District Geothermal Energy Systems with Seasonal Underground Thermal Storage: Load Profiles, Modeling Workflow, and Techno-Economic Results for U.S. Screening
This dataset accompanies the paper "Geothermal district energy systems coupled with seasonal underground thermal energy storage: a U.S. techno-economic screening by climate and geology." It contains the data and scripts required to reproduce the study's results across ten U.S. cities, where ground heat exchangers (GHEs_ and underground thermal energy storage (UTES) were modeled to assess district-scale heating and cooling performance. The dataset includes Python scripts implementing the workflow described in the paper, county-level building load profiles derived from ComStock data, SUTRA inputs and outputs for aquifer and reservoir thermal energy storage simulations, and a comprehensive technical and cost results summary.
The workflow integrates standardized load aggregation, GHE sizing with GHEDesigner, subsurface thermal storage modeling using SUTRA, and economic assessment through unified cost modeling. The specific configuration modeled here has the GHE supplying district heating and an equal share of cooling, with the UTES system (either Aquifer- or Reservoir- TES) supplying the remaining cooling load. Intermediate and final outputs are structured so that the workflow can be rerun or modified for different cities, system configurations, or parameter assumptions. The dataset also links to a supporting U.S. Geological Survey data release that documents the SUTRA framework and provides additional model files and reference simulations.
Citation Formats
TY - DATA
AB - This dataset accompanies the paper "Geothermal district energy systems coupled with seasonal underground thermal energy storage: a U.S. techno-economic screening by climate and geology." It contains the data and scripts required to reproduce the study's results across ten U.S. cities, where ground heat exchangers (GHEs_ and underground thermal energy storage (UTES) were modeled to assess district-scale heating and cooling performance. The dataset includes Python scripts implementing the workflow described in the paper, county-level building load profiles derived from ComStock data, SUTRA inputs and outputs for aquifer and reservoir thermal energy storage simulations, and a comprehensive technical and cost results summary.
The workflow integrates standardized load aggregation, GHE sizing with GHEDesigner, subsurface thermal storage modeling using SUTRA, and economic assessment through unified cost modeling. The specific configuration modeled here has the GHE supplying district heating and an equal share of cooling, with the UTES system (either Aquifer- or Reservoir- TES) supplying the remaining cooling load. Intermediate and final outputs are structured so that the workflow can be rerun or modified for different cities, system configurations, or parameter assumptions. The dataset also links to a supporting U.S. Geological Survey data release that documents the SUTRA framework and provides additional model files and reference simulations.
AU - Mello, Scott
A2 - Oh, Hyunjun
A3 - Trainor-Guitton, Whitney
DB - Geothermal Data Repository
DP - Open EI | National Laboratory of the Rockies
DO -
KW - geothermal
KW - energy
KW - district energy systems
KW - underground thermal energy storage
KW - UTES
KW - ATES
KW - RTES
KW - ground heat exchanger
KW - GHE
KW - SUTRA
KW - techo-economic analysis
KW - energy modeling
KW - ComStock
KW - building load profiles
KW - LCOE
KW - aquifer storage
KW - seasonal storage
KW - U.S. cities
KW - Python
KW - model
KW - scripts
KW - model data
KW - subsurface simulation
KW - GeoTES
LA - English
DA - 2025/09/27
PY - 2025
PB - National Laboratory of the Rockies
T1 - District Geothermal Energy Systems with Seasonal Underground Thermal Storage: Load Profiles, Modeling Workflow, and Techno-Economic Results for U.S. Screening
UR - https://gdr.openei.org/submissions/1795
ER -
Mello, Scott, et al. District Geothermal Energy Systems with Seasonal Underground Thermal Storage: Load Profiles, Modeling Workflow, and Techno-Economic Results for U.S. Screening. National Laboratory of the Rockies, 27 September, 2025, Geothermal Data Repository. https://gdr.openei.org/submissions/1795.
Mello, S., Oh, H., & Trainor-Guitton, W. (2025). District Geothermal Energy Systems with Seasonal Underground Thermal Storage: Load Profiles, Modeling Workflow, and Techno-Economic Results for U.S. Screening. [Data set]. Geothermal Data Repository. National Laboratory of the Rockies. https://gdr.openei.org/submissions/1795
Mello, Scott, Hyunjun Oh, and Whitney Trainor-Guitton. District Geothermal Energy Systems with Seasonal Underground Thermal Storage: Load Profiles, Modeling Workflow, and Techno-Economic Results for U.S. Screening. National Laboratory of the Rockies, September, 27, 2025. Distributed by Geothermal Data Repository. https://gdr.openei.org/submissions/1795
@misc{GDR_Dataset_1795,
title = {District Geothermal Energy Systems with Seasonal Underground Thermal Storage: Load Profiles, Modeling Workflow, and Techno-Economic Results for U.S. Screening},
author = {Mello, Scott and Oh, Hyunjun and Trainor-Guitton, Whitney},
abstractNote = {This dataset accompanies the paper "Geothermal district energy systems coupled with seasonal underground thermal energy storage: a U.S. techno-economic screening by climate and geology." It contains the data and scripts required to reproduce the study's results across ten U.S. cities, where ground heat exchangers (GHEs_ and underground thermal energy storage (UTES) were modeled to assess district-scale heating and cooling performance. The dataset includes Python scripts implementing the workflow described in the paper, county-level building load profiles derived from ComStock data, SUTRA inputs and outputs for aquifer and reservoir thermal energy storage simulations, and a comprehensive technical and cost results summary.
The workflow integrates standardized load aggregation, GHE sizing with GHEDesigner, subsurface thermal storage modeling using SUTRA, and economic assessment through unified cost modeling. The specific configuration modeled here has the GHE supplying district heating and an equal share of cooling, with the UTES system (either Aquifer- or Reservoir- TES) supplying the remaining cooling load. Intermediate and final outputs are structured so that the workflow can be rerun or modified for different cities, system configurations, or parameter assumptions. The dataset also links to a supporting U.S. Geological Survey data release that documents the SUTRA framework and provides additional model files and reference simulations. },
url = {https://gdr.openei.org/submissions/1795},
year = {2025},
howpublished = {Geothermal Data Repository, National Laboratory of the Rockies, https://gdr.openei.org/submissions/1795},
note = {Accessed: 2026-05-10}
}
Details
Data from Sep 27, 2025
Last updated Apr 22, 2026
Submitted Apr 22, 2026
Organization
National Laboratory of the Rockies
Contact
Scott Mello
Authors
Keywords
geothermal, energy, district energy systems, underground thermal energy storage, UTES, ATES, RTES, ground heat exchanger, GHE, SUTRA, techo-economic analysis, energy modeling, ComStock, building load profiles, LCOE, aquifer storage, seasonal storage, U.S. cities, Python, model, scripts, model data, subsurface simulation, GeoTESDOE Project Details
Project Name FLXenabler - Flexible heating and cooling and geothermal energy storage as an enabler for decarbonized integrated energy systems
Project Lead Arlene Anderson
Project Number FY25 AOP 4.1.3.3

