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 and underground thermal energy storage 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, ground heat exchanger sizing with GHEDesigner, subsurface thermal storage modeling using SUTRA, and economic assessment through unified cost modeling. 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. These materials provide a complete foundation for replicating the study results.

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 and underground thermal energy storage 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, ground heat exchanger sizing with GHEDesigner, subsurface thermal storage modeling using SUTRA, and economic assessment through unified cost modeling. 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. These materials provide a complete foundation for replicating the study results. AU - Mello, Scott A2 - Oh, Hyunjun A3 - Trainor-Guitton, Whitney A4 - Cahalan, Ryan A5 - Pepin, Jeffrey A6 - Burns, Erick DB - Geothermal Data Repository DP - Open EI | National Renewable Energy Laboratory 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 - UTES simulation KW - GeoTES LA - English DA - 2025/09/27 PY - 2025 PB - National Renewable Energy Laboratory 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 Renewable Energy Laboratory, 27 September, 2025, Geothermal Data Repository. https://gdr.openei.org/submissions/1795.
Mello, S., Oh, H., Trainor-Guitton, W., Cahalan, R., Pepin, J., & Burns, E. (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 Renewable Energy Laboratory. https://gdr.openei.org/submissions/1795
Mello, Scott, Hyunjun Oh, Whitney Trainor-Guitton, Ryan Cahalan, Jeffrey Pepin, and Erick Burns. District Geothermal Energy Systems with Seasonal Underground Thermal Storage: Load Profiles, Modeling Workflow, and Techno-Economic Results for U.S. Screening. National Renewable Energy Laboratory, 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 and Cahalan, Ryan and Pepin, Jeffrey and Burns, Erick}, 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 and underground thermal energy storage 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, ground heat exchanger sizing with GHEDesigner, subsurface thermal storage modeling using SUTRA, and economic assessment through unified cost modeling. 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. These materials provide a complete foundation for replicating the study results.}, url = {https://gdr.openei.org/submissions/1795}, year = {2025}, howpublished = {Geothermal Data Repository, National Renewable Energy Laboratory, https://gdr.openei.org/submissions/1795}, note = {Accessed: 2025-10-06} }

Details

Data from Sep 27, 2025

Last updated Sep 28, 2025

Submission in progress

Organization

National Renewable Energy Laboratory

Contact

Scott Mello

Authors

Scott Mello

National Renewable Energy Laboratory

Hyunjun Oh

National Renewable Energy Laboratory

Whitney Trainor-Guitton

National Renewable Energy Laboratory

Ryan Cahalan

United States Geological Survey

Jeffrey Pepin

United States Geological Survey

Erick Burns

United States Geological Survey

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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