NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for S ustainable Energy, LLC.



### Contract No. DE

- AC36

- 08 GO28308 

# 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 2012NREL 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 EnergyTechnical Potentials: A GISBased Analysis

Anthony Lopez

, Billy Roberts

, Donna Heimiller, Nate Blair, and Gian Porro

Prepared under Task No s

. SA10

. 1012 and SA10

. 20A4

Techni c al Report NREL/TP -6A20- 51946 July 2012NOTICE

This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights . Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any ag ency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof.

Available electronically at http://www.osti.gov/br idge

Available for a processing fee to U.S. Department of Energy and its contractors, in paper, from:

U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, TN 37831

- 0062 phone: 865.576.8401 fax: 865.576.5728 email: mailto:reports@adonis.osti.gov

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

U.S. Department of Commerce National Technical Information Service 5285 Port Royal Road Springfield, VA 22161 phone: 80 0.553.6847 fax: 703.605.6900 email: orders@ntis.fedworld.gov online ordering: http://www.ntis.gov/help/ordermethods.aspx

Cover Photos: (left to rig ht) PIX 16416, PIX 17423, PIX 16560, PIX 17613, PIX 17436, PIX 17721

Printed on paper containing at least 50% wastepaper, including 10% post consumer waste

.

### 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 Rese arch Service.

### iv 

## Executive Summary

The National Renewable Energy Laboratory (NREL) routinely estimate s the technical potential of specific ren ewable 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 cross

technology comparison

. Technical potential estimates for six different renewable energy technologies were calculated by NREL, and methods and results fo r 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 methodolog y and assumptions for estimating the technical potential of each technology , and then briefly descri bes the resulting estimates . The results discussion includes state

- level maps and tables containing available land area (square kilometers), installed capacity (gigawatts), and electric generation (gigawatt

hours) for each technology.

**Table ES**  **-1 . Total**  **E stimated**  **U.S. T**  **echnical Potential G**  **eneration and C**  **apacity by**  **T echnology** 
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 Biopower b 500 62 Hydrothermal power systems 300 38

Enhanced geothermal systems 31,300 4,000

Hydropower 300 60

a N on

- 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 Figure s

............................................................................................................................................. 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 Figure s

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 technica l 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 Concent rating 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 E stimated 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 

## I ntroduction

R enewable 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 a n upper-boundary estimat e 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 the ir results is difficult because of the different assumptions, methodologies, reporting units, and analysis time frame s used ( DOE EERE 2006 ). A national study of resource

based 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 p erformance estimates rel y heavily on NREL’s Systems Advisor Model (SAM) 1 

### and Regional Energy Deployment System (ReEDS), 2 

### a 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 metho dological 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 analy sis 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. Fu rther, as t his analysis does

no t 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 fo r generating technical estimates for urban utility-scale PV begins with excluding areas not suitabl e 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 area s to those with slopes less than or equal to 3%. Parking lots, roads, and urbanized ar eas 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 (m 2 

### ) 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 represen tative of the final available urban open space suitable for PV development. We obtai n state-level annual cap acity 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 degr ees tilt from the horizontal, which has a power density of 48 MW per square kilometer (MW/km 2 

### ) (Denholm and Margolis 2008a). State technical potential generation is expressed as:

ܽܿ݁݌ݏ݁݊݌݋ ܾܽ݊ݎݑሾ∑݁ݐܽݐܵ ൌ ܹ݄ܯ ݁ݐܽݐܵ ሺ ݇݉ ଶ ሻ 48൬ ݕݐ݅ݏ݀݁݊ ݎ݁ݓ݋݌ · ܹܯ
݇݉ ଶ ൰

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



### Utility-Scale Photovoltaics (Rural) We define rural utility-scale PV as large-scale PV deploye d outside urban boundaries (the complement of urban utility-scale PV). T echnical potential estimates for rural utilityscale PV begin by first excludi ng urban areas as defined by the U.S. Census Bureau’s urbanized area boundaries data se t. We calculate percent slop e for areas outside the urban boundaries and eliminate all areas with slopes greater than or equal to 3%. Federally protected lands, inventoried ro adless areas, and areas of cr itical environmental concern are also excluded, as they are considered unlikely areas for development. Table A-3 contains the full list of exclusions. To limit th e available lands to only larger PV systems, a 1-km 2 

### contiguous area filter was applied to produ ce a final available land layer. Finally, we calculate technical potential energy generation for this available land with the same annual average capacity factors, system desi gn, and power density as for urban utilityscale PV, expressed as:

݈ܽ݊݀ ݈ܾ݈ܽ݅ܽ݁ݒܽሾ∑݁ݐܽݐܵ ൌ ܹ݄ܯ ݁ݐܽݐܵ ሺ ݇݉ ଶ ሻ 48൬ ݕݐ݅ݏ݀݁݊ ݎ݁ݓ݋݌ · ܹܯ
݇݉ ଶ ൰

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

3 Depending on the PV system, 18,000 m 2 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 In formation 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 build ing footprint by the number of floors. They estimated 8% of residential rooftops 4 

### and 63% of commercial rooftops 5 

### were flat. Orientations of pitched roof s were distributed uni formly. Usable roof area was extracted from total r oof area using an availability factor that accounted for shading, rooftop obstructions, and constraints. Ba se 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/m 2 

### and 135 W/m 2 

### for the rest. Denholm and Margolis (2008b) then aggregated state PV capacity to match Census Block Group populations; they then calculated capac ity factors for the closest TMY station an d applied these to th e closest population group.

Concentrating Solar Power We define concentrating solar power (CSP) as power from a util ity-scale solar power facility in which the solar h eat energy is collected in a central location. The technical potential estimates for CSP were calculate d using satellite-modeled data from the National Solar Radiation Databa se (Wilcox, 2007), which repres ent annual average direct normal irradiance (DNI) as kilowatt-hour s per square meter per day (kWh/m 2 

### /day) from 1998 to 2005 at a 10-km horizontal spatial re solution. We consider viable only those areas with DNI greater than or equal to 5 kWh/m 2 

### /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 multiple 7 

### of 2, with a system power density of 32.8 MW/km 2



### . 8 

### The capacity factors for ea ch 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). Tec hnical state energy ge neration was expressed

as:

݈ܽ݊݀ ݈ܾ݈ܽ݅ܽ݁ݒܽሾ∑݁ݐܽݐܵ ൌ ܹ݄ܯ ݁ݐܽݐܵ ሺ ݇݉ ଶ ሻ 32.895൬ ݕݐ݅ݏ݀݁݊ ݎ݁ݓ݋݌ · ܹܯ
݇݉ ଶ ൰

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

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 Anal yst, 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 gross 9 

### 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 Mesoma p® process to produce estimates at a 200

- m horizontal spatial resolution. T hese resource estimates are processed to eliminate areas unlikely to be developed, such as urban areas, federally protected lands, and onshor e water features

, Table A -5 includes a full list of exclusions . We estimate annual generation by assuming a power density of 5 MW/km 2 

### (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 consist s 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 s ome cases ha ve 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 l ist of exclusions. Our annual generation estimates assume a power density of 5 MW/km 2 

### 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 NRE L 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; d isturbed 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 

### w e obtained c ounty- level estimates of gaseous biomass ( methane emissions ), from animal manure

, domestic wastewater treatment plants, and landfills ; all estimates were reported in tonnes of methane (CH 4 

### ) per year. We calculate technical potential energy generation assuming 4.7 MWh/tonne of CH 4 

### , 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. O ther biomass resources (such as orchard/vineyard pruning’s and black liquor) were not included in this study due to data limitations

. Also, this analysis assume d that all biomass resources considered were available for biopower and did not evaluate competing uses such as biofuels production. The data from Milbrand t (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 b illion

ton study (Perlack et al. 2005).

Geothermal Energy Technologies **Hydrothermal Power Systems** For i dentified 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 w estern United States

, Alaska

, and Hawaii

. Williams et al. derived t otal 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 l ogistic r egression models of the w estern United States to estimate favorability of h ydrothermal development and thus, to estimate undiscovered potential. In all cases, exclusions included public lands, such as n ational parks , that are not available for resource development.

**Enhanced Geothermal Systems** We derive t echnical potential estimates for enhanced geothermal s ystems ( 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 r egions at each depth interval with temperatures ≥150°C. We apply known potential electric capacity (MW e 

### /km 3 

### ) to each temperature

- depth interval to estimate total potential at each dept h 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 Energ y (MIT 2006)

### 7 

### depth interval, shown in Ta ble A-10. Electric generation pot ential calculations summarize the technical potential (MW) at all depth intervals, electric generation potential (GWh) at all depth intervals with a 90% capacity fact or, and annual electric generation potential (GWh) only at optimum depth. We determin e optimum depth by a quantitative analysis 18


### of levelized cost of electr icity (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 co sts 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 assume s that the EGS reservoir has a height or thickness of 1 km.

Hydropower Technologies Hydropower Source point locations of hydropower estimat es 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 genera te their own estimates, Hall et al. developed and used a feasibility study and developm ent model. The feasibility study included additional economic potential criteria such as site accessibility, load or transmission proximity, along with technical potential ex clusions of land use or environmental sensitivity. Sites meeting Hall et al. (2006) feasibility criteri a 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 s ource 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 summa ry 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 sola r 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 le ads all other technologies in techni cal potential. This is a result of relatively high power density, the absence of minimum re source threshold, and the availability of large swaths for develo pment. Texas accounts for roughly 14% (38,993 TWh) of the entire estimated U.S. technical potential fo r 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 potentia l 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 pres ent the total estimated technical potential for rural utility-scale PV.

Concentrating Solar Power Technical potential for CSP exists predominat ely 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, whic h is present in nearly every state, is largest in the western and central Great Plai ns and lowest in the southeastern United States. While the wind resource intensity in the Gr eat Plains is not as hi gh 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 easte rn 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 en tire estimated U.S. annual technical

### 9 

### potential for onshore wind (32,784 TWh). Figure 6 and Table 6 present the t otal 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 t otal estimated technical potential for off shore wind power.

Biopower Technologies **Biopower (Solid a nd 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 t otal 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 un discovered hydrothermal resources are estimated to exist among these same
states. Figure 9 and Table 9 present the t otal estimated technical potential fo r hydrothermal power systems.
**Enhanced Geothermal Systems** The vast majority of the geothermal potential for EGS (31,344 TWh) within the

c ontiguous 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 t otal 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 t otal estimated technical potential for hydropower.

### 10 Figure 2. Total estimated technical potential for urban utility

- scale photovoltaics in the United States

**Table 2.**  **Total E stimated**  **T echnical**  **Potential for U rban**  **U tility**  **-S cale**  **Photovoltaics by**  **S tate**  **a**

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 E**  **stimated T**  **echnical Potential for R**  **ural U**  **tility -S**  **cale Photovoltaics**  **by State**  **a**

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 E**  **stimated T**  **echnical P**  **otential for Rooftop Photovoltaics**  **by S**  **tate a** 

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 E**  **stimated T**  **echnical P**  **otential for Concentrating Solar Power**  **by State**  **a**

a N on

- 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 E**  **stimated T**  **echnical P**  **otential for O**  **nshore W**  **ind P**  **ower by S**  **tate a** 

a N on

- 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 E**  **stimated T**  **echnical P**  **otential for O**  **ffshore W**  **ind P**  **ower by S**  **tate a** 

a N on

- 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 E**  **stimated T**  **echnical P**  **otential for B**  **iopower by**  **S tate**  **a**

a N on

- excluded land was assumed to be available to support development of more than one technology . A ll 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 St ates

**Table 9. Total E**  **stimated T**  **echnical P**  **otential for Hydrothermal P**  **ower by**  **State a** 

a N on

- 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 E**  **stimated T**  **echnical P**  **otential for E**  **nhanced G**  **eothermal S**  **ystems by**  **S tate**  **a**

a N on

- 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 E**  **stimated T**  **echnical P**  **otential for H**  **ydropower by State**  **a**

a N on

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

.

### 20 

## Discussion

Table 12 summarize s 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 e xisting or planned transmission infrastructure that is necessary to tie generation into the electricity grid

• T he 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**  **E stimated**  **T echnical**  **P otential**  **G eneration and**  **C apacity 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 Biopower b 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 c onsidered. 

### 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

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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. Gol den, 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/TM

2011/224. Oak Ridge, TN : Oak Ri dge 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.g ov/ 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.

Hal l, 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 21 st 

### 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: T he 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 S ystem (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 Ra diation 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 U rban**  **U tility**  **-S cale**  **Photovoltaics**

Slope Exclusion > 3%
Contiguous Area Exclusion < 0.018 km 2

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 F**  **actors for U**  **tility -S**  **cale Photovoltaics**  **a**

State Capacity Factor State CapacityFactor 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 R ural**  **U tility**  **-S cale**  **P hotovoltaics and**  **Concentrating Solar P**  **ower**
Slope Exclusion > 3%
Contiguous Area Exclusion < 1 km 2

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 F**  **actors for Concentrating Solar P**  **ower a** 

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 O nshore**  **W ind**  **P ower** 
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 (non

cumulative 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 F**  **actor for O**  **ffshore W**  **ind P**  **owe r**  **a**
Depth Class Watts/m 2 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 W**  **ind S**  **peed s**  **at 90**  **M eter**  **s to P ower**  **C lass**  **es a** 
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, p ersonal c ommunication

### 29 **Table A-8.**  **Exclusions and**  **Constraints for O ffshore**  **W ind**  **P ower**  **a**

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**  **C onstraints for**  **E nhanced**  **G eothermal**  **S ystems**  **a**
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 D**  **ensities for E**  **nhanced G**  **eothermal S**  **ystems a** 
Temperature C MW / km 2

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**

**. E**  **xclusio ns and**  **C onstraints for**  **E nhanced**  **G eothermal**  **S ystems**  **a**
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

Elect ric 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 20 10 (EIA)

. **Table B-1** 

**. Electric**  **R etail**  **S ales**  **by S**  **tate ,**  **2010 a** 

a EIA