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

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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 National Renewable Energy Laboratory (NREL), dGeo is a geospatially resolved, bottom-up modeling framework designed to explore the deployment potential of geothermal distributed energy resources.

The dataset, created as part of the Cornell EGS Ground-Truthing Project, provides census tract-level data that includes inputs and outputs such as thermal demand, road length, energy prices, geothermal system sizing, annual energy contributions from geothermal and natural gas peaking boilers, system capital costs (CAPEX), operation and maintenance costs (OPEX), and the levelized cost of heat (LCOH). Key simulation parameters include geothermal gradients, measured well depths, production temperatures, and district heating piping lengths based on S1400 neighborhood road lengths. The simulations assume a target bottom hole temperature of 80C and the development of new district heating networks in each census tract.

Citation Formats

TY - DATA AB - 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 National Renewable Energy Laboratory (NREL), dGeo is a geospatially resolved, bottom-up modeling framework designed to explore the deployment potential of geothermal distributed energy resources. The dataset, created as part of the Cornell EGS Ground-Truthing Project, provides census tract-level data that includes inputs and outputs such as thermal demand, road length, energy prices, geothermal system sizing, annual energy contributions from geothermal and natural gas peaking boilers, system capital costs (CAPEX), operation and maintenance costs (OPEX), and the levelized cost of heat (LCOH). Key simulation parameters include geothermal gradients, measured well depths, production temperatures, and district heating piping lengths based on S1400 neighborhood road lengths. The simulations assume a target bottom hole temperature of 80C and the development of new district heating networks in each census tract. AU - Pauling, Hannah DB - Geothermal Data Repository DP - Open EI | National Renewable Energy Laboratory DO - 10.15121/2507420 KW - geothermal KW - energy KW - EGS KW - district heating KW - dGeo KW - TEA KW - techno-economic analsyis KW - feasibility KW - EGS feasibility KW - EGS direct use KW - deep direct use KW - DU KW - DDU KW - CAPEX KW - OPEX KW - LCOH KW - modeling KW - geothermal market demand KW - model KW - simulation KW - thermal demand KW - heating demand KW - district heating networks LA - English DA - 2024/09/30 PY - 2024 PB - National Renewable Energy Laboratory T1 - Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States UR - https://doi.org/10.15121/2507420 ER -
Export Citation to RIS
Pauling, Hannah. Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States. National Renewable Energy Laboratory, 30 September, 2024, Geothermal Data Repository. https://doi.org/10.15121/2507420.
Pauling, H. (2024). Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States. [Data set]. Geothermal Data Repository. National Renewable Energy Laboratory. https://doi.org/10.15121/2507420
Pauling, Hannah. Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States. National Renewable Energy Laboratory, September, 30, 2024. Distributed by Geothermal Data Repository. https://doi.org/10.15121/2507420
@misc{GDR_Dataset_1698, title = {Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States}, author = {Pauling, Hannah}, abstractNote = {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 National Renewable Energy Laboratory (NREL), dGeo is a geospatially resolved, bottom-up modeling framework designed to explore the deployment potential of geothermal distributed energy resources.

The dataset, created as part of the Cornell EGS Ground-Truthing Project, provides census tract-level data that includes inputs and outputs such as thermal demand, road length, energy prices, geothermal system sizing, annual energy contributions from geothermal and natural gas peaking boilers, system capital costs (CAPEX), operation and maintenance costs (OPEX), and the levelized cost of heat (LCOH). Key simulation parameters include geothermal gradients, measured well depths, production temperatures, and district heating piping lengths based on S1400 neighborhood road lengths. The simulations assume a target bottom hole temperature of 80C and the development of new district heating networks in each census tract.}, url = {https://gdr.openei.org/submissions/1698}, year = {2024}, howpublished = {Geothermal Data Repository, National Renewable Energy Laboratory, https://doi.org/10.15121/2507420}, note = {Accessed: 2025-04-24}, doi = {10.15121/2507420} }
https://dx.doi.org/10.15121/2507420

Details

Data from Sep 30, 2024

Last updated Jan 31, 2025

Submitted Dec 31, 2024

Organization

National Renewable Energy Laboratory

Contact

Koenraad Beckers

Authors

Hannah Pauling

National Renewable Energy Laboratory

DOE Project Details

Project Name Cornell EGS Ground Truthing Project

Project Lead Zachary Frone

Project Number FY25 AOP 5.4.3.1

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