Description
This data packet contains supply curves and a composite siting exclusion TIFF for EGS and hydrothermal geothermal across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE), levelized cost of transmission (LCOT), and more for each reV site. The composite exclusion TIFF is a single file that delineates areas where geothermal installations are permissible based on various siting assumptions. This data packet contains information for a single scenario across four depths and two technologies (enhanced geothermal systems and hydrothermal).
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| Geothermal Standard Scenarios 2024 Carto Map | HTML | The data contained in this map use the 2035 ATB costs | Open resource |
| EGS 4500m Supply Curve.csv | CSV | Enhanced Geothermal Systems at 4500 m depth | Open resource |
| EGS 5500m Supply Curve.csv | CSV | Enhanced Geothermal Systems at 5500 m depth | Open resource |
| EGS 6500m Supply Curve.csv | CSV | Enhanced Geothermal Systems at 6500 m depth | Open resource |
| Geothermal reV Supply Curve Column Lookup.csv | CSV | Contains the names and descriptions of the columns contained within the supply curves. | Open resource |
| Hydrothermal 3500m Supply Curve.csv | CSV | Hydrothermal at 3500 m depth | Open resource |
| Standard Exclusions Geothermal Map.png | PNG | Map showing the exclusion areas used for the standard scenarios geothermal runs | Open resource |
| Standard Scenarios Exclusions.tif | TIFF | Contains a composite exclusions map of the exclusions used in the 2024 standard scenarios geothermal reV runs. | Open resource |
| Renewable Energy Technical Potential and Supply Curves for the Contiguous United States | 2024 Edition | Open resource | |
| Development of a Geothermal Module in reV | This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. | Open resource |