Related Datasets

Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results

Publicly accessible License

This dataset contains the results of a study conducted by the National Renewable Energy Laboratory (NREL) to identify potential future priority geothermal leasing areas on Bureau of Land Management (BLM) and United States Forest Service (USFS) lands. The analysis uses the Regional Energy Deployment System (ReEDS) model to evaluate geothermal resource potential under different scenarios of resource depth and technology combinations through the year 2050. The study considers geothermal resource potential, natural resource conflicts, and transmission access to categorize areas into near, mid, and far deployment priorities.

The dataset includes outputs from the ReEDS model, such as geothermal capacity, generation, system costs, and emissions under various economic and technical scenarios. Favorability site data with geographic coordinates and site-specific attributes (e.g., resource favorability, land type) are also provided. Supporting resources include a technical report detailing methodologies and assumptions, along with a link to the ReEDS model GitHub repository, which requires GAMS and Python software for execution.

Associated Technical Report

This report describes the methodology, analysis, and results of the study, including identification of high-priority geothermal leasing areas and their economic potenti... more

View

Favorability Sites.xlsx

This file includes data on potential geothermal leasing sites, categorized by favorability levels (near, mid, and far priorities), with geographic coordinates and wheth... more

Download 38.07 kB

ReEDS Model GitHub

Python GAMS

This link provides access to the ReEDS model repository, which includes the full model code, documentation, and input data required to replicate the analysis. The repos... more

View Repository

ReEDS Results.xlsx

This file contains model outputs from the ReEDS system, providing scenarios for geothermal energy deployment, including generation, capacity, system costs, electricity ... more

Download 821.05 kB

Citation Formats

National Renewable Energy Laboratory. (2024). Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results [data set].  Retrieved from https://gdr.openei.org/submissions/1604.

Export Citation to RIS

Smith, Faith, Ho, Jonathan, Trainor-Guitton, Whitney, Thomson, Sophie-Min, Smith, Ligia E. P., and Heimiller, Donna. Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results. United States: N.p., 20 May, 2024. Web. https://gdr.openei.org/submissions/1604.

Smith, Faith, Ho, Jonathan, Trainor-Guitton, Whitney, Thomson, Sophie-Min, Smith, Ligia E. P., & Heimiller, Donna. Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results. United States. https://gdr.openei.org/submissions/1604

Smith, Faith, Ho, Jonathan, Trainor-Guitton, Whitney, Thomson, Sophie-Min, Smith, Ligia E. P., and Heimiller, Donna. 2024. "Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results". United States.  https://gdr.openei.org/submissions/1604.

@div{oedi_8320, title = {Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results}, author = {Smith, Faith, Ho, Jonathan, Trainor-Guitton, Whitney, Thomson, Sophie-Min, Smith, Ligia E. P., and Heimiller, Donna.}, abstractNote = {This dataset contains the results of a study conducted by the National Renewable Energy Laboratory (NREL) to identify potential future priority geothermal leasing areas on Bureau of Land Management (BLM) and United States Forest Service (USFS) lands. The analysis uses the Regional Energy Deployment System (ReEDS) model to evaluate geothermal resource potential under different scenarios of resource depth and technology combinations through the year 2050. The study considers geothermal resource potential, natural resource conflicts, and transmission access to categorize areas into near, mid, and far deployment priorities.



The dataset includes outputs from the ReEDS model, such as geothermal capacity, generation, system costs, and emissions under various economic and technical scenarios. Favorability site data with geographic coordinates and site-specific attributes (e.g., resource favorability, land type) are also provided. Supporting resources include a technical report detailing methodologies and assumptions, along with a link to the ReEDS model GitHub repository, which requires GAMS and Python software for execution.}, doi = {}, url = {https://gdr.openei.org/submissions/1604}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {05}}

Details

Data from May 20, 2024

Last updated Jan 23, 2025

Submitted May 29, 2024