Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results

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.

Data and Resources

Field Value
DOI 10.15121/2516751
accessLevel public
bureauCode {019:20}
catalog_@context https://openei.org/data.json
catalog_@id https://openei.org/data.json
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
dataQuality true
identifier https://data.openei.org/submissions/8320
issued 2024-05-20T06:00:00Z
landingPage https://gdr.openei.org/submissions/1604
license https://creativecommons.org/licenses/by/4.0/
modified 2025-02-14T21:03:43Z
old-spatial {"type":"Polygon","coordinates":[[[-125.4514,24.5873],[-66.5318,24.5873],[-66.5318,49.2637],[-125.4514,49.2637],[-125.4514,24.5873]]]}
programCode {019:006}
projectLead Sean Porse
projectNumber FY24 AOP 5.3.1.4
projectTitle Geothermal Leasing Analysis
publisher National Renewable Energy Laboratory
resource-type Dataset
source_datajson_identifier true
source_hash d41d4b711bc586169f7294dd81482c94635f3dacf231266260bb4cd6b3e6e0d7
source_schema_version 1.1
spatial {"type":"Polygon","coordinates":[[[-125.4514,24.5873],[-66.5318,24.5873],[-66.5318,49.2637],[-125.4514,49.2637],[-125.4514,24.5873]]]}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • blm
  • emissions
  • energy
  • feasibility
  • gams
  • generation
  • geothermal
  • geothermal-capacity
  • geothermal-leasing-areas
  • github
  • model-results
  • modeling
  • natural-resource-conflicts
  • priority-leasing
  • processed-data
  • python
  • reeds
  • renewable-energy-potential-model
  • resource-potential
  • system-cost
  • technical-report
  • technology-combination
  • transmission
  • usfs
isopen True
license_id cc-by
license_title Creative Commons Attribution
license_url http://www.opendefinition.org/licenses/cc-by
maintainer Sophie-Min Thomson
maintainer_email sophiemin.thomson@nrel.gov
metadata_created 2025-09-24T01:17:48.684714
metadata_modified 2025-09-24T01:17:48.684723
notes 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.
num_resources 4
num_tags 32
title Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results