Renewable Energy Potential Model: Hawaii Geothermal Supply Curves

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This dataset extends the development of the Renewable Energy Potential (reV) model to include geothermal energy, with a specific focus on Hawaii. Provided here are the results of two scenarios that were modeled for geothermal energy in Hawaii: binary enhanced geothermal systems (EGS) at a depth of 2.5 km and hydrothermal binary systems at a depth of 1.5 km. The resource data for both scenarios were derived from Lautze & Haskins (2024) using an exponential method. The PFA probability of heat map was used as a look up table for which temperature gradient to use (Lautze & Haskins, 2024).

The dataset provides geospatial and techno-economic details for evaluating geothermal energy potential. It includes spatial coordinates, estimated capacity factors, developable area, resource potential, and annual energy production metrics. Economic details such as levelized cost of electricity (LCOE), site development costs, transmission costs, and fixed-charge rates are also included. The reV model, originally developed for wind and solar energy (Maclaurin et al., 2021), incorporates these variables to evaluate deployment constraints related to land use, environmental and cultural factors, and grid integration.

Citation Formats

National Renewable Energy Laboratory. (2025). Renewable Energy Potential Model: Hawaii Geothermal Supply Curves [data set]. Retrieved from https://gdr.openei.org/submissions/1702.
Export Citation to RIS
Trainor-Guitton, Whitney, Pinchuk, Paul, Olsson, Reid, and Maclaurin, Galen. Renewable Energy Potential Model: Hawaii Geothermal Supply Curves. United States: N.p., 13 Jan, 2025. Web. https://gdr.openei.org/submissions/1702.
Trainor-Guitton, Whitney, Pinchuk, Paul, Olsson, Reid, & Maclaurin, Galen. Renewable Energy Potential Model: Hawaii Geothermal Supply Curves. United States. https://gdr.openei.org/submissions/1702
Trainor-Guitton, Whitney, Pinchuk, Paul, Olsson, Reid, and Maclaurin, Galen. 2025. "Renewable Energy Potential Model: Hawaii Geothermal Supply Curves". United States. https://gdr.openei.org/submissions/1702.
@div{oedi_1702, title = {Renewable Energy Potential Model: Hawaii Geothermal Supply Curves}, author = {Trainor-Guitton, Whitney, Pinchuk, Paul, Olsson, Reid, and Maclaurin, Galen.}, abstractNote = {This dataset extends the development of the Renewable Energy Potential (reV) model to include geothermal energy, with a specific focus on Hawaii. Provided here are the results of two scenarios that were modeled for geothermal energy in Hawaii: binary enhanced geothermal systems (EGS) at a depth of 2.5 km and hydrothermal binary systems at a depth of 1.5 km. The resource data for both scenarios were derived from Lautze & Haskins (2024) using an exponential method. The PFA probability of heat map was used as a look up table for which temperature gradient to use (Lautze & Haskins, 2024).

The dataset provides geospatial and techno-economic details for evaluating geothermal energy potential. It includes spatial coordinates, estimated capacity factors, developable area, resource potential, and annual energy production metrics. Economic details such as levelized cost of electricity (LCOE), site development costs, transmission costs, and fixed-charge rates are also included. The reV model, originally developed for wind and solar energy (Maclaurin et al., 2021), incorporates these variables to evaluate deployment constraints related to land use, environmental and cultural factors, and grid integration.}, doi = {}, url = {https://gdr.openei.org/submissions/1702}, journal = {}, number = , volume = , place = {United States}, year = {2025}, month = {01}}

Details

Data from Jan 13, 2025

Last updated Jan 14, 2025

Submitted Jan 13, 2025

Organization

National Renewable Energy Laboratory

Contact

Sophie-Min Thomson

Authors

Whitney Trainor-Guitton

National Renewable Energy Laboratory

Paul Pinchuk

National Renewable Energy Laboratory

Reid Olsson

National Renewable Energy Laboratory

Galen Maclaurin

National Renewable Energy Laboratory

DOE Project Details

Project Name Enhanced representation of geothermal power potential in reV

Project Lead Sean Porse

Project Number FY25 AOP 5.4.2.3

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