market simulation

To assess the carbon reduction potential, the wind capacity

from the market simulation was converted to annual energy.

Because different regions of the country have significant 

differences in generation fuel mixes, quantifying the carbon

reduction potential from wind is not straightforward. Under 

the assumption that wind displaces only coal, we used the 

rate of 260 metric tons of carbon per GWh to estimate offset

carbon. 

Figure 9 shows the relationship between wind energy

generation and carbon reduction using two carbon

displacement rates: 260 metric tons per GWh and 130 

metric tons per GWh. This latter rate may be more reflective 

of fuel displacement that includes fuels other than just coal, 

although a more rigorous analysis is required to obtain a 

more accurate estimate of carbon reduction.

Annual Avoided Carbon from Wind

0.0

100.0

200.0

300.0

400.0

500.0

600.0

2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

Year

Metric Tons of Carbon (millions)

Upper Lower

Figure 9. Annual avoided carbon calculated on coal-only

displacement (260 metric tons/GWh) and at 130 metric

tons/GWh 

Cumulative carbon offset is represented in Figure 10 for the 

two carbon offset rates discussed above. 

Cumulative Avoided Carbon from Wind

0.0

500.0

1000.0

1500.0

2000.0

2500.0

3000.0

3500.0

4000.0

4500.0

2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

Year

Metric Tons of Carbon (millions)

Upper Lower

Figure 10. Range of cumulative carbon reduction 

estimates through 2030 

7. CONCLUSIONS 

• The potential for wind to supply a significant quantity

of energy in the United States is enormous. 

• This study is parametric and shows the importance of

transmission availability on wind supply; however, 

detailed transmission studies with appropriate data sets 

are required to more fully assess this issue for specific 

deployment options. 

• The availability of transmission capacity helps largescale deployment by reducing the cost of delivered 

wind energy. 

• Since wind transmission does not require firm

transmission rights, alternative transmission tariffs can

make more effective transmission available for wind

delivery.

• Aside from the supply curves, there is additional 

empirical evidence of a potential large-scale expansion

of wind. This evidence comes from utility IRPs, state 

RPS requirements, and large-scale transmission studies 

in the West and the Midwest. 

• Continuing declines in the cost of wind generation will

increase wind development. The recent cost increases

may be temporary but may also signal an upward trend 

in wind turbine prices. 

• GIS data used for this supply curve analysis may

significantly underestimate the supply of wind in the 

West. 

• Carbon reduction potential of wind is significant but 

will depend on the specific fuel mix displaced by wind. 

5
8. ACKNOWLEDGMENTS 

Thanks to Donna Heimiller and George Scott, National 

Renewable Energy Laboratory, for their excellent support of

the supply curve development, and to Nate Blair, Maureen

Hand, Alan Laxson, and Walter Short for the use of their 

market analysis results and WinDS. 

The Wind Task Force report of the CDEAC can be found at 

http://www.westgov.org/wga/initiatives/cdeac/Wind-full.pdf

Information on the WinDS model can be found online at

http://www.nrel.gov/analysis/winds

9. REFERENCES 

1

http://www.awea.org/news/US_Wind_Industry_Ends_Most

_Productive_Year_012406.html

2 Bolinger, Mark and Ryan Wiser, Balancing Cost and 

Risk: The Treatment of Renewable Energy in Western 

Utility Resource Plans, Lawrence Berkeley National 

Laboratory, 2005. 

http://eetd.lbl.gov/EA/EMP/reports/58450.pdf 3

 Wind Powering America has developed wind resource

maps for much of the United States. These maps are 

available at 

http://www.eere.energy.gov/windandhydro/windpoweringa

merica/wind_maps.asp 4

 Wind Task Force Report, March 2006. 

http://www.westgov.org/wga/initiatives/cdeac/Windfull.pdf. 5

 Midwest ISO, Transmission Expansion Plan 2003 (MTEP03), June 19, 2003. 

http://www.midwestiso.org/plan_inter/documents/expansion

_planning/MTEP%202002-

2007%20Board%20Approved%20061903.pdf 6

 MTEP 05, Page 136.

http://www.midwestiso.org/publish/Document/3e2d0_106c6

0936d4_-

751a0a48324a/MTEP05_Report_061605.pdf?action=downl

oad&_property=Attachment 7

 Short, W.; Blair, N.; Heimiller, D.; Singh, V. (2003). 

Modeling the Long-Term Market Penetration of Wind in the 

United States. 15 pp.; NREL Report No. CP-620-34469. 

http://www.nrel.gov/docs/fy03osti/34469.pdf 8

 Laxson, A.; M. Hand; N. Blair, High Wind Penetration 

Impact on U.S. Wind Manufacturing Capacity and Critical 

Resources. Working paper, National Renewable Energy

Laboratory. 2006. 

6
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Tackling Climate Change in the United States: The Potential 

Contribution from Wind Power; Preprint 

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14. ABSTRACT (Maximum 200 Words)

To support the Western Governors’ Association’s Clean and Diversified Energy Advisory Committee, a Wind Task 

Force (WTF) was convened to assess the feasibility of achieving 30,000 MW of clean and diversified energy in the 

West by 2015. The WTF examined the near-term potential of wind energy in the West, using a combination of 

technical supply curves based on GIS data, and information from recent utility and transmission studies. The study 

results indicate a very large potential for wind generation in the West. Supplementing the GIS analysis is information 

extracted from utility integrated resource plans that include wind additions in the near term, along with estimates of 

wind development that will be induced by state renewable portfolio standards. However, these results depend on 

federal and state policy support and transmission access. 

In this paper, we briefly discuss the results of the WTF report and develop expanded wind supply curves for the 

entire United States. Wind potential was estimated using a GIS database that contains data on average annual wind 

speed and transmission lines. We also develop estimates of carbon reduction that would result from large-scale 

deployment of wind and find that 2,000-4,000 million metric tons of carbon could be avoided by 2030. 

15. SUBJECT TERMS

wind energy; Wind Task Force; Western Governors' Association; capacity; PTC; transmission; transmission studies 

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