Technical Report

NREL/TP-6A2-47179

December 2009

Colorado's Prospects for 

Interstate Commerce in 

Renewable Power

Prepared for the Colorado Governor’s 

Energy Office, Renewable Energy 

Development Infrastructure (REDI)

David J. Hurlbut
National Renewable Energy Laboratory

1617 Cole Boulevard, Golden, Colorado 80401-3393

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-AC36-08-GO28308

Technical Report

NREL/TP-6A2-47179

December 2009

Colorado's Prospects for 

Interstate Commerce in 

Renewable Power

Prepared for the Colorado Governor’s 

Energy Office, Renewable Energy 

Development Infrastructure (REDI)

David J. Hurlbut

Prepared under Task No. WTG8.1000
NOTICE

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iii

Foreword

This report was prepared by the National Renewable Energy Laboratory (NREL) under a 

contract with the Colorado Governor’s Energy Office (GEO). It supplements GEO’s 

broader examination of transmission issues contained in its Renewable Energy 

Development Infrastructure (REDI) report. 

During the preparation of the REDI report and its predecessor report—produced in 2007 

by the Renewable Resource Generation Development Areas Task Force as directed by 

the Colorado State Assembly in Senate Bill 07-91—commenters frequently noted the fact 

that Colorado has more renewable resources than it needs for its own consumption. Many 

of these commenters concluded that such surplus could be sold to other states, thereby 

increasing the state’s revenues from interstate commerce in energy. The purpose of this 

report is to provide analytical background for further discussion about interstate 

commerce in renewable energy development, drawing on current technical analysis being 

conducted by NREL and others. 

The findings presented here do not constitute policy recommendations. Rather, they are 

intended to clarify the salient issues that would arise if Colorado policymakers choose to 

include interstate commerce in renewable energy development as part of the state’s longterm goals for transmission investment.
iv

Acknowledgments

As of this writing, several major studies are under way examining the technical 

challenges of large-scale regional renewable energy deployment. The author is grateful 

for the assistance provided by those involved in these efforts, particularly the Western 

Governors’ Association (WGA) and WestConnect. Background research for the WGA’s 

Western Renewable Energy Zone Initiative was crucial to the analysis presented in this 

report, as was data from the Western Wind and Solar Integration Study (WWSIS) being 

conducted by WestConnect and NREL. The consulting firm Black & Veatch conducted 

much of the analysis for WGA. NREL’s Debra Lew and Michael Milligan provided 

crucial guidance on WWSIS, particularly with regard to navigating its massive data set 

and to understanding the study’s preliminary findings. If this report errs in its use of 

information from either study, the responsibility lies with the author of this report and not 

with those who provided guidance.

Eric Lantz of NREL also provided important background on the renewable energy value 

chain and its implications for Colorado. Thanks also go to the REDI Advisory Committee 

for comments on early drafts of this study; and to Lori Bird, Matthew Brown, Jeff Hein,

and Morey Wolfson for their review of the overall report.

Finally, the author gratefully acknowledges both the financial and intellectual support 

provided by the U.S. Department of Energy’s Office of Electricity Delivery and Energy 

Reliability.
v 

List of Acronyms 

AC alternating current 

CAISO California Independent System Operator 

DC direct current 

DNI direct normal insolation 

GDA 

GEO 

generation development area 

Governor’s Energy Office (Colorado) 

NERC North American Electric Reliability Corporation 

NREL 

R&D 

National Renewable Energy Laboratory 

research and development 

REDI 

REZ 

Renewable Energy Development Infrastructure 

Renewable Energy Zone 

RMPA Rocky Mountain Power Area 

RPS renewable portfolio standard 

WEEC Western Electric Coordinating Council 

WGA Western Governors’ Association 

WREZ Western Renewable Energy Zone 

WWSIS Western Wind and Solar Integration Study 

 
vi

Table of Contents

Foreword ....................................................................................................................................... iii

Acknowledgments........................................................................................................................ iv

Table of Contents ......................................................................................................................... vi

List of Maps.................................................................................................................................. vii

List of Figures.............................................................................................................................. vii

List of Tables................................................................................................................................ vii

Executive Summary ...................................................................................................................... 1

Introduction.................................................................................................................................... 3

The Relevant Market...................................................................................................................... 5

Demand in the WECC region ..................................................................................................... 5

Competitive Position of Colorado’s Renewable Resources ..................................................... 8

Wind.......................................................................................................................................... 10

Solar.......................................................................................................................................... 11

Regional Management of Renewable Energy Resources ....................................................... 14

Real-time Variation in Wind Output......................................................................................... 17

Matching Production to Load throughout the Day ................................................................... 20

Conclusion ................................................................................................................................... 26
vii

List of Maps

Map 1: Region Served by the Western Electric Coordinating Council (WECC)............... 6

Map 2: Potential Regional Hubs for Renewable Energy in the Western U.S..................... 9

Map 3: Thirty-seven Balancing Authorities in the Western Interconnection................... 15

Map 4: Six Sample Sites Used in Geographic Diversity Analysis................................... 17

List of Figures

Figure 1: Retail Electricity Sales Projected for 2025, Portions Covered by RPS Goals.... 6

Figure 2: State Wind Resources that Passed WREZ Screening, by Class........................ 11

Figure 3: State Solar Resources that Passed WREZ Screening........................................ 12

Figure 4: Diurnal Load Profiles for PSCo, Averaged by Month ...................................... 22

Figure 5: Diurnal Load Profiles for California ISO, Averaged by Month........................ 23

List of Tables

Table 1: Geographic Diversity and Variation in Output................................................... 18

Table 2: Implications of Extrema Differences in Diurnal Net Load ................................ 21

Table 3: Estimated Wind Power Deliveries to Destination Markets................................ 21

Table 4: Diurnal Extrema Differences for PSCo, 2005 .................................................... 22

Table 5: Diurnal Extrema Differences for California ISO, 2005...................................... 24
1

Executive Summary

Colorado has more renewable energy potential than it is ever likely to need for its own instate electricity consumption. Such abundance may suggest an opportunity for the state to 

sell renewable power elsewhere, but Colorado faces considerable competition from other 

western states that may have better resources and easier access to key markets on the 

West Coast.

This report examines factors that will be important to the development of interstate 

commerce for electricity generated from renewable resources. It examines market 

fundamentals in a regional context, and then looks at the implications for Colorado.

• Colorado’s relevant market for renewable power is the Western Interconnection, 

which includes all states west of the Great Plains. 

The relevant market

• The greatest demand for renewable power within the Western Interconnection is 

on the West Coast, particularly California. 

• Wind resources in Colorado’s Eastern Plains constitute the state’s most 

economically competitive, utility-scale renewable power (based on cost per unit 

of output), yet there is no viable transmission corridor by which these resources 

can reach West Coast demand centers. In-state transmission constraints limit the 

flow of power from the Eastern Plains to the Western Slope, and the two major 

high-voltage paths out of the state westward have little spare transfer capacity. 

• States adjacent to Colorado do not constitute a large source of demand. 

Consequently, economies of scale may be difficult to achieve for projects in 

Colorado that are intended to serve load in adjacent states.

• Wyoming has significant amounts of wind resource potential that is rated higher 

than Colorado’s wind potential (based on cost per unit of output). In addition, 

Wyoming has better transmission access to West Coast demand centers. 

Competing resources

• New Mexico has solar resource potential with higher direct normal insolation 

factors than are found in Colorado, while New Mexico’s wind potential is 

comparable to Colorado’s.

• Lower-rated wind resources in California, Washington, and Oregon enjoy a 

competitive advantage because they are closer to that region’s largest demand 

centers. Lower transmission costs reduce the delivered cost per unit of output, 

compensating for generally lower wind speeds. 
2

• Managing Colorado and Wyoming wind resources together may reduce costs and 

make both more competitive.

Cost impact of regional operations

• Combining geographically diverse wind and solar resources into a single portfolio 

tends to reduce hourly and sub-hourly variations in real-time output. This would 

result in a more consistent level of output over a longer time frame, which could 

reduce the cost of wind integration.

• A larger and more geographically diverse portfolio of wind and solar resources 

requires less use of reserves from conventional generating units. Using less 

reserved conventional power can reduce the costs that a utility would need to 

recover in its rates, and could increase the interstate competitiveness of the 

portfolio as a whole.

• Wyoming wind power would tend to mitigate high wholesale electricity prices in 

California more so than Colorado wind power would, due to the hourly 

production profiles of wind power throughout the year and especially during the 

summer.

• Jointly managing wind resources from Colorado and Wyoming would largely 

preserve Wyoming wind power’s downward pressure on California wholesale 

power prices. 

The report concludes that a successful interstate commerce strategy for Colorado wind 

and solar power may need to include multi-state collaboration on the planning, approval, 

dispatch and operation of renewable resources and the transmission system. Colorado 

would have a dual stake in the success of such a regional effort: greater value-added for 

its own renewable energy production, and greater in-state economic development because 

of Colorado’s position as a regional manufacturing center for renewable energy 

technologies.
3

Introduction

Interstate commerce in energy has fueled local economic booms for states rich in oil, 

natural gas, and coal throughout U.S. history. Similar opportunities are now arising for 

wind, solar, and other renewable energy resources as the New Energy Economy takes on 

national proportions. The economic value of the nation’s least-cost, zero-carbon 

alternatives will almost certainly increase with the promulgation of public policies to 

reduce carbon emissions.

Colorado has abundant renewable energy resources for generating electricity—much 

more potential for wind power and solar power than it needs for its own use. The best 

potential was documented and mapped in “Connecting Colorado’s Renewable Resources 

to the Markets,” a study authorized by the Colorado State Assembly under Senate Bill 

07-091. Theoretically, the state’s apparent surplus of renewable energy resources might 

suggest a new opportunity for state energy revenues. While it has policies in place to 

increase its internal use of renewable power, Colorado’s activity with respect to interstate 

commerce has emphasized expanding the state’s manufacturing base, not the sales of its 

renewable power to other states.

The ability to be a competitive player in a regional renewable energy market depends on 

more than just having spare resources, however. This study critically examines the factors 

that affect Colorado’s position as a potential interstate supplier of renewable energy. The 

first section provides an overview of the likely geographic market, which is essentially 

defined by the transmission infrastructure along which power generated in Colorado can 

reach end users. Next, the paper examines the distribution and quality of wind and solar 

power throughout the region. This discussion will draw from recently completed regional 

analysis conducted for the Western Governors’ Association (WGA). The third section 

discusses issues affecting the grid’s ability to integrate larger amounts of wind and solar 

power. These technical issues are obstacles under existing grid management practices, 

but at the same time they point the way to changes that could open up the market 

considerably. 

Robust interstate commerce presumes a regional market with willing buyers and 

sufficient transmission infrastructure. Colorado would not be the only player in this 

market. Other states may want a piece of the regional action, and some may be tough 

competitors. The greatest potential demand is on the West Coast, and some states have a 

competitive advantage over Colorado as potential suppliers to that market. Wyoming

(which is already sending wind power to the West Coast) has world-class wind resources 

that tend to be more productive than Colorado’s wind resources, and that also tend to 

follow hourly and daily load in a way that would provide more stability for wholesale 

power prices in California. Utility-scale solar resources in Arizona and Nevada are closer 

to demand on the Pacific Coast, and they are more productive and more consistent. New 

Mexico’s wind resources are comparable to Colorado’s, and its solar resource areas 

receive more sunshine and are closer to market.
4

A regional market, therefore, would provide no guarantee that a load-serving utility in 

any other state would want to buy Colorado renewable power if it were available. 

Colorado’s best prospects for selling renewable power will depend on interstate 

partnerships and on eliminating outdated practices for operating the power grid—

practices that prevent a regional market from operating efficiently. In any case, however, 

Colorado’s head start as a manufacturing hub for renewable energy leaves it well 

positioned for significant job growth in the equipment supply chain, regardless of how a 

regional market may develop.

It is important to note that this analysis sets aside the question of “unbundling” renewable 

energy credits (RECs). Unbundling means that RECs and the physical energy they 

represent may be traded separately, as long as the latter is treated as generic electricity 

without any particular environmental attributes. In theory, a California utility could buy a 

Colorado wind farm’s unbundled RECs and apply them towards its state-mandated 

renewable energy requirement even though the power generated by the Colorado wind 

farm may not actually flow to California.1 Several state and regional authorities are 

looking at the pros and cons of unbundled RECs; this analysis makes no attempt to 

resolve those issues, as many of them are tangential to the questions at hand. Instead, this 

analysis presumes a physical flow of power from generation to demand, consistent with 

current transmission planning practice. This presumption enables a more in-depth 

analysis of Colorado’s competitive position, as it includes value-added elements that 

would not be present in an unbundled REC scenario.2

 1 Consequently, the Colorado wind farm’s production would not count toward the Colorado state 

requirement, although the additional electricity would have to be accommodated locally.

New rules allowing greater use of 

unbundled RECs would require re-examining the conclusions from this analysis.

2 Two examples are a generator’s capacity value, and the effect on wholesale prices. Both of these factors, 

which this analysis addresses in detail, depend on the real-time match between the generator’s output level 

and the level of demand.
5

The Relevant Market

The configuration of the national electric grid dictates that the western United States is 

Colorado’s main economic trading area for renewable power. Map 1 shows the region 

covered by the Western Electric Coordinating Council (WECC), the transmission 

reliability organization responsible for the synchronous grid to which Colorado is 

connected. Colorado already sends power to and takes power from other WECC states 

during the course of normal operations.

Very little power flows from WECC to the eastern grid because of technical differences 

in how the eastern and western grids operate. Consequently, bulk power movement from 

Colorado to Kansas would require a significant interstate investment in direct-current 

(DC) transmission lines that would both carry the power to eastern demand centers and 

enable it to mesh synchronously with the eastern grid. An alternative is to add tie stations 

at the interconnection seam near the Colorado-Kansas border that convert the alternating 

current (AC) from Colorado into DC, and then back to an AC current that is synchronized 

with the eastern grid. A tie would require sufficient transmission capability in western 

Kansas to move the power eastward through the local network. The network is currently 

transmission-limited, although current expansion plans would enable the development of 

more wind power in western Kansas.

Perhaps the greatest challenge, however, is that Colorado wind power may not be 

competitive economically. The eastern grid’s own indigenous wind resources in the 

Dakotas, Kansas, and the Texas-Oklahoma Panhandle area are at least as productive as

those in eastern Colorado. Thus, while DC options are conceivable and would 

theoretically expand Colorado’s possible interstate commerce scenarios, they do not at

this time represent the most likely near-term economic opportunities and therefore will 

not be addressed in depth.

Demand in the WECC region

Two factors currently affect a state’s likely demand for renewable power: the size of 

total retail electricity sales, and whether the state has a renewable portfolio standard 

(RPS) in place. The economic influence of an RPS is not limited to the quantity of 

renewable power that is mandated. Of even greater importance is what an RPS signals to 

renewable energy developers and load-serving utilities: there will be a demand for 

renewable power inside these markets that is firm and certain. By contrast, a state with no 

RPS is an economically soft and highly uncertain source of demand. 

New carbon reduction policies may stimulate even more demand in the near future, as 

may a future federal RPS. Assessing the shape and impact of these potential future 

policies is not the purpose of this analysis, however, so here they are set aside. Demand 

projections used in this analysis rely exclusively on state RPS policies as they exist in 

2009. This analysis also sets aside any existing RPS eligibility requirement that may 

favor in-state resources—a simplifying assumption that is necessary if the aim is to assess 

the possible benefits of interstate commerce.
6

Map 1: Region Served by the Western Electric Coordinating Council (WECC)

Shading indicates North American Electric Reliability Corporation (NERC) reliability regions.

Figure 1: Retail Electricity Sales Projected for 2025, and Portions Covered by RPS Goals

Note: Changes in the rate of growth for electricity demand will change projected RPS requirements. 

Projections assume a simple 2% annual growth rate. State sales are allocated among provider categories 

(investor-owned utilities, municipally owned utilities, and rural electric cooperatives) based on distribution of 

2007 retail sales. Sector-specific RPS goals for 2025 that were in effect as of 2009 are applied to each 

provider category. For a description of RPS goals by provider category, see Database of State Incentives for 

Renewables and Efficiency, at http://www.dsireusa.org/.

Source: Energy Information Administration (EIA), “Retail Sales of Electricity by State by Sector by Type of 

Provider” (Form EIA-861 database), http://www.eia.doe.gov/cneaf/electricity/epa/sales_state.xls. 

0 100,000 200,000 300,000 400,000

Montana

Idaho

Nevada

Oregon

Arizona

Washington

California

Wyoming

New Mexico

Utah

Colorado

GWh per year

Projected sales not covered by an RPS

Projected sales covered by an RPS
7

California has by far the largest demand for renewable power in the West. As Figure 1

illustrates, California’s total electricity demand is significantly higher than any other 

western state. In addition, California has the region’s most ambitious RPS requirement − 

33% of retail sales by 2020.3

The renewable energy goals in place as of 2009 are equivalent to approximately 28% of

the WECC region’s total projected demand for 2025. Assuming historical load growth, 

this amounts to about 188,000 GWh of generation from new renewable resources 

annually. Three-fourths of that demand will be in California, Washington, and Oregon, 

assuming no significant change in current trends or policies.

Washington, the state with the second-largest demand, has 

an RPS requirement of 15% by 2020. 

The three states that border Colorado in the WECC region—Utah, New Mexico, and 

Wyoming—are each much smaller than Colorado in terms of total electricity demand. In 

addition, Wyoming has no renewable portfolio standard and therefore no minimum 

demand level for renewable power. Utah has a non-binding renewable energy goal. 

Fanning outward from Colorado, the overall demand for renewable power may be 

summarized as follows.

• In-state. Colorado’s home market accounts for about 8% of total retail electricity 

sales in the WECC region. The state's 2020 RPS requirement—20% for investorowned utilities and 10% for rural electric associations and large city-owned 

utilities—establishes a firm demand for renewable power in Colorado, but that 

required amount constitutes only 6% of the region’s RPS-related demand 

projected for 2025. 

• Surrounding states. Utah, New Mexico, and Wyoming together account for 10% 

of WECC retail sales—not much larger than Colorado’s own internal demand. 

However, the market for renewable power in this surrounding area is less firm 

than within Colorado, because only New Mexico has an RPS requirement. 

Together, the three surrounding states account for only 6% of the projected RPSrelated demand for 2025.

• West Coast. California, Washington, and Oregon account for about 54% of the 

projected electricity demand in the WECC region for 2025; they also account for 

three-fourths of the region’s projected demand for renewable power. California is 

the largest demand center, where the projected need for renewable power is 59% 

of the region’s projected demand. Like Colorado, all three of these states have 

RPS requirements in place, as do Arizona and Nevada.

Consequently, the largest potential demand for Colorado renewable power outside the 

state is on the West Coast. Moreover, the West Coast’s already-large share of overall 

electricity demand is further weighted by the fact that all of these states have RPS 

requirements. 

 3 California’s 33% goal is currently effected by an executive order from the governor. The statutory goal is 

20%. See Database of State Incentives for Renewables and Efficiency, www.dsireusa.org.
8

To reach this relatively robust market, however, renewable power from Colorado would 

have to cross an area where demand for renewable energy is relatively small. While 

Colorado's surrounding states may contain niche markets for renewable power, those 

state's local resources would most likely enjoy a comparative advantage in their home 

markets. Because total demand in these neighboring markets would be small, a Colorado 

project with generation and transmission sized for these markets alone probably would 

not be large enough to achieve economies of scale.

Competitive Position of Colorado’s Renewable Resources

Whether Colorado resources will be competitive on the West Coast will depend primarily 

on quantity and cost relative to other alternatives. This section examines both with 

respect to wind and solar potential, the two resources most easily developed in 

concentrations at utility scale in Colorado.

Concurrent with the preparation of the REDI report, the WGA conducted an assessment 

of renewable energy potential throughout the Western Interconnection. The objective of 

the Western Renewable Energy Zone (WREZ) Initiative was to “identify Renewable 

Energy Zones (REZ) in the Western Interconnection based on developable potential, 

development timeframes, common transmission needs, and cost of development.”4

This section draws on the detailed assessments done in the WREZ initiative to examine 

the competitiveness of Colorado’s best resources, both in terms of quantity and quality. 

The resources selected for comparison do not represent the entirety of the potential that 

exists in each state, only the amounts that passed various stages of WREZ screening for 

the anticipated purpose of large-scale, multi-state transmission.

Part 

of the WREZ effort was to identify the best renewable resources in each state, and from 

among those screened areas identify those with the greatest economic potential to meet 

regional demand for renewable power.

Map 2 shows the geographic distribution of renewable energy resources identified in the 

WREZ initiative as being competitive regionally. Blue areas indicate the region’s best 

wind resources based on the most recent validated data from NREL, with darker shades 

indicating the highest-class wind potential. Areas shaded orange to dark red indicate solar 

potential. In all cases, areas have been excluded if they are unavailable for development 

by law or by policy (e.g., national parks).

 4 The outcomes of the WREZ initiative are the product of stakeholder input and technical analysis 

conducted for the WGA by NREL and the Lawrence Berkeley National Laboratory, with assistance from 

the consulting firm Black & Veatch. Final products were recommended by a technical committee 

comprising industry experts and stakeholders, and reviewed and approved by a steering committee 

comprising governors’ designees and other officials from states throughout the West. In June 2009, the 

WGA endorsed the report on the first phase of the initiative, including the map shown in Map 2. WGA, 

“Western Renewable Energy Zones Phase 1 Report,” June 16, 2009 (“WREZ Phase 1”) (available on-line 

at http://www.westgov.org).
9

The results shown in Map 2 account for some reductions based on sensitive habitat areas. 

The adjustments vary from state to state, as determined by each state for the WGA 

analysis. There are currently no region-wide criteria for categorizing specific habitat 

issues in the context of renewable energy development.

Map 2: Potential Regional Hubs for Renewable Energy in the Western U.S.

Hubs represent concentrations of renewable energy potential in qualified resource areas (QRAs) identified in 

the WREZ stakeholder process. Renewable resources not part of a QRA are presumed to be available for 

in-state demand rather than for interstate commerce. Source: WREZ Phase 1.

The regional hubs represent approximately 577,000 GWh of generation from top-quality 

renewable energy resources annually. This includes about 123,000 GWh from areas in 

Canada and Mexico that are on the WECC system. The total generation potential in these 

regional zones is about three times what will be required under these states’ current RPS 

programs by 2025.

Consequently, the pool of potential suppliers is likely to be very competitive if a regional 

market for utility-scale renewable energy develops in the West. A large part of any state’s 

renewable energy needs will likely be met by in-state resources not represented in a 

WREZ hub, therefore the demand pool for regional renewable resources (power 

delivered from one state to another via long-distance transmission) will be smaller than 

the overall projected demand of 188,000 GWh. Transmission to support this regional 

market would be selective and would not be built everywhere, and if no regional high-
10

voltage corridor connected Colorado to the West Coast, then Colorado would not be a 

player. 

Expectations about the delivered cost of wind power and solar power would play 

significantly into criteria for selecting regional transmission corridors. The quality of an 

area’s native climate with respect to wind and sunshine determine the delivered cost of 

wind or solar power from that area. The next sections examine Colorado’s comparative 

position with regard to these two resources.

Wind

The Colorado wind resources that passed WREZ screening are largely the same as the 

wind generation development areas (GDAs) identified in the SB 91 report. Unlike that

report, however, WREZ capacity estimates for each zone included a 25% “developability 

factor.” This adjustment (applied uniformly to wind resources in each state) represents 

the amount of capacity that is likely to be developed in a zone, and is therefore a 

reasonable representation of the amount of transmission that may be needed. In other 

words, it was assumed that every 400 MW of technical potential for wind power would 

be competing for 100 MW of transmission access. This is the main reason that the 16 

GW of wind potential that WREZ estimated for Colorado was a fraction of the 96 GW 

estimated by SB 91.5

WREZ also applied different wind class thresholds in each state. For Colorado and New 

Mexico, only class 4 wind areas or better were counted (as was the case for Colorado in 

the SB 91 report). In Wyoming, however, the amount of class 5 and better wind resources 

was so great that WREZ stakeholders judged the state’s class 4 resources to be

economically uninteresting from the standpoint of a regional market. Therefore, class 4 

wind areas were not included in the regional capacity estimates for Wyoming.

 5 In addition, Wind GDAs 4 and 7 did not pass the WREZ screening. Wind GDA 1 was part of a zone 

shared by Colorado and Wyoming; as most of this zone was in Wyoming, it is not included in the Colorado 

total.
11

Figure 2: State Wind Resources that Passed WREZ Screening, by Class

*Wind class 4 and below not shown for Wyoming and Montana; wind class 3 and below not shown for 

Colorado and New Mexico. Wind resources outside a renewable energy zone are not included. Source: 

WREZ Phase 1.

Figure 2 shows the wind resources in each state that passed WREZ screens. These totals 

take into account the 25% developability factor, so the technical potential is four times 

the amounts shown in the figure. Figure 2 illustrates that:

• Wyoming has about as much commercially competitive wind power as Colorado, 

but the quality is higher

• New Mexico has almost as much regional-class wind power as Colorado, but has 

more that is class 5 or better.

Thus, while Colorado’s wind potential is large enough to support its own RPS and a 

portion of the requirements on the West Coast, transmission that would take Colorado 

resources either northwest or southwest to that demand would pass through states with 

significant amounts of higher-class wind resources. Wyoming’s advantage stems from its 

world-class wind potential; New Mexico’s slight advantage with respect to wind is 

enhanced by a significant competitive advantage with respect to solar potential, as 

analyzed in the next section. While wind resources on the West Coast tend to be Class 3 

or 4 and of limited quantity; as local resources, they have the cost advantage of being 

closer to demand. 

Solar

The developability factor applied by WREZ to solar resources is 3.5%—much steeper 

than the factor used for wind power, because utility-scale solar plants are more 

concentrated geographically. (Wind turbines need to be far enough apart to ensure that 

downwind turbines suffer no degradation in production; solar collectors generally need to 

be as close as possible to minimize installation cost and maximize thermal efficiency.) 
12

So whereas nearly all of Colorado’s San Luis Valley has the technical potential for highquality solar power development—240 GW in all, as estimated in SB 91—the solar 

developability factor imposes the operational assumption that only 3.5% of that potential 

would actually be developed, with the rest continuing to be farmland or some other 

existing use.

Colorado’s best utility-scale solar potential as estimated by WREZ amounts to about 2.6 

GW. Figure 3 shows the Colorado solar potential estimate alongside those for other 

western states.

Figure 3: State Solar Resources that Passed WREZ Screening

*DNI below 7.25 not shown for Arizona. For all states, solar resources outside a renewable energy zone are 

not included. DNI (direct normal insolation) is the amount of sunlight hitting the ground on an average day, 

expressed as kilowatt-hours per square meter per day. 

Source: WREZ Phase 1.

Unlike wind resources, the West’s best solar resources are located relatively close to 

demand. In fact, the California resources shown n Figure 3 are more than enough for its 

own requirements. Adding the potential in Arizona and Nevada, the near-by solar 

potential available to the combined West Coast markets is relatively rich.

Disparities in quality, quantity, and proximity to market pose significant challenges to the 

ability of Colorado’s solar potential to compete in the West Coast market. The amount of 

premium solar resources—direct normal insolation (DNI) of 7.5 or higher—in Arizona, 

Nevada, and California each are more than the total WREZ-identified solar resources for 
13

Colorado, where nearly all of the solar potential is less than 7.25.6

In short, Colorado wind and solar resources enjoy a home-market advantage for the 

largest renewable energy demand in the eastern portion of the WECC system. The West 

Coast, on the other hand, will fundamentally be a very challenging market for the state. 

Wyoming wind power is generally more productive and therefore less expensive (more 

output per dollar of capital investment) than Colorado wind power. 

New Mexico also has 

solar potential of higher DNI and greater quantity than that normally found in Colorado.

If Colorado aims to compete outside its home market, it will need a policy strategy that 

leverages the state’s regional position so that developers can deliver the greatest value 

from Colorado resources to West Coast customers. One possible strategy is to combine 

grid operations over a larger area that includes Colorado, Wyoming, New Mexico and 

other states. If geographic diversity reduces the cost and increases the value of wind and 

solar power, Colorado could still be a viable player in a regional renewable energy 

market. The next section takes a close look at some of the technical issues that, if 

addressed, could increase Colorado’s competitiveness.

 6 DNI (direct normal insolation) is the amount of sunlight hitting the ground on an average day, expressed 

as kilowatt-hours per square meter per day.
14

Regional Management of Renewable Energy Resources

A 2009 study by the North American Electric Reliability Corporation (NERC) concludes 

that effective, efficient integration of wind and solar resources would require changes in 

the traditional ways that operators manage the grid.7 One of the changes it recommends is 

to consolidate daily operations of small transmission systems into larger balancing 

authority areas. NERC found that a larger pool of generation resources and demand-side 

management capability would make reliability problems easier and less costly to manage. 

These findings agree with the analysis conducted in this study, and they could have 

significant material implications for the regional competitiveness of Colorado’s 

renewable resources.8

A balancing authority area is the geographic unit within which generation and demand 

are kept in balance every moment of the operating day.9 The entire Western 

Interconnection comprises 37 balancing authority areas, as shown on Map 3.

 7 North American Electric Reliability Corp., “Accommodating High Levels of Variable Generation,” April 

2009 [http://www.nerc.com/files/IVGTF_Report_041609.pdf]. 8 The findings would still be applicable in the event that California decides to allow unbundled renewable 

energy credits (RECs) to count toward RPS compliance. “Unbundled” means that RECs issued for 

renewable energy production could be traded as commodities independent of how the corresponding power 

physically flowed on the grid. Greater use of unbundled RECs would reduce the need for interstate 

transmission from Colorado to California, but would increase the amount of renewable power that would 

have to be accommodated in Colorado.

9 The net between generation and load also includes the flow of power to or from neighboring balancing 

authority areas.
15

Map 3: Thirty-seven Balancing Authorities in the Western Interconnection

Source: Western Electricity Coordinating Council (available on-line at http://www.wecc.biz/).
16

Wind and solar resources are by nature variable and uncontrollable. This poses two 

challenges for routine grid operations. 

• Moment-to-moment changes in wind or sunshine and, consequently, the amount of 

instantaneous power produced by the equipment. Random changes in actual wind 

or solar output have to be balanced in real-time with flexible generation resources 

(usually natural gas), so that total system generation matches total system load at 

all times throughout the day. Load itself is variable and largely uncontrollable, 

and system operators rely on flexible reserves to manage the changes. Wind and 

solar generation introduce an additional source of uncontrollable variation. 

• Typical daily production profiles that differ from typical load profiles. Even when 

the real-time variations are averaged into typical daily production profiles, the 

shape of those profiles may require grid operators to change how they schedule 

flexible resources, such as natural gas, a day in advance. 

In theory, geographic diversity should make the first problem easier to manage as the 

amount of wind and solar power on the system becomes large. The farther apart two 

points are, the greater likelihood that random changes happening at the same time at each 

point will cancel each other out. If diversity creates greater predictability, operators 

should also find it easier to schedule flexible resources in the normal day-ahead schedule

so that the renewable resources and the flexible resources, when combined, fit the hourly 

profile of the load forecast.

These challenges, as well as other operational benefits of regional diversity of wind and 

solar power, are among the questions addressed in the Western Wind and Solar 

Integration Study (WWSIS). A partnership between NREL and WestConnect, WWSIS 

uses mesoscale-modeled wind production potential for wind turbines at a hub height of 

100 meters, which is the height of many new wind installations. Site-specific production 

potential is calculated by a computerized model that combines wind turbine technical 

specifications and topographic data with detailed meteorological data for 2004, 2005, and 

2006. The results are estimates of wind speed at a height of 100 meters at 10-minute 

intervals throughout the year. Data for more than 32,000 sites across the WestConnect 

footprint were selected for detailed analysis. 

This report uses six selected data points from the WWSIS study to examine the question 

of diversity between Colorado and Wyoming, because these are the two primary states 

that constitute the Rocky Mountain Power Area (RMPA). Two balancing authority areas 

make up most of RMPA, one operated by Xcel Energy and the other operated by the 

Western Area Power Administration. 

The locations of the sites are shown on Map 4. Site selection was not random, as the goal 

was to select sites indicative of each state’s best wind resources. The Colorado sites are in 

Wind GDAs 4, 6, and 8 identified in the SB 91 report. The selected sites are those with 

the highest capacity factor within the bounds of the GDAs, as estimated by the WWSIS 

mesoscale modeling. A similar selection method was used for the Wyoming sites, using 

the north, east, and central resource hubs identified in the WREZ initiative, selected so as 
17

to avoid sensitive wildlife areas identified by the state. All six sites represent relatively 

high annual capacity factors ranging from 33% to 46%.

Map 4: Six Sample Sites Used in Geographic Diversity Analysis

Real-time Variation in Wind Output

Does managing wind power over a more expansive balancing authority area make 

Colorado wind power more valuable? A key determinant is the potential savings in 

balancing costs if the larger pool of wind resources deviates less from its scheduled 

output. This analysis used the following approach.

1. Using the modeled data for 2005, standardize the estimated 10-minute output

levels of each individual sample site, as well as the same-time sum of output 

combining the sites.

2. Calculate the changes in standardized output over each 10-minute interval, and 

from hour to hour.

3. Compare the average differences to determine whether combining sites results in 

smaller differences.

For context, the measures of average variation (in standard deviations from the mean) 

were converted into an equivalent amount of megawatts, assuming one gigawatt of 

nameplate wind capacity.
18

Table 1: Geographic Diversity and Variation in Output

Sample Site 10-minute variation One-hour variation

σ

MW 

equivalent** σ *

MW 

equivalent**

Colorado sample site 1 0.24 96 0.48 193 

Colorado sample site 2 0.23 75 0.47 153 

Colorado sample site 3 0.24 81 0.48 162 

Simultaneous output 

at three Colorado sites 0.18 45 0.40 102

Wyoming sample site 1 0.19 72 0.38 148 

Wyoming sample site 2 0.20 73 0.48 172 

Wyoming sample site 3 0.18 69 0.38 143 

Simultaneous output 

at three Wyoming sites 0.13 42 0.29 95

Simultaneous output

at all six sample sites 0.12 31 0.28 71

*Standard deviations from mean annual output.

** Converted to megawatt equivalent for one gigawatt of nameplate wind capacity.

Source: Author’s analysis using mesoscale-modeled data from the Western Wind and Solar Integration 

Study (http://www.nrel.gov/wind/integrationdatasets/western/methodology.html). Wyoming sample site 

were Nos. 16338, 19065, and 22193; Colorado sample sites were Nos. 9099, 31139, and 30940. 

Production data for all sites were based on meteorological data for 2005.

Table 1 shows the average for the sites over a typical 10-minute interval and in the span 

of an hour. The changes labeled “σ” (sigma) are statistical standard deviations from the 

mean output for the year; this makes the results comparable for any given amount of 

wind capacity, regardless of whether it is placed entirely at one site or spread equally 

among the group of sites. 

The combined output exhibits smaller 10-minute changes than any of the individual sites.

Moreover, the net change becomes relatively smaller as the analytical footprint becomes 

larger. For each state, the σ values for the combined output at all three sites are lower 

than for any of the individual sites. The reduction in variation was even greater when all 

six sites were examined. In fact, the 10-minute change for the combined sites is less than 

the change at any individual site. 

What this means is that less flexible reserve capacity would be deployed over the course 

of a typical year if 1 GW of wind power were spread out between Colorado and 

Wyoming in a larger balancing authority area, instead of being all in Wyoming or all in 

Colorado. 
19

Precisely estimating the value resulting from less use of flexible reserves is beyond the 

scope of this report, as it would involve detailed simulations of economic dispatch 

system-wide. By applying a number of simplifying assumptions, however, it is possible 

to provide a very rough indication of the relative degree to which the use of flexible 

reserves would be reduced by managing wind resources over a larger and more 

geographically diverse control area. To roughly estimate the value of such savings, the 

study calculated the amount of flexible reserves that would have been needed in 2005 to 

balance wind output on a daily basis, as follows.

1. Assume that a wind farm’s set point (the output at which it would be scheduled to 

operate the next day, based on wind forecasts) is the average of its output 

estimated for that day.

2. Calculate hourly average output, and calculate the reserves that would need to be 

deployed up or down in order to make up the difference between the hourly 

average and the daily set point. (Positive differences would represent updeployments.)

3. Sum the estimated up-deployments for the year (in megawatt-hours), calculate the 

wind farm’s electricity production for the year (also in megawatt-hours), and 

calculate the amount of up-deployment required for each megawatt-hour of 

production.

Using this very rough methodology, a set point based on the same-time output of all six 

sites would require about 120 MWh of up-deployment from flexible resources for one 

gigawatt of nameplate capacity. Applying the same methodology to the three Colorado 

wind sites individually, the up-deployment requirement increases to between 240 MWh 

and 260 MWh. Assuming that the output is typical of a good site, and natural gas prices 

of $7 per mcf, the difference in up-deployment costs would be between $20 million and 

$30 million annually.

The net cost of up-deployments and down deployments together would be smaller than 

the value of up-deployments alone. This is because down-deployments would involve 

over-production at the wind farm, and a corresponding reduction in the output of a 

flexible natural gas generator. Typically, up-deployments involve increasing production 

on units that are more expensive than any of the units running at the time. Downdeployments tend to be the opposite, as they remove the most expensive units running at 

the time. In other words, what may be saved by reducing output by 10 MW would tend to 

be less than the additional cost of increasing output by 10 MW; even if the quantities are 

equal in either direction, the economic value is not. An accurate estimation of the true net 

savings would require modeling the landscape of variable costs at different levels of 

production, which is beyond the scope of this report.

What the foregoing analysis suggests is that management across a larger balancing 

authority area would increase the value—and, therefore, the regional competitiveness—

of wind resources in both Colorado and Wyoming. The additional competitive value is 
20

attributed to reduced operational costs, particularly the use of flexible reserves to balance 

real-time errors from scheduled output levels.

Matching Production to Load throughout the Day

If combining wind resources across a larger area makes the net wind schedule less 

variable and more stable, operators can incorporate the shape of wind power’s hourly 

production profile into the next day’s operating schedule with greater confidence in its 

consistency. This raises another analytical question, however: assuming that wind 

power’s production profile is stable enough for day-ahead scheduling, how does the wind 

profile match the daily load profile?

The diurnal pattern of load or generation is how either one changes during the course of 

an average day. The diurnal load profile is low in the early morning hours and gradually 

increases through the rest of the morning and early afternoon. In Colorado, load tends to 

peak in the late afternoon during the summer, and in the evening during a typical winter 

day.

Operational issues can arise from how the diurnal profile of wind production differs from 

the load profile. If the two patterns are counter-cyclical (i.e., one tends to be up when the 

other tends to be down), then it may reduce the amount of baseload generation needed 

from coal-fired plants, and require more reliance on generation from natural gas units. 

Coal plants are expensive to start up and difficult to adjust once they are operating, and 

for these reasons operators prefer to operate coal-fired units at the same level around the 

clock. Consequently, coal plant generation is often scheduled based on the system’s 

minimum load level. 

When wind production peaks at night, the net effect is to reduce the effective minimum 

load. This, in turn, would reduce the amount of baseload production needed from coal 

plants but would also increase the use of flexible generation from natural gas throughout 

the day. A counter-cyclical pattern between load and wind, therefore, usually reduces 

electricity-related carbon emissions, but it also increases exposure to potentially extreme 

changes in natural gas prices.

The more renewable generation tends to peak during the day, the flatter the combination 

load and renewable generation tends to be. The use of coal baseload may change little, 

while daytime use of natural gas resources would decrease. This pattern provides more 

price stability, but carbon emissions would not fall as much. (Coal produces about twice 

the amount of carbon dioxide that natural gas does per unit of electricity generated.) 

For the purposes of this analysis, net load is the difference between electricity demand 

and the level of wind output, or mathematically,

net load MWt = load MWt – wind MWt,

where t designates the operating hour, and all three quantities are expressed in 

megawatts. The analytical metric used in this analysis is the difference between a diurnal 

profile’s extrema, that is, the difference between the maximum and minimum megawatt
21

levels over the course of a typical operating day. The analysis examines what happens to 

the extrema differences when taking into account wind power that is distributed among 

the six sample sites in Colorado and Wyoming shown on Map 4. Table 2 provides a 

simplified thumbnail sketch of what the changes in the extrema differences mean.

First, the analysis examined Colorado as an energy importer, using 2005 load data for 

PSCo. The scenarios tested were based on 2.5 GW of wind power. This amount of 

capacity would have produced about 20% of PSCo’s annual demand, based on 2005 data 

for load and meteorological conditions. (Colorado’s renewable energy standard calls for 

PSCo to obtain at least 20% of its power from renewable resources by 2020.) More 

precisely, 2.5 GW at the three Colorado sites would have produced 19.6% of PSCo’s 

demand in 2005, while 2.5 GW distributed among all six sites would have produced 

20.8% of the utility’s 2005 demand. 

Table 2: Implications of Extrema Differences in Diurnal Net Load

Consequence: Why: Assumption:

Bigger 

difference

Better for 

reducing carbon 

emissions

Minimum demand is lower, reducing 

the amount of baseload generation 

needed.

Baseload 

generation reduced 

is coal-fired. 

Smaller 

difference

Better for price 

stability

Peak demand is lower, reducing the 

amount of intermediate and peak 

generation needed.

Intermediate and 

peak generation 

reduced is from 

natural gas. 

Table 3: Estimated Wind Power Deliveries to Destination Markets

To Colorado 

(2.5 GW of wind power to PSCo)

To California 

(15 GW of wind power to CAISO)

Est. GWh

% of 2005 

demand Est. GWh

% of 2005 

demand

From Colorado 7,843 19.6% 47,061 20.0%

From Wyoming Not estimated* 52,777 22.4%

From both states 8,320 20.8% 49,919 21.2%

*A Wyoming-only scenario is not realistic for Colorado, as nearly all of the wind power already serving 

Colorado customers is from in-state resources.

Figure 4 shows the hypothetical reductions in demand for the Colorado import analysis. 

Each month’s segment along the x-axis shows the typical 24-hour profile for that month, 

calculated as the average load (or net load) at a given hour for each day of that month. 

The two net load profiles differ little during the summer months. Each yields the greatest 

net load reductions during the winter and spring months, although in most cases (but not 
22

all) the two-state distribution of wind power reduces net load more than the Coloradoonly distribution does.

Figure 4: Diurnal Load Profiles for PSCo, Averaged by Month

Net load for PSCo calculated based on 2.5 gigawatts of wind capacity.

Sources: SNL Financial (load data); WWSIS (wind site production estimates).

Table 4 compares the magnitude of the extrema differences. For every month except 

November, the two-state net load profile showed smaller differences between the daily 

high and the daily low than did the Colorado-only profile. In February and March, the 

two-state net load actually reduced the gap between daily high and daily low as compared 

with gross load. 

Table 4: Diurnal Extrema Differences for PSCo, 2005

Difference between average daily 

maximum and minimum load

Magnitude of net load 

difference relative to load-only

LoadonlyNet load 

(CO sites)

Net load 

(CO-WY 

sites)

Net load 

(CO sites)

Net load 

(CO-WY sites)

Jan 1,705 1,973 1,956 16% 15%

Feb 1,595 1,597 1,560 0% -2%

Mar 1,527 1,560 1,413 2% -7%

Apr 1,387 1,593 1,398 15% 1%

May 1,556 1,912 1,719 23% 10%

Jun 2,115 2,524 2,428 19% 15%

Jul 2,843 3,317 3,179 17% 12%

Aug 2,409 2,718 2,563 13% 6%

Sep 2,035 2,483 2,215 22% 9%

Oct 1,658 1,774 1,708 7% 3%

Dec 1,852 1,886 1,900 2% 3%

Nov 1,710 1,802 1,764 5% 3%

Sources: SNL Financial (load data); WWSIS (wind site production estimates).

2,000

3,000

4,000

5,000

6,000

7,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Load Net load (CO sites) Net load (CO-WY sites)
23

Generally, then, combining wind power supplies from Colorado and Wyoming tends to 

increase the stability of electricity costs more than obtaining wind power only from 

Colorado. Conversely, using only Colorado wind would tend toward less use of coal and 

a greater reduction in carbon emissions from coal plants serving Colorado load.

The next part of the analysis examined Colorado as an energy exporter, using 2005 load 

data for the California Independent System Operator (CAISO). As earlier sections of this 

report demonstrate, California constitutes the largest demand for regional renewable 

energy. This part of the analysis uses 15 GW of wind power, which would have produced 

about 20% of CAISO’s 2005 demand. (The three Colorado sites would yield 20%, while 

the three Wyoming sites would yield 22.4%. The same capacity distributed among the six 

Colorado and Wyoming sites would yield 21.2%.)

Figure 5 shows—and Table 5 quantifies—what would happen to CAISO’s net load with 

Colorado competing head-to-head with Wyoming via separate transmission lines, and 

with Colorado and Wyoming sharing a single line to California.10 For every month 

except December, California’s net load profile with Colorado wind exhibits larger 

differences between the daily highs and lows than is the case with Wyoming wind. 

Moreover, the net load profile with Wyoming wind is actually flatter than the unadjusted

daily load profile for four months out of the year.

Figure 5: Diurnal Load Profiles for California ISO, Averaged by Month

Net load for California ISO calculated based on 15 gigawatts of wind capacity.

Sources: SNL Financial (load data); WWSIS (wind site production estimates).

 10 For simplicity, this analysis assumes a direct DC line to CAISO from Colorado fed by Colorado 

resources only, from Wyoming fed by Wyoming resources only, or a single line fed by wind resources 

from both states. On an upgraded AC network path, the diurnal effect of Wyoming or Colorado wind on 

California’s net load would be affected by the diurnal profiles of other loads on the network path.

0

10,000

20,000

30,000

40,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Average of CAISO load Net load (CO sites)

Net load (WY sites) Net load (CO-WY sites)
24

Table 5: Diurnal Extrema Differences for California ISO, 2005

Difference between average daily maximum 

and minimum load

Magnitude of net load difference 

relative to load-only

Loadonly

Net load 

(CO 

sites)

Net load

(WY sites)

Net load 

(CO-WY 

sites)

Net load 

(CO sites)

Net load

(WY sites)

Net load 

(CO-WY 

sites)

Jan 10,256 11,860 11,656 11,758 16% 14% 15%

Feb 9,629 9,640 9,192 9,416 0% -5% -2%

Mar 9,544 9,763 7,985 8,863 2% -16% -7%

Apr 8,658 9,874 8,134 8,722 14% -6% 1%

May 9,776 12,039 9,740 10,881 23% 0% 11%

Jun 10,800 13,168 12,326 12,685 22% 14% 17%

Jul 16,710 19,594 18,129 18,776 17% 8% 12%

Aug 16,416 18,408 16,703 17,527 12% 2% 7%

Sep 11,203 13,850 10,748 12,243 24% -4% 9%

Oct 10,047 10,744 10,119 10,347 7% 1% 3%

Nov 10,262 10,943 10,489 10,688 7% 2% 4%

Dec 11,287 11,493 11,656 11,574 2% 3% 3%

Sources: SNL Financial (load data); WWSIS (wind site production estimates).

Significantly, during the peak load months of July and August, 15 GW of Wyoming wind 

would have flattened CAISO’s net load profile by 1,500 MW to 1,700 MW more than the 

same amount of Colorado wind would have. This means that Wyoming wind (relative to 

the same amount of Colorado wind capacity) would have required more baseload during 

the early-morning hours, and less natural gas generation during the peak hours. The effect 

would be more relief from high wholesale prices in the entire CAISO market during the 

peak summer hours.

A two-state supply, however, would preserve much of the summertime price relief effects 

in California. Over the entire year, the price effect (as represented by changes in the 

difference between daily extrema) would be midway between that of Colorado and 

Wyoming separately.

In summary, 2005 empirical data from the six sample wind sites, CAISO load, and PSCo 

suggest the following.

• Wind farms in Wyoming can typically deliver more electricity to the market on an 

annual basis than can the same quantity of wind capacity located in Colorado. 

• A common transmission system with a balancing authority area spanning both 

Colorado and Wyoming would yield price stability benefits and emissionreduction benefits midway between what wind resources from either state would 

provide individually.
25

• The daily profile of Wyoming wind power is such that it would be more likely to 

help mitigate high wholesale prices in the CAISO market than would Colorado 

wind power.

Implications for energy storage

Energy storage, operating reserves, and curtailing spikes in wind output are three tools 

for addressing the same task of managing naturally variable renewable resources. Each 

tool poses its own challenges, but if a larger balancing area improves renewable energy’s 

intra-hour variability and load-following characteristics, the challenges may be less 

problematic.

For storage, the challenges are regulatory (e.g., permits for adding pumped storage 

capability to existing reservoirs), technological (e.g., large-scale use of underground 

compressed air storage, batteries or flywheels), as well as economic (particularly how 

costs are recovered). The details of these challenges are beyond the scope of this analysis

and are being addressed in several studies by NREL and others. Nevertheless, the present 

analysis does suggest that, if a storage facility supports a geographically larger balancing 

area rather than a smaller one, then

• the real-time production changes that storage would need to offset would tend to 

be smaller, and

• the risk and financial burden of the project could be spread out over a larger 

economic base.
26

Conclusion

Colorado could benefit from selling renewable power to other states, but doing so would 

most likely require multistate policy partnerships. Interstate commerce in almost any 

commodity requires some conveyance infrastructure as well as common rules ensuring 

fair and open access to the market. Colorado cannot by itself plan or authorize the 

transmission that would be necessary for more robust interstate commerce in renewable 

power to happen. Even if Colorado were to try to get ahead of other states by accelerating 

its environmental and siting reviews11, there would still be the issue of whether the power 

could get to market via the existing regional transmission network.12

With respect to the renewable energy supply chain, Colorado is already a major regional 

presence. Its emergence as a center for manufacturing and production of renewable 

energy equipment effectively makes Colorado the commercial hub of a regional New 

Energy Economy. Vestas, the world’s largest manufacturer of wind turbines, builds 

components in Colorado. Likewise the Solar Energy Industries Association estimates 

there are nineteen companies currently in Colorado that produce equipment that directly 

serve the solar energy technologies supply chain.

Expanding its existing manufacturing base for renewable energy would allow Colorado 

to take advantage of renewable energy development across the region wherever it occurs. 

For the most part, doing so would involve expanding and promoting advantages the state 

already has, particularly:

• The value of existing manufacturers and institutions engaged in R&D. Colorado’s 

existing manufacturing base and R&D facilities at its research universities, 

NREL, and in private industry provide a unique advantage for Colorado. By 

leveraging the benefits that result from having a strong R&D and manufacturing 

base, Colorado can use these assets to attract component suppliers, entrepreneurs, 

and new manufacturing firms to the state. 

• Continued development of the state’s renewable energy markets. A proven market 

demand for renewable energy increases investor confidence, and therefore helps 

attract new manufacturing investment. State policymakers may not be able to 

have a direct influence on national market conditions, but ensuring a robust state 

market for emerging renewable energy technologies can help draw manufacturers, 

especially for emerging technologies.

• State and local infrastructure development. A well-functioning and efficient 

transportation system is critical for the movement of renewable energy 

components between suppliers and assemblers as well as the movement of 

product to the site of final installation. Research has shown that local 

infrastructure is important for the support of large-scale equipment producers; 

 11 Wyoming and Utah are already ahead of Colorado in providing wind power to the West Coast, however. 12 The use of unbundled RECs would make this problem moot, but at the same time Colorado would face 

higher reliability costs due to the larger amount of renewable power it would have to accommodate locally. 
27

infrastructure can also reflect on broad trends in governance. Furthermore, 

investments in fundamental economic assets can enhance economic productivity

throughout the state. 

• Education and workforce training. Workforce development becomes easier and 

gathers its own momentum when a sector becomes large and active enough to 

reach critical mass in the economic sense. As such, Colorado’s renewable energy 

workforce is likely to grow simply based on existing assets. To keep its advantage 

over other states, however, Colorado will need to continue maintaining and 

expanding its renewable energy workforce.

This analysis shows that some empirical reason exists for believing multistate 

collaboration could yield efficiency gains that may augment the regional competitiveness 

of Colorado’s wind resources. Consolidating operations across larger balancing authority 

areas would likely make wind power easier and less costly to manage. Geographic 

diversity would reduce moment-to-moment variability in wind power output, which 

would reduce the amount of reserves required to keep load and generation in balance and 

to manage reliability. Less moment-to-moment variability in wind and solar resources 

would help day-ahead scheduling of coal- and gas-fired generators. The forecasted net 

load profile would be more consistent, providing clearer benchmarks for the amount of 

baseload, intermediate, and peaking generation that would be required from conventional 

resources during the operating day. 

Additional WWSIS analysis will indicate whether the findings of the present study 

(limited to Colorado and Wyoming) also hold across the entire West. If so, it could 

indicate greater value-added for renewable energy overall if a larger and more robust 

regional market were to develop. Colorado could, therefore, have a dual stake in a 

regional transmission strategy: greater opportunities to sell its own wind power, and 

greater manufacturing output as renewable energy suppliers in Colorado increase their 

production. 
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1. REPORT DATE (DD-MM-YYYY)

December 2009

2. REPORT TYPE

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4. TITLE AND SUBTITLE

Colorado’s Prospects for Interstate Commerce in Renewable Power

5a. CONTRACT NUMBER

DE-AC36-08-GO28308

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

D.J. Hurlbut

5d. PROJECT NUMBER

NREL/TP-6A2-47179

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WTG8.1000

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National Renewable Energy Laboratory

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Golden, CO 80401-3393

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REPORT NUMBER

NREL/TP-6A2-47179

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14. ABSTRACT (Maximum 200 Words)

Colorado has more renewable energy potential than it is ever likely to need for its own in-state electricity consumption. 

Such abundance may suggest an opportunity for the state to sell renewable power elsewhere, but Colorado faces 

considerable competition from other western states that may have better resources and easier access to key markets on 

the West Coast. This report examines factors that will be important to the development of interstate commerce for 

electricity generated from renewable resources. It examines market fundamentals in a regional context, and then looks 

at the implications for Colorado.

15. SUBJECT TERMS

solar photovoltaics; solar energy; PV; analysis; NREL; wind energy; Colorado; interstate commerce; renewable 

power; electricity transmission; renewable energy markets; electricity consumption; Western Renewable Energy 

Zone; WREZ; Colorado Governor's Energy Office; Western Governors' Association; WGA; NREL; David J. Hurlbut

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