OpenEI: Energy Information
  • Geothermal Data Repository
  • My User
    • Sign Up
    • Login
 
  • Data
    • View All Submissions
    • Data Lakes
    • Data Standards
    • Submit Data
  • Help
    • Frequently Asked Questions
    • Data Submission Best Practices
    • Data Submission Tutorial Videos
    • Contact GDR Help
  • About
  • Search

Search GDR Data

Showing results 1 - 6 of 6.
Show results per page.
Order by:
Available Now:
Filters Clear All Filters ×
Topic
Technologies
Demonstration Sites
Data Type
"levelized"×
EGS×

Enhanced Geothermal System (EGS) Suitability for Contiguous United States

Dec 01, 2025
527.64 kB
Publicly accessible
This data set includes maps of normalized LCOE all-in (Levelized Cost of Transmission [LCOT] inclusive) as calculated using NLR's Annual Technology Baseline (ATB) costs, both drilling and CAPEX/OPEX, and considering the best depth option (1-7 km) for each location across the conti...
Authors
Trainor-Guitton, W. et al National Laboratory of the Rockies
geothermalenergylcoelcotatbmapegsresource potentialcapexopexdrilling costsuitability maplevelized cost of transmissionlevelized cost of energyenhanced geothermalgeospatial dataraster datafavorabilityegs favorabilitymodel

United States Geothermal Supply Curves 2024

Apr 15, 2025
627.1 MB
Publicly accessible
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 ...
Authors
Trainor-Guitton, W. et al National Renewable Energy Laboratory
energypowerenergy analysisgeothermalegsenhanced geothermal systemshydrothermalrevsupply curvecost of energycost of transmissiongeothermal powerrev siting labssitinglabsiting labsupply curvesunited states2024hourly generationsitingcapacitygenerationpower profiles

Renewable Energy Potential Model: Geothermal Supply Curves

Aug 21, 2023
4.9 MB
Publicly accessible
The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmenta...
Authors
Trainor-Guitton, W. et al National Renewable Energy Laboratory
geothermalenergysmu temperaturessupply curvegeospatialgrid infrastructureexclusionslevelized cost of electricityegsoperating costsfeasibilitymodelrevhydrothermalcapital costsgeothermal location

Renewable Energy Potential Model: Hawaii Geothermal Supply Curves

Jan 13, 2025
102.89 kB
Publicly accessible
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 (E...
Authors
Trainor-Guitton, W. et al National Renewable Energy Laboratory
geothermalenergysupply curvegeospatialhawaiirevlevelized cost of energyhydrothermalcapital costgeothermal locationlcoeegspfaplay fairwaysimulationmodelmodel resultsheat mapbinary egsbinary hydrothermaltransmissiongrid connectiondevelopmentfeasibilityproduction metricssupply curves

Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States

Sep 30, 2024
3.1 MB
Publicly accessible
This dataset presents the results of techno-economic simulations performed using the Distributed Geothermal Market Demand Model (dGeo) to evaluate the feasibility of Enhanced Geothermal Systems (EGS)-based district heating in the Northeastern United States. Developed by the Nation...
Authors
Pauling, H. National Renewable Energy Laboratory
geothermalenergyegsdistrict heatingdgeoteatechno-economic analsyisfeasibilityegs feasibilityegs direct usedeep direct usedudducapexopexlcohmodelinggeothermal market demandmodelsimulationthermal demandheating demanddistrict heating networks

Sedimentary Geothermal Feasibility in Nevada, Western Utah, Colorado, and the Gulf Coast Region of Texas Final Report

Jul 01, 2020
Size unavailable
Publicly accessible
The objectives of this project were to (1) perform a literature review of sedimentary geothermal resources, (2) identify data sources and develop data-collection methodologies that characterize selected resources, (3) screen sedimentary basins and formations for sedimentary geothe...
Authors
Johnston, H. et al National Renewable Energy Laboratory
geothermalenergysedimentaryfeasibilitysedimentary basinelko basinrailroad valleysteptoe valleypavant buttedenver basinpiceance basinraton basingulf coast regionnevadautahtexasgbcaasgreat basin carbonate and alluvial aquifer systemcarbonateagsadvanced geothermal systembottom-hole temperaturewell datalcoeeconomicsupperlowercarbonate aquifer unitegsenhanced geothermal systemplay fairway analysiscoloradotemperaturebottom-holemarys river basindrillingpermeabilityreservoirmodelingcarbonate geothermal systemcgstechno-economicanalysisdownselectsubsurfacedata mininggeologygradientheatflowgeophysicsseismicclosed-loophydrogeologycoststructuralbedrockmapaquifersedgeo
Google Map
  • About the GDR
  • Partners & Sponsors
  • Disclaimers
  • Developer Services
  • The GDR provides free access to data generated from projects funded by the U.S. Department of Energy's Office of Geothermal.
  • Content is available under Creative Commons Attribution 4.0 unless otherwise noted.

Privacy Policy Notification

This site uses cookies to store and share user preferences with other OpenEI sites, and uses Google Analytics to collect anonymous user information such as which pages are visited, for how often, and what searches or other webpages may have led users here. You can prevent Google Analytics from recognizing you on return visits to this site by disabling cookies on your browser or by installing a Google Analytics Opt-out Browser Add-on. By clicking "Accept" you agree this site can store cookies on your device and disclose information to OpenEI and Google Analytics in accordance with our privacy policy.

OpenEI Privacy Policy Google Analytics Terms of Service