NREL is a national laboratory of the U.S. Department of Energy, Office of Energy 

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Contract No. DE-AC36-08GO28308

U.S. Renewable Energy Technical 

Potentials: A GIS-Based Analysis 

Anthony Lopez, Billy Roberts, Donna Heimiller, 

Nate Blair, and Gian Porro

Technical Report

NREL/TP-6A20-51946

July 2012
NREL is a national laboratory of the U.S. Department of Energy, Office of Energy 

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

National Renewable Energy Laboratory

15013 Denver West Parkway

Golden, Colorado 80401

303-275-3000 • www.nrel.gov

Contract No. DE-AC36-08GO28308

U.S. Renewable Energy 

Technical Potentials: A GISBased Analysis 

Anthony Lopez, Billy Roberts, Donna 

Heimiller, Nate Blair, and Gian Porro

Prepared under Task Nos. SA10.1012 and SA10.20A4

Technical Report

NREL/TP-6A20-51946

July 2012
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iii

Acknowledgments 

For their valuable contributions, the authors would like to thank Paul Denholm, Craig 

Turchi, Sean Ong, Eason Drury, Matt Mowers, Trieu Mai, Randolph Hunsberger, Anelia 

Milbrandt, Marc Schwartz, Chad Augustine, Andrew Perry, and Mike Meshek of the 

National Renewable Energy Laboratory and Douglas Hall from the Idaho National 

Laboratory. The authors would also like to thank peer reviewers Irene Xiarchos from the 

U.S. Department of Agriculture and Phillip Brown from the Congressional Research 

Service.
iv

Executive Summary

The National Renewable Energy Laboratory (NREL) routinely estimates the technical 

potential of specific renewable electricity generation technologies. These are technologyspecific estimates of energy generation potential based on renewable resource availability 

and quality, technical system performance, topographic limitations, environmental, and 

land-use constraints only. The estimates do not consider (in most cases) economic or 

market constraints, and therefore do not represent a level of renewable generation that 

might actually be deployed. 

This report is unique in unifying assumptions and application of methods employed to 

generate comparable estimates across technologies, where possible, to allow crosstechnology comparison. Technical potential estimates for six different renewable energy 

technologies were calculated by NREL, and methods and results for several other 

renewable technologies from previously published reports are also presented. Table ES-1 

summarizes the U.S. technical potential, in generation and capacity terms, of the 

technologies examined. 

The report first describes the methodology and assumptions for estimating the technical 

potential of each technology, and then briefly describes the resulting estimates. The 

results discussion includes state-level maps and tables containing available land area 

(square kilometers), installed capacity (gigawatts), and electric generation (gigawatthours) for each technology. 

Table ES-1. Total Estimated U.S. Technical Potential Generation and Capacity

by Technology

Technology Generation 

Potential (TWh)a

Capacity 

Potential (GW)a

Urban utility-scale PV 2,200 1,200

Rural utility-scale PV 280,600 153,000

Rooftop PV 800 664

Concentrating solar power 116,100 38,000

Onshore wind power 32,700 11,000

Offshore wind power 17,000 4,200

Biopowerb 500 62

Hydrothermal power 

systems

300 38

Enhanced geothermal

systems

31,300 4,000

Hydropower 300 60 a

 Non-excluded land was assumed to be available to support development of more 

than one technology. b All biomass feedstock resources considered were assumed to be available for 

biopower use; competing uses, such as biofuels production, were not considered. 
v 

Table of Contents

Acknowledgments......................................................................................................................................iii

Executive Summary ...................................................................................................................................iv

List of Figures .............................................................................................................................................vi

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

Introduction .................................................................................................................................................. 1

Analysis ........................................................................................................................................................ 3

Solar Power Technologies .........................................................................................................3

Wind Power Technologies .........................................................................................................5

Biopower Technologies .............................................................................................................5

Geothermal Energy Technologies ..............................................................................................6

Hydropower Technologies .........................................................................................................7

Results.......................................................................................................................................................... 8

Solar Power Technologies .........................................................................................................8

Wind Power Technologies .........................................................................................................8

Biopower Technologies .............................................................................................................9

Geothermal Energy Technologies ..............................................................................................9

Hydropower Technologies .........................................................................................................9

Discussion..................................................................................................................................................20

References .................................................................................................................................................21

Appendix A. Exclusions and Constraints, Capacity Factors, and Power Densities ..........................24

Appendix B. Energy Consumption by State...........................................................................................32
vi

List of Figures 

Figure 1. Levels of potential ......................................................................................................1

Figure 2. Total estimated technical potential for urban utility-scale photovoltaics in 

the United States ................................................................................................................10

Figure 3. Total estimated technical potential for rural utility-scale photovoltaics in the 

United States ......................................................................................................................11

Figure 4. Total estimated technical potential for rooftop photovoltaics in the United 

States ..................................................................................................................................12

Figure 5. Total estimated technical potential for concentrating solar power in the 

United States ......................................................................................................................13

Figure 6. Total estimated technical potential for onshore wind power in the United 

States ..................................................................................................................................14

Figure 7. Total estimated technical potential for offshore wind power in the United 

States ..................................................................................................................................15

Figure 8. Total estimated technical potential for biopower in the United States .....................16

Figure 9. Total estimated technical potential for hydrothermal power in the United 

States ..................................................................................................................................17

Figure 10. Total estimated technical potential for enhanced geothermal systems in the 

United States ......................................................................................................................18

Figure 11. Total estimated technical potential for hydropower in the United States ..............19

Figure B-1. Electric retail sales in the United States in 2010 (EIA). .......................................32
vii

List of Tables

Table ES-1. Total Estimated U.S. Technical Potential Generation and Capacity by 

Technology ........................................................................................................................ iv

Table 2. Total Estimated Technical Potential for Urban Utility-Scale Photovoltaics by 

State....................................................................................................................................10

Table 3. Total Estimated Technical Potential for Rural Utility-Scale Photovoltaics by 

State....................................................................................................................................11

Table 4. Total Estimated Technical Potential for Rooftop Photovoltaics by State .................12

Table 5. Total Estimated Technical Potential for Concentrating Solar Power by State ..........13

Table 6. Total Estimated Technical Potential for Onshore Wind Power by State ...................14

Table 7. Total Estimated Technical Potential for Offshore Wind Power by State ..................15

Table 8. Total Estimated Technical Potential for Biopower by State ......................................16

Table 9. Total Estimated Technical Potential for Hydrothermal Power by State ....................17

Table 10. Total Estimated Technical Potential for Enhanced Geothermal Systems by 

State....................................................................................................................................18

Table 11. Total Estimated Technical Potential for Hydropower by State ...............................19

Table 12. Total Estimated Technical Potential Generation and Capacity by 

Technology ........................................................................................................................20

Table A-1. Exclusions and Constraints for Urban Utility-Scale Photovoltaics .......................24

Table A-2. Capacity Factors for Utility-Scale Photovoltaics ..................................................25

Table A-3. Exclusions and Constraints for Rural Utility-Scale Photovoltaics and 

Concentrating Solar Power ................................................................................................26

Table A-4. Capacity Factors for Concentrating Solar Power ..................................................26

Table A-5. Exclusions and Constraints for Onshore Wind Power ..........................................27

Table A-6. Capacity Factor for Offshore Wind Power ............................................................28

Table A-7. Conversion of Offshore Wind Speeds at 90 Meters to Power Classes ..................28

Table A-8. Exclusions and Constraints for Offshore Wind Power ..........................................29

Table A-9. Exclusions and Constraints for Enhanced Geothermal Systems ...........................30

Table A-10. Power Densities for Enhanced Geothermal Systems ..........................................31

Table A-11. Exclusions and Constraints for Enhanced Geothermal Systems .........................31

Table B-1. Electric Retail Sales by State, 2010 .......................................................................32
1 

Introduction

Renewable energy technical potential, as defined in this study, represents the achievable 

energy generation of a particular technology given system performance, topographic 

limitations, environmental, and land-use constraints. The primary benefit of assessing 

technical potential is that it establishes an upper-boundary estimate of development 

potential (DOE EERE 2006). It is important to understand that there are multiple types of 

potential—resource, technical, economic, and market—each seen in Figure 1 with its key 

assumptions. 

Figure 1. Levels of potential 

Figure 1 is based on Table 4-1 in the 2011 update of DOE EERE (2006).

Although numerous studies have quantified renewable resource potential, comparing 

their results is difficult because of the different assumptions, methodologies, reporting 

units, and analysis time frames used (DOE EERE 2006). A national study of resourcebased renewable energy technical potential across technologies has not been publicly 

available due to the challenges of unifying assumptions for all geographic areas and 

technologies (DOE EERE 2006). 
2 

This report presents the state-level results of a spatial analysis calculating renewable 

energy technical potential, reporting available land area (square kilometers), installed 

capacity (gigawatts), and electric generation (gigawatt-hours) for six different renewable 

electricity generation technologies: utility-scale photovoltaics (both urban and rural), 

concentrating solar power, onshore wind power, offshore wind power, biopower, and 

enhanced geothermal systems. Each technology’s system-specific power density (or 

equivalent), capacity factor, and land-use constraints (Appendix A) were identified using 

published research, subject matter experts, and analysis by the National Renewable 

Energy Laboratory (NREL). System performance estimates rely heavily on NREL’s

Systems Advisor Model (SAM)1 and Regional Energy Deployment System (ReEDS),2a 

multiregional, multi-time period, geographic information system (GIS) and linear 

programming model. This report also presents technical potential findings for rooftop 

photovoltaic, hydrothermal, and hydropower in a similar format based solely on previous 

published reports. 

We provide methodological details of the analysis and references to the data sets used to 

ensure readers can directly assess the quality of data used, the data’s underlying 

uncertainty, and impact of assumptions. While the majority of the exclusions applied for 

this analysis focus on evaluating technical potential, we include some economic 

exclusion criteria based on current commercial configuration standards to provide a more 

reasonable and conservative estimation of renewable resource potential. 

Note that as a technical potential, rather than economic or market potential, these estimates 

do not consider availability of transmission infrastructure, costs, reliability or time-ofdispatch, current or future electricity loads, or relevant policies. Further, as this analysis does

not allocate land for use by a particular technology, the same land area may be the basis for 

estimates of multiple technologies (i.e., non-excluded land is assumed to be available to 

support development of more than one technology). 

Finally, since technical potential estimates are based in part on technology system 

performance, as these technologies evolve, their technical potential may also change. 

 

1 For more information, see http://sam.nrel.gov/. 2 For more information, see http://www.nrel.gov/analysis/reeds/. 
3 

Analysis 

Solar Power Technologies 

Utility-Scale Photovoltaics (Urban) 

We define urban utility-scale photovoltaics (PV) as large-scale PV deployed within urban 

boundaries on urban open space. The process for generating technical estimates for urban 

utility-scale PV begins with excluding areas not suitable for this technology. We first 

limit areas to those within urbanized area boundaries as defined by the U.S. Census 

Bureau (ESRI 2004) and further limit these areas to those with slopes less than or equal 

to 3%. Parking lots, roads, and urbanized areas are excluded by identifying areas with 

imperviousness greater than or equal to 1% (MRLC n.d.). Additional exclusions (Table 

A-1) are applied to eliminate areas deemed unlikely for development. The remaining land 

is grouped into contiguous areas and areas less than 18,000 square meters (m2

) are 

removed to ensure that total system size is large enough to be considered a utility-scale 

project.3

 This process produces a data set representative of the final available urban open 

space suitable for PV development. We obtain state-level annual capacity factors using 

the National Solar Radiation Database Typical Meteorological Year 3 (TMY3) data set 

(Wilcox, 2007; Wilcox and Marion, 2008) (Table A-2) and the SAM model. The PV 

system assumed in this analysis was a 1-axis tracking collector with the axis of rotation 

aligned north-south at 0 degrees tilt from the horizontal, which has a power density of 48 

MW per square kilometer (MW/km2

) (Denholm and Margolis 2008a). State technical 

potential generation is expressed as: 

ܹܯ 48൬ ݕݐ݅ݏ݀݁݊ ݎ݁ݓ݋݌ · ଶሻ݇݉ሺ ܽܿ݁݌ݏ݁݊݌݋ ܾܽ݊ݎݑሾ∑݁ݐܽݐܵ ൌ ܹ݄ܯ ݁ݐܽݐܵ

݇݉ଶ൰

 ሻሿݎ݁ܽݕ ݎ݁݌ ݏݎݑ݋݄ሺ 8760 · ሻ%ሺ ݎ݋ݐ݂ܽܿ ݕݐܽܿ݅݌ܿܽ ݁ݐܽݐݏ ·

Utility-Scale Photovoltaics (Rural) 

We define rural utility-scale PV as large-scale PV deployed outside urban boundaries (the 

complement of urban utility-scale PV). Technical potential estimates for rural utilityscale PV begin by first excluding urban areas as defined by the U.S. Census Bureau’s 

urbanized area boundaries data set. We calculate percent slope for areas outside the urban 

boundaries and eliminate all areas with slopes greater than or equal to 3%. Federally 

protected lands, inventoried roadless areas, and areas of critical environmental concern 

are also excluded, as they are considered unlikely areas for development. Table A-3 

contains the full list of exclusions. To limit the available lands to only larger PV systems, 

a 1-km2

 contiguous area filter was applied to produce a final available land layer. Finally, 

we calculate technical potential energy generation for this available land with the same 

annual average capacity factors, system design, and power density as for urban utilityscale PV, expressed as: 

ܹܯ 48൬ ݕݐ݅ݏ݀݁݊ ݎ݁ݓ݋݌ · ଶሻ݇݉ሺ ݈ܽ݊݀ ݈ܾ݈ܽ݅ܽ݁ݒܽሾ∑݁ݐܽݐܵ ൌ ܹ݄ܯ ݁ݐܽݐܵ

݇݉ଶ൰

 ሻሿݎ݁ܽݕ ݎ݁݌ ݏݎݑ݋݄ሺ 8760 · ሻ%ሺ ݎ݋ݐ݂ܽܿ ݕݐܽܿ݅݌ܿܽ ݁ݐܽݐݏ ·

 

3

 Depending on the PV system, 18,000 m2 produces roughly a 1-MW system. 
4 

Rooftop Photovoltaics 

We obtained rooftop PV estimates from Denholm and Margolis (2008b), who obtained 

floor space estimates for commercial and residential buildings from McGraw-Hill and 

scaled these to estimate a building footprint based on the number of floors. Average floor 

estimates were obtained from the Energy Information Administration’s 2005 Residential 

Energy Consumption Survey (RECS) (DOE EIA 2005) and the 2003 Commercial 

Building Energy Consumption Survey (CBECS) (DOE EIA 2003). Denholm and 

Margolis (2008b) calculated roof footprint by dividing the building footprint by the 

number of floors. They estimated 8% of residential rooftops4

 and 63% of commercial 

rooftops5

 were flat. Orientations of pitched roofs were distributed uniformly. Usable roof 

area was extracted from total roof area using an availability factor that accounted for 

shading, rooftop obstructions, and constraints. Base estimates resulted in availability of 

22% of roof areas for residential buildings in cool climates and 27% available in 

warm/arid climates. Denholm and Margolis (2008b) estimated commercial building 

availability at 60% for warm climates and 65% for cooler climates. Estimated average 

module efficiency was set at 13.5% with a power density for flat roofs of 110 W/m2 and 

135 W/m2 for the rest. Denholm and Margolis (2008b) then aggregated state PV capacity 

to match Census Block Group populations; they then calculated capacity factors for the 

closest TMY station and applied these to the closest population group.

Concentrating Solar Power 

We define concentrating solar power (CSP) as power from a utility-scale solar power 

facility in which the solar heat energy is collected in a central location. The technical 

potential estimates for CSP were calculated using satellite-modeled data from the 

National Solar Radiation Database (Wilcox, 2007), which represent annual average direct 

normal irradiance (DNI) as kilowatt-hours per square meter per day (kWh/m2/day) from 

1998 to 2005 at a 10-km horizontal spatial resolution. We consider viable only those 

areas with DNI greater than or equal to 5 kWh/m2/day (Short et al. 2011).6 Capacity 

factor values used in this analysis were generated for a trough system, dry-cooled with 

six hours of storage and a solar multiple7 of 2, with a system power density of 32.8 

MW/km2

.

8

 The capacity factors for each resource class (Table A-4) are generated using 

the SAM model and TMY3. Land, slope, and contiguous area exclusions are consistent 

with rural utility-scale PV (Table A-3). Technical state energy generation was expressed 

as: 

ܹܯ 32.895൬ ݕݐ݅ݏ݀݁݊ ݎ݁ݓ݋݌ · ଶሻ݇݉ሺ݈ܽ݊݀ ݈ܾ݈ܽ݅ܽ݁ݒܽሾ∑݁ݐܽݐܵ ൌ ܹ݄ܯ ݁ݐܽݐܵ

݇݉ଶ൰ 

 ሻሿݎ݁ܽݕ ݎ݁݌ ݏݎݑ݋݄ሺ 8760 · ሻ%ሺ ݎ݋ݐ݂ܽܿ ݕݐܽܿ݅݌ܿܽ ݁ݐܽݐݏ ·

 

4

 Based on estimates from Navigant Consulting 

5

 Based on Commercial Building Energy Consumption Survey (CBECS) database 

6

 Technology improvements may lead to improved performance in the future that could affect this 

threshold. 

7

 The field aperture area expressed as a multiple of the aperture area required to operate the power cycle at 

its design capacity. 

8

 Craig Turchi, NREL CSP Analyst, personal communication 
5 

Wind Power Technologies

Onshore Wind Power

We define onshore wind power as wind resource at 80 meters (m) height above surface

that results in an annual average gross9

 capacity factor of 30% (net capacity factor of 

25.5%), using typical utility-scale wind turbine power curves. AWS Truepower modeled 

the wind resource data using its Mesomap® process to produce estimates at a 200-m 

horizontal spatial resolution. These resource estimates are processed to eliminate areas 

unlikely to be developed, such as urban areas, federally protected lands, and onshore 

water features, Table A-5 includes a full list of exclusions. We estimate annual 

generation by assuming a power density of 5 MW/km2 (DOE EERE 2008)10 and 15% 

energy losses to calculate net capacity factor.11

Offshore Wind Power

We define suitable offshore wind resource as annual average wind speed greater than or 

equal to 6.4 meters per second (m/s) at 90 m height above surface.

12 The offshore wind 

resource data consists of a composite of data sets modeled to estimate offshore wind 

potential generated by AWS Truepower for the Atlantic Coast from Maine to 

Massachusetts, Texas, Louisiana, Georgia, and the Great Lakes. Other areas are included 

using near-shore estimates from onshore-modeled wind resources from published 

research (Schwartz et al. 2010). Because no offshore or near-shore estimates were 

available for Florida or Alaska (at the time of this publication), these states are omitted 

from the technical potential calculations. The offshore resource data extend 50 nautical 

miles from shore, and in some cases have to be extrapolated to fill the extent (Schwartz et 

al. 2010). We further filter the resource estimates to eliminate shipping lanes, marine 

sanctuaries, and a variety of other areas deemed unlikely to be developed. Table A-8 

contains a full list of exclusions. Our annual generation estimates assume a power density 

of 5 MW/km2 and capacity factors based on wind speed interval and depth-based wind 

farm configurations to account for anchoring and stabilization for the turbines as 

developed by NREL analysts for use in the ReEDS model (Musial and Ram 2010). 

Biopower Technologies

Biopower (Solid and Gaseous)

We obtained county-level estimates of solid biomass resource for crop, forest, 

primary/secondary mill residues, and urban wood waste from Milbrandt (2005, updated 

in 2008)13 who reported the estimates in bone-dry tonnes (BDT) per year. We calculate 

technical potential energy generation assuming 1.1 MWh/BDT, which represents an 

average solid biomass system output with an industry-average conversion efficiency of 

 

9 Gross capacity factor does not include plant downtime, parasitic power, or other factors that would be 

included to reduce the output to the “Net” capacity factor.

10 Represents total footprint; disturbed footprint ranges from 2% to 5% of the total

11 For more information, see http://www.windpoweringamerica.gov/wind_maps.asp. 12 This is a typical wind turbine hub-height for offshore wind developments.

13 For more information, see http://www.nrel.gov/gis/biomass.html. 
6 

20%, and a higher heating value (HHV) of 8,500 BTU/lb (Ince 1979). From Milbrandt 

(2005, partially updated in 2008),14

 we obtained county-level estimates of gaseous 

biomass (methane emissions), from animal manure, domestic wastewater treatment 

plants, and landfills; all estimates were reported in tonnes of methane (CH4) per year. We

calculate technical potential energy generation assuming 4.7 MWh/tonne of CH4, which 

represents a typical gaseous biomass system output with an industry-average conversion 

efficiency of 30% (Goldstein et al), and a HHV of 24,250 BTU/lb. Other biomass 

resources (such as orchard/vineyard pruning’s and black liquor) were not included in this 

study due to data limitations. Also, this analysis assumed that all biomass resources 

considered were available for biopower and did not evaluate competing uses such as 

biofuels production. The data from Milbrandt (2005, updated in 2008)15 illustrates the 

biomass resource currently available in the United States. Subsequent revisions of this 

analysis could evaluate projected U.S. resource potential, including dedicated energy 

crops such as those provided by the recent U.S. DOE update (DOE 2011) of the billionton study (Perlack et al. 2005). 

Geothermal Energy Technologies

Hydrothermal Power Systems

For identified hydrothermal and undiscovered hydrothermal, we used estimates from 

Williams et al. (2008), who estimated electric power generation potential of conventional 

geothermal resources (hydrothermal), both identified and unidentified in the western 

United States, Alaska, and Hawaii. Williams et al. derived total potential for identified 

hydrothermal resources by state from summations of volumetric models for the thermal 

energy and electric generation potential of each individual geothermal system (Muffler, 

1979). For undiscovered hydrothermal estimates, we used resource estimates generated 

by Williams et al. (2009) that used logistic regression models of the western United 

States to estimate favorability of hydrothermal development and thus, to estimate 

undiscovered potential. In all cases, exclusions included public lands, such as national 

parks, that are not available for resource development. 

Enhanced Geothermal Systems

We derive technical potential estimates for enhanced geothermal systems (EGS)

16 from 

temperature at depth data obtained from the Southern Methodist University’s (SMU)

Geothermal Laboratory.

17 The data ranged from 3 km to 10 km in depth. We consider 

viable those regions at each depth interval with temperatures ≥150°C. We apply known 

potential electric capacity (MWe/km3

) to each temperature-depth interval to estimate total 

potential at each depth interval based on the total volume of each unique temperature-

 

14 For more information, see http://www.nrel.gov/gis/biomass.html. 

15 For more information, see http://www.nrel.gov/gis/biomass.html. 

16 Deep enhanced geothermal systems (EGS) are an experimental method of extracting energy from deep 

within the Earth's crust. This is achieved by fracturing hot dry rock between 3 and 10 kilometers (km) 

below the Earth’s surface and pumping fluid into the fracture. The fluid absorbs the Earth's internal heat 

and is pumped back to the surface and used to generate electricity.

17 Maria Richards, SMU Geothermal Laboratory, e-mail message to author, May 29, 2009. Data set 

featured in The Future of Geothermal Energy (MIT 2006) 
7 

depth interval, shown in Table A-10. Electric generation potential calculations summarize 

the technical potential (MW) at all depth intervals, electric generation potential (GWh) at 

all depth intervals with a 90% capacity factor, and annual electric generation potential 

(GWh) only at optimum depth. We determine optimum depth by a quantitative analysis18

of levelized cost of electricity (LCOE). An optimum depth is found because drilling costs 

increase with depth while temperature, and therefore power plant efficiency, generally 

increase with depth so that power plant costs decrease with depth. Because drilling costs 

are increasing while power plant costs are decreasing on a per-MW basis, at some point 

there is a minimum. The optimum depth assumes that the EGS reservoir has a height or 

thickness of 1 km. 

Hydropower Technologies 

Hydropower 

Source point locations of hydropower estimates were provided by the Idaho National 

Laboratory and were taken from Hall et al. (2006). The point locations were based on a 

previous study (Hall et al. 2004) that produced an assessment of gross power potential of 

every stream in the United States. To generate their own estimates, Hall et al. developed 

and used a feasibility study and development model. The feasibility study included 

additional economic potential criteria such as site accessibility, load or transmission 

proximity, along with technical potential exclusions of land use or environmental 

sensitivity. Sites meeting Hall et al. (2006) feasibility criteria were processed to produce 

power potential using a development model that did not require a dam or reservoir be 

built. The development model assumed only a low power (<1 MWa) or small hydro (>= 

1 MWa and <= 30 MWa) plant would be built. To produce state technical potentials, we 

aggregated the previously mentioned source point locations to the state level.

 

18 We used the quantitative analysis method from Augustine (2011). 
8 

Results 

For each technology, we provide a brief summary of our findings along with a figure 

(map) showing the total estimated technical potential for all states and a table listing the 

total estimated technical potential by state. 

Solar Power Technologies 

Utility-Scale PV (Urban) 

The total estimated annual technical potential in the United States for urban utility-scale 

PV is 2,232 terawatt-hours (TWh). Texas and California have the highest estimated 

technical potential, a result of a combination of good solar resource and large population. 

Figure 2 and Table 2 present the total estimated technical potential for urban utility-scale 

PV. 

Utility-Scale PV (Rural) 

Rural utility-scale PV leads all other technologies in technical potential. This is a result of 

relatively high power density, the absence of minimum resource threshold, and the 

availability of large swaths for development. Texas accounts for roughly 14% (38,993 

TWh) of the entire estimated U.S. technical potential for utility-scale PV (280,613 TWh). 

Figure 3 and Table 3 present the total estimated technical potential for rural utility-scale 

PV. 

Rooftop PV 

Total annual technical potential for rooftop PV is estimated at 818 TWh. States with the 

largest technical potential typically have the largest populations. California has the 

highest technical potential of 106 TWh due to its mix of high population and relatively 

good solar resource. Figure 4 and Table 4 present the total estimated technical potential 

for rural utility-scale PV. 

Concentrating Solar Power 

Technical potential for CSP exists predominately in the Southwest. The steep cutoff of 

potential, as seen in Figure 5, can be attributed to the resource minimum threshold of 

5 kWh/m2/day that was used in the analysis. Texas has the highest estimated potential of 

22,786 TWh, which accounts for roughly 20% of the entire estimated U.S. annual 

technical potential for CSP (116,146 TWh). Figure 5 and Table 5 present the total 

estimated technical potential for concentrating solar power. 

Wind Power Technologies 

Onshore Wind Power 

Technical potential for onshore wind power, which is present in nearly every state, is 

largest in the western and central Great Plains and lowest in the southeastern United 

States. While the wind resource intensity in the Great Plains is not as high as it is in some 

areas of the western United States, very little of the land area is excluded due to 

insufficient resource or due to other exclusions. In the eastern and western United States, 

the wind resource is more limited in coverage and is more likely to be impacted by 

environmental exclusions. Texas has the highest estimated annual potential of 5,552 

TWh, which accounts for roughly 17% of the entire estimated U.S. annual technical 
9 

potential for onshore wind (32,784 TWh). Figure 6 and Table 6 present the total 

estimated technical potential for onshore wind power. 

Offshore Wind Power

Technical potential for offshore wind power is present in significant quantities in all 

offshore regions of the United States. Wind speeds off the Atlantic Coast and in the Gulf 

of Mexico are lower than they are off the Pacific Coast, but the presence of shallower 

waters there makes these regions more attractive for development. Hawaii has the highest 

estimated annual potential of 2,837 TWh, which accounts for roughly 17% of the entire 

estimated U.S. annual technical potential for offshore wind (16,975 TWh). Figure 7 and 

Table 7 present the total estimated technical potential for offshore wind power. 

Biopower Technologies

Biopower (Solid and Gaseous)

Solid biomass accounts for 82% of the 400 TWh total estimated annual technical 

potential of biopower; of that, crop residues are the largest contributor. Gaseous biomass 

has an estimated annual technical potential of 88 TWh, of which landfills were the largest 

contributor. Figure 8 and Table 8 present the total estimated technical potential for

biopower. 

Geothermal Energy Technologies

Hydrothermal Power Systems

In the assessment, 71 TWh of electric power generation potential is the estimated total 

from existing (identified) hydrothermal sites spread among 13 states. An additional 237 

TWh of undiscovered hydrothermal resources are estimated to exist among these same 

states. Figure 9 and Table 9 present the total estimated technical potential for 

hydrothermal power systems.

Enhanced Geothermal Systems

The vast majority of the geothermal potential for EGS (31,344 TWh) within the 

contiguous United States is located in the westernmost portion of the country. The Rocky 

Mountain States, and the Great Basin particularly, contain the most favorable resource for 

EGS (17,414 TWh). However, even the central and eastern portions of the country have 

13,930 TWh of potential for EGS development. Note that, especially in western states, a 

considerable portion of the EGS resource occurs on protected land and was filtered out 

after exclusions were applied. Figure 10 and Table 10 present the total estimated 

technical potential for enhanced geothermal systems.

Hydropower Technologies

Hydropower

According to Hall et al. (2006), technical potential for hydropower exists predominately 

in the Northwest and Alaska with a combined total estimated at 69 TWh annually, which 

accounts for roughly 27% of the entire estimated U.S. annual technical potential for 

hydropower (259 TWh). Figure 11 and Table 11 present the total estimated technical 

potential for hydropower. 
10

Figure 2. Total estimated technical potential for urban utility-scale photovoltaics in the 

United States

Table 2. Total Estimated Technical Potential for Urban Utility-Scale Photovoltaics by Statea

a Non-excluded land was assumed to be available to support development of more than one 

technology.
11

Figure 3. Total estimated technical potential for rural utility-scale photovoltaics in the 

United States

Table 3. Total Estimated Technical Potential for Rural Utility-Scale Photovoltaics by Statea

a Non-excluded land was assumed to be available to support development of more than one 

technology.
12

Figure 4. Total estimated technical potential for rooftop photovoltaics in the United States

Table 4. Total Estimated Technical Potential for Rooftop Photovoltaics by Statea

a Non-excluded land was assumed to be available to support development of more than one 

technology.
13

Figure 5. Total estimated technical potential for concentrating solar power in the

United States 

Table 5. Total Estimated Technical Potential for Concentrating Solar Power by Statea

a

 Non-excluded land was assumed to be available to support development of more than one 

technology. 
14

Figure 6. Total estimated technical potential for onshore wind power in the United States

Table 6. Total Estimated Technical Potential for Onshore Wind Power by Statea

a

 Non-excluded land was assumed to be available to support development of more than one 

technology. 
15

Figure 7. Total estimated technical potential for offshore wind power in the United States

Table 7. Total Estimated Technical Potential for Offshore Wind Power by Statea

a Non-excluded land was assumed to be available to support development of more than one 

technology. 
16

Figure 8. Total estimated technical potential for biopower in the United States

Table 8. Total Estimated Technical Potential for Biopower by Statea

a

 Non-excluded land was assumed to be available to support development of more than one 

technology. All biomass feedstock resources considered were assumed to be available for 

biopower use; competing uses, such as biofuels production, were not considered.
17

Figure 9. Total estimated technical potential for hydrothermal power in the United States

Table 9. Total Estimated Technical Potential for Hydrothermal Power by Statea

a

 Non-excluded land was assumed to be available to support development of more than one 

technology. 
18

Figure 10. Total estimated technical potential for enhanced geothermal systems in the 

United States

Table 10. Total Estimated Technical Potential for Enhanced Geothermal Systems by Statea

a

 Non-excluded land was assumed to be available to support development of more than one 

technology. 
19

Figure 11. Total estimated technical potential for hydropower in the United States

Table 11. Total Estimated Technical Potential for Hydropower by Statea

a

 Non-excluded land was assumed to be available to support development of more than one 

technology. 
20

Discussion 

Table 12 summarizes the estimated technical generation and capacity potential in the Unites 

States for each renewable electricity technology examined in this report. As estimates of 

technical, rather than economic or market, potential, these values do not consider: 

• Allocation of available land among technologies (available land is generally 

assumed to be available to support development of more than one technology 

and each set of exclusions was applied independently) 

• Availability of existing or planned transmission infrastructure that is 

necessary to tie generation into the electricity grid

• The relative reliability or time-of-productions of power 

• The cost associated with developing power at any location 

• Presence of local, state, regional or national policies, either existing or 

potential, that could encourage renewable development 

• The location or magnitude of current and potential electricity loads. 

While not a direct comparison, given the above considerations, one useful point of reference 

for the generation potential estimate is annual electricity retail sales in the United States. In 

2010, aggregate sales for all 50 states were roughly 3,754 TWh (see Appendix B). 

Table 12. Total Estimated Technical Potential Generation and Capacity by Technology 

Technology Generation Potential 

(TWh)a Capacity Potential 

(GW)a

Urban utility-scale PV 2,200 1,200

Rural utility-scale PV 280,600 153,000

Rooftop PV 800 664

Concentrating solar power 116,100 38,000

Onshore wind power 32,700 11,000

Offshore wind power 17,000 4,200

Biopowerb 500 62

Hydrothermal power systems 300 38

Enhanced geothermal systems 31,300 4,000

Hydropower 300 60

a Non-excluded land was assumed to be available to support development of more than one 

technology.

b All biomass feedstock resources considered were assumed to be available for biopower use; 

competing uses, such as biofuels production, were not considered. 

Updates to these technical potentials are possible on an ongoing basis as resource, 

system, exclusions and domain knowledge change and data sets improve in quality and 

resolution. In this study, we identified areas of potential improvements that include the 

acquisition of localized PV capacity factors, updated exclusion layers, and the use of 

updated land-cover data sets. 
21

References 

Augustine, C. (October 2011). “Updated U.S. Geothermal Supply Characterization and 

Representation for Market Penetration Model Input.” NREL/TP-6A20-47459. Golden, 

CO: National Renewable Energy Laboratory. 

Black & Veatch. (2009). Internal NREL Subcontract.

U.S. Bureau of Land Management (BLM). (2009). “Area of Critical Environmental 

Concern (ACEC).”

Conservation Biology Institute (CBI). (2004). Protected Areas Database. “State/GAP 

Land Stewardship.” 

Denholm, P.; Margolis, R. M. (2008a). "Land-Use Requirements and the Per-Capita 

Solar Footprint for Photovoltaic Generation in the United States." Energy Policy, (36:9); 

pp. 3531-3543. 

Denholm, P.; Margolis, R. (2008b). "Supply Curves for Rooftop Solar PV-Generated 

Electricity for the United States." NREL/TP-6A0-44073. Golden, CO: National 

Renewable Energy Laboratory.

U.S. Department of Agriculture Forest Service (USFS). (2003). “National Inventoried 

Roadless Areas (IRA).”

U.S. Department of Energy. (2011). “U.S. Billion-Ton Update: Biomass Supply for a 

Bioenergy and Bioproducts Industry.” R.D. Perlack and B.J. Stokes (Leads). ORNL/TM2011/224. Oak Ridge, TN: Oak Ridge National Laboratory. 

U.S. Department of Energy (DOE) Energy Information Administration (EIA). (2003). 

Commercial Buildings Energy Consumption Survey (CBECS): 2003 Detailed Tables. 

http://www.eia.gov/emeu/cbecs/cbecs2003/detailed_tables_2003/detailed_tables_2003

.html. Accessed 2008. 

U.S. Energy Information Administration (EIA). State Electricity Profiles. http://205.254

.135.7/electricity/state/. Accessed 2012.

DOE EIA. (2005). Residential Energy Consumption Survey (RECS). http://www.eia.gov/

consumption/residential/data/2005/. Accessed 2008. 

DOE Office of Energy Efficiency and Renewable Energy (EERE). (October 2006, 

updated January 2011). “Report to Congress on Renewable Energy Resource Assessment 

Information for the United States.” January 2011 (EPACT) Prepared by the National 

Renewable Energy Laboratory. 

DOE EERE. (July 2008). “20% Wind Energy by 2030: Increasing Wind Energy's 

Contribution to U.S. Electricity Supply.” NREL/TP-500-41869. Golden, CO: National 

Renewable Energy Laboratory.
22

ESRI. (2003). “Airports and Airfields.” 

ESRI. (2004). “U.S. Census Urbanized Areas.” 

ESRI. (2007a). “Landmarks.” 

ESRI. (2007b). “U.S. Parks.” 

U.S. Geological Survey (USGS). (1993). “North America Land Use Land Cover 

(LULC),” version 2.0. 

USGS. (2005). Federal and Indian Lands. 

Goldstein, L.; Hedman, B.; Knowles, D.; Freedman, S.I.; Woods, R.; Schweizer, T. 

(2003). “Gas-Fired Distributed Energy Resource Technology Characteristics.” 

NREL/TP-620-34783. Golden, CO: National Renewable Energy Laboratory. 

Hall, D.G.; Cherry, S.J.; Kelly, S.R.; Lee, R.D.; Carroll, G.R.; Sommers, G.L.; Verdin, 

K.L. (April 2004). “Water Energy Resources of the United States with Emphasis on Low 

Head/Low Power Resources.” DOE/ID-11111. U.S. Department of Energy. 

Hall D.G.; Reeves, K.S.; Brizzee, J.; Lee, R.D.; Carroll, G.R.; Sommers, G.L. (January 

2006). "Feasibility Assessment of the Water Energy Resources of the United States for 

New Low Power and Small Hydro Classes of Hydroelectric Plants." DOE-ID-11263. 

Idaho National Laboratory. 

Ince, P.J. (1979). “How To Estimate Recoverable Heat Energy in Wood or Bark Fuels.” 

General Technical Report FPL 29. Madison, WI: United States Department of 

Agriculture, Forest Products Laboratory. http://www.fpl.fs.fed.us/documnts/fplgtr/

fplgtr29.pdf. 

Massachusetts Institute of Technology. (2006). “The Future of Geothermal Energy 

Impact of Enhanced Geothermal Systems (EGS) on the United in the 21st Century.” 

INL/EXT0611746. Cambridge, MA: Massachusetts Institute of Technology. http://

www1.eere.energy.gov/geothermal/future_geothermal.html 

Multi-Resolution Land Characteristics (MRLC) Consortium. (n.d.). National Land Cover 

Database. http://www.mrlc.gov/. Accessed 2010. 

Milbrandt, A. (December 2005). "A Geographic Perspective on the Current Biomass 

Resource Availability in the United States." NREL/TP-560-39181. Golden, CO: National 

Renewable Energy Laboratory.

Muffler, L.J.P., ed. (1979). “Assessment of geothermal resources of the United States — 

1978.” U. S. Geol. Survey Circ. 790. Arlington, VA: U.S. Geological Survey. 
23

Musial, W.; Ram, B. (2010). “Large-Scale Offshore Wind Power in the United States: 

Assessment of Opportunities and Barriers.” NREL/TP-500-40745. Golden, CO: National 

Renewable Energy Laboratory. 

NREL. (2010). Electricity Generation and Consumption by State 2008. http://en.openei

.org/datasets/node/60. Accessed 2010.

Perlack, R.; Wright, L.; Turhollow, A.; Graham, R.; Stokes, B.; Erbach, D. (2005). 

“Biomass as Feedstock for a Bioenergy and BioProducts Industry: The Technical 

Feasibility of a Billion-Ton Annual Supply.” ORNL/TM-2005/66. Oak Ridge, TN: Oak 

Ridge National Laboratory.

Short, W.; Sullivan, P.; Mai, T.; Mowers, M.; Uriarte, C.; Blair, N.; Heimiller, D.; 

Martinez, A. (2011). “Regional Energy Deployment System (ReEDS).” NREL/TP-6A2-

46534. Golden, CO: National Renewable Energy Laboratory. 

Schwartz, M.; Heimiller, D.; Haymes, S.; Musial, W. (June 2010). “Assessment of 

Offshore Wind Energy Resources for the United States.” NREL/TP-500-45889. Golden, 

CO: National Renewable Energy Laboratory. 

Williams, C.F.; Reed, M.J.; Mariner, R.H., DeAngelo, J.; Galanis, S.P., Jr. (2009). 

“Quantifying the Undiscovered Geothermal Resources of the United States.” U.S. 

Geologic Survey, Geothermal Resources Council Transactions, v. 33. p. 995-1001. 

Williams, C.F.; Reed, M.J.; Mariner, R.H., DeAngelo, J.; Galanis, S.P., Jr. (2008). 

“Assessment of Moderate- and High-Temperature Geothermal Resources of the United 

States.” U.S. Geological Survey Fact Sheet 2008-3082. Menlo Park, CA: U.S. Geological 

Survey. 

Wilcox, S. (2007). “National Solar Radiation Database 1991-2005 Update: User's 

Manual.” NREL/TP-581-41364. Golden, CO: National Renewable Energy Laboratory. 

Wilcox, S.; Marion, W. (2008). “Users Manual for TMY3 Data Sets (Revised).” NREL

/TP-581-43156. Golden, CO: National Renewable Energy Laboratory. 
24

Appendix A. Exclusions and Constraints, Capacity Factors, 

and Power Densities

Table A-1. Exclusions and Constraints for Urban Utility-Scale Photovoltaics 

Slope Exclusion > 3%

Contiguous Area Exclusion < 0.018 km2

Land Type(s) Exclusion Within Urban Boundaries ESRI (2004) 

Landmarks ESRI (2007a)

Parks ESRI (2007b) 

MRLC - Water MRLC (n.d.) 

MRLC - Wetlands MRLC (n.d.) 

MRLC - Forests MRLC (n.d.) 

MRLC -Impervious Surface >= 1% MRLC (n.d.) 
25

Table A-2. Capacity Factors for Utility-Scale Photovoltaicsa 

State Capacity Factor State Capacity Factor State Capacity Factor

Alabama 0.200 Maine 0.191 Oklahoma 0.223

Alaska 0.105 Maryland 0.179 Oregon 0.227

Arizona 0.263 Massachusetts 0.182 Pennsylvania 0.177

Arkansas 0.207 Michigan 0.173 Rhode Island 0.176

California 0.252 Minnesota 0.189 South Carolina 0.202

Colorado 0.259 Mississippi 0.197 South Dakota 0.214

Connecticut 0.182 Missouri 0.193 Tennessee 0.201

Delaware 0.186 Montana 0.212 Texas 0.218

Florida 0.209 Nebraska 0.217 Utah 0.248

Georgia 0.203 Nevada 0.263 Vermont 0.176

Hawaii 0.210 New Hampshire 0.184 Virginia 0.200

Idaho 0.220 New Jersey 0.200 Washington 0.199

Illinois 0.186 New Mexico 0.263 West Virginia 0.172

Indiana 0.184 New York 0.184 Wisconsin 0.180

Iowa 0.199 North Carolina 0.206 Wyoming 0.229

Kansas 0.238 North Dakota 0.203

Kentucky 0.186 Ohio 0.173

Louisiana 0.196

a (SAM)
26

Table A-3. Exclusions and Constraints for Rural Utility-Scale Photovoltaics and Concentrating 

Solar Power

Slope Exclusion > 3%

Contiguous Area 

Exclusion

< 1 km2

Land Type(s) 

Exclusion

Urban Areas ESRI (2004)

MRLC - Water MRLC (n.d.) 

MRLC - Wetlands MRLC (n.d.) 

BLM ACEC Lands (Areas of Critical 

Environmental Concern) (BLM 2009)

BLM (2009)

Forest Service IRA (Inventoried Roadless 

Area) (USFS 2003)

USFS (2003)

National Park Service Lands USGS (2005)

Fish & Wildlife Lands USGS (2005)

Federal Parks USGS (2005)

Federal Wilderness USGS (2005)

Federal Wilderness Study Area USGS (2005)

Federal National Monument USGS (2005)

Federal National Battlefield USGS (2005)

Federal Recreation Area USGS (2005)

Federal National Conservation Area USGS (2005)

Federal Wildlife Refuge USGS (2005)

Federal Wildlife Area USGS (2005)

Federal Wild and Scenic Area USGS (2005)

Table A-4. Capacity Factors for Concentrating Solar Powera 

Class Kwh/m2/day Capacity Factor

1 5–6.25 0.315

2 6.25–7.25 0.393

3 7.25–7.5 0.428

4 7.5–7.75 0.434

5 > 7.75 0.448

a (SAM) 
27

Table A-5. Exclusions and Constraints for Onshore Wind Power

Slope Exclusion > 20%

Distance 

Exclusion

< 3 km Distance to Excluded Area (does not apply to 

water)

Land Type(s) 

Exclusion

50% Forest Service Lands (includes National 

Grasslands, excludes ridge crests)

USGS (2005)

50% Department of Defense Lands (excludes ridge 

crest)

USGS (2005)

50% GAP Land Stewardship Class 2 - Forest CBI (2004)

50% Exclusion of non-ridge crest forest (noncumulative over Forest Service Land)USGS (2005)

Airports ESRI (2003)

Urban Areas ESRI (2004)

LULC - Wetlands USGS (1993)

LULC - Water USGS (1993)

Forest Service IRA (Inventoried Roadless Areas) USFS (2003)

National Park Service Lands USGS (2005)

Fish & Wildlife Lands USGS (2005)

Federal Parks USGS (2005)

Federal Wilderness USGS (2005)

Federal Wilderness Study Area USGS (2005)

Federal National Monument USGS (2005)

Federal National Battlefield USGS (2005)

Federal Recreation Area USGS (2005)

Federal National Conservation Area USGS (2005)

Federal Wildlife Refuge USGS (2005)

Federal Wildlife Area USGS (2005)

Federal Wild and Scenic Area USGS (2005)

GAP Land Stewardship Class 2 - State & Private Lands 

Equivalent to Federal Exclusions

CBI (2004)
28

Table A-6. Capacity Factor for Offshore Wind Powera 

Depth Class Watts/m2 Capacity Factor 

Shallow

0–30 meters 3 300–400 0.36

0–30 meters 4 400–500 0.39

0–30 meters 5 500–600 0.45

0–30 meters 6 600–800 0.479

0–30 meters 7 > 800 0.5

Deep

> 30 meters 3 300–400 0.367

> 30 meters 4 400–500 0.394

> 30 meters 5 500–600 0.45

> 30 meters 6 600–800 0.479

> 30 meters 7 > 800 0.5

a (ReEDS)

Table A-7. Conversion of Offshore Wind Speeds at 90 Meters to Power Classesa 

Wind Speed (meters / second) Power Class

6.4–7.0 3 

7 .0–7.5 4 

7.5–8.0 5 

8.0–8.8 6 

> 8.8 7 

a Marc Schwartz, NREL Wind Analyst, personal communication
29

Table A-8. Exclusions and Constraints for Offshore Wind Powera

Distance Exclusion < 50 nautical miles from shoreline

Land Type(s) Exclusion

Federal Exclusions National Marine Sanctuaries

Marine Protected Areas Inventory – ‘NAL’, ‘NIL’, ‘NTL’

Office of Habitat Conservation Habitat Protection Div. EFH – 

Shipping Routes, Sanctuary Protected Areas

NOAA Jurisdictional Boundaries and Limits – Coastal National 

Wildlife Refuges – Pacific 

Navigational & Marine Infrastructure – Shipping Lanes, Drilling 

Platforms (Gulf), Pipelines (Gulf), Fairways (Gulf)

NWIOOS – Towlane Agreement WSG 2007

World Database on Protected Areas Annual Release 2009 Global 

Data set – Offshore Oil & Gas Pipelines/Drilling Platforms

Texas Pipelines & Easements

Audubon Sanctuaries

Gulf Inter-coastal Waterway/Ship Channels

National Wildlife Refuges

Shipping Safety Fairways

State Coastal Preserves

Dredged Material Placement Sites

State Tracts with Resource Management Codes

North Carolina Significant Natural Heritage Areas

Sea Turtle Sanctuary 

Crane Spawning Sanctuary

Great Lakes IM ACC EPA

IM Ship Routes

Virginia Near-shore Coastal Parks

Threatened & Endangered Species Waters

Crab Sanctuary

Security Areas

Striped Bass Sanctuary 

State Park & State Dedicated Natural Area Preserve (w/in 1 mile of 

shoreline)

Rhode Island Habitat Restoration Area
30

Hazardous Material Sites Designated by the U.S. EPA and RIDEM 

(w/in 0.5 miles of shoreline)

CRMCWT08 (Type = 1 or 2)

South Carolina: Refuges

OCRM Critical Area

New Hampshire Conservation Focus Area

Florida Ocean Dredged Material Disposal Sites

Aquatic Preserve Boundaries

California Cordell Banks Closed Areas

Massachusetts Ferry Routes

Oregon Oregon Islands National Wildlife Refuges USFWS 2004

Oregon Marine Managed Areas

Oregon Cables OFCC 2005

Dredged Material Disposal Sites ACDE 2008

New Jersey New Jersey Coastal Wind Turbine Siting Map – Exclusion Areas

a Exclusions were developed by Black & Veatch (2009). 

Table A-9. Exclusions and Constraints for Enhanced Geothermal Systemsa

Land Type(s) Exclusion National Park Service Lands

Fish and Wildlife Service Lands

Federal Parks

Federal Wilderness

Federal National Monuments

Federal National Battlefields

Federal Restoration Areas

Federal National Conservation Areas

Federal Wildlife Refuge Areas

Federal Wild and Scenic Areas

a USGS (2005)
31

Table A-10. Power Densities for Enhanced Geothermal Systemsa 

Temperature C MW / km2

150–200 0.59

200–250 0.76

250–300 0.86

300–350 0.97

> 350 1.19

a Augustine (2011)

Table A-11. Exclusions and Constraints for Enhanced Geothermal Systemsa

Depth Constraints Depth > 3 and < 10 km

Land Type(s) Exclusion National Park Service Lands

Fish and Wildlife Service Lands

Federal Parks

Federal Wilderness

Federal National Monuments

Federal National Battlefields

Federal Restoration Areas

Federal Conservation Areas

Federal Wildlife Refuge Areas

Federal Wild and Scenic Areas

a USGS (2005)
32

Appendix B. Energy Consumption by State

Electric retail sales in the United States were roughly 3,754 TWh in 2010 (EIA). 

Figure B-1. Electric retail sales in the United States in 2010 (EIA). 

Table B-1. Electric Retail Sales by State, 2010a

a EIA