District Geothermal Energy Systems with Seasonal Underground Thermal Storage: Load Profiles, Modeling Workflow, and Techno-Economic Results for U.S. Screening

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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 -
Export Citation to RIS
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

Scott Mello

National Laboratory of the Rockies

Hyunjun Oh

National Laboratory of the Rockies

Whitney Trainor-Guitton

National Laboratory of the Rockies

DOE 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

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