The U.S. Department of Energy Geothermal Vision (GeoVision) Study is currently looking at the potential to increase geothermal deployment in the U.S. and to understand the impact of this increased deployment. This paper reviews 31 performance, cost, and financial parameters as input for numerical simulations describing GDH system deployment in support of the GeoVision effort. The focus is on geothermal district heating (GDH) systems using hydrothermal and Enhanced Geothermal System resources in the U.S.; ground-source heat pumps and heat-to-electricity conversion technology were excluded. Parameters investigated include: 1) capital and operation and maintenance costs for both subsurface and surface equipment; 2) performance factors such as resource recovery factors, well flow rates, and system efficiencies; and 3) financial parameters such as inflation, interest, and tax rates. Current values as well as potential future improved values under various scenarios are presented. Sources of data considered include academic and popular literature, software tools such as GETEM and GEOPHIRES, industry interviews, and analysis conducted by other task forces for the GeoVision Study, e.g., on the drilling costs and reservoir performance.

This dataset contains all the inputs used and output produced from the modified GEOPHIRES for the economic analysis of base case hybrid GDHC system, improved hybrid GDHC system with heat pump and for hot water GDHC. Software required: Microsoft Notepad, Microsoft Excel and GEOPHIRES modified source code

This submission includes input and results data from analysis done as part of the Geothermal Technology Office's Geothermal Vision Study (GeoVision). The submission includes data for both analysis of the electricity sector and the heating and cooling sector. For the electricity sector, the submission includes geothermal resource potential and development cost inputs for the ReEDS model and ReEDS model results of projected installed capacity and generation of geothermal and other technologies under the GeoVision scenarios. It also includes results from environmental and social impacts analysis. For the cooling sector, the submission includes geothermal resource potential and development cost inputs for the dGeo model and dGeo model results of economic, market, and deployment potential.

This submission includes input and results data from analysis done as part of the Geothermal Technology Office's Geothermal Vision Study (GeoVision). The submission includes data for both analysis of the electricity sector and the heating and cooling sector. For the electricity sector, the submission includes geothermal resource potential and development cost inputs for the ReEDS model and ReEDS model results of projected installed capacity and generation of geothermal and other technologies under the GeoVision scenarios. It also includes results from environmental and social impacts analysis. For the cooling sector, the submission includes geothermal resource potential and development cost inputs for the dGeo model and dGeo model results of economic, market, and deployment potential.

Data included in this submission support the analysis conducted for the report "Nontechnical Barriers to Geothermal Development" which is linked bellow. These data include information about the power purchase agreements (PPAs) analyzed for the report, inputs and model results for the pro forma economic analysis, and outputs from the regression analysis conducted on PPAs comparing geothermal and other power generation technologies.

Data included in this submission support the analysis conducted for the report "Nontechnical Barriers to Geothermal Development" which is linked bellow. These data include information about the power purchase agreements (PPAs) analyzed for the report, inputs and model results for the pro forma economic analysis, and outputs from the regression analysis conducted on PPAs comparing geothermal and other power generation technologies.

This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production from two potential geothermal reservoirs that were evaluated for the Cornell University Deep Direct-Use project. These potential reservoirs are the Trenton-Black River (TBR) from 2.27-2.3 km depth, and basement rocks from 3.0-3.5 km depth and 3.5-4.0 km depth. Several utilization scenarios consisting of different injection fluid temperatures and flow rates were evaluated for each reservoir. Uncertainty in geologic properties, thermal properties, economic costs, and utilization efficiencies were evaluated using a Monte Carlo analysis of the reservoir simulations. Some reservoir simulations of the TBR were completed using the TOUGH2 software, as implemented in PetraSIM. The PetraSIM run files and associated data are provided with this submission. All other reservoir simulations were completed using the GEOPHIRES software, with some modifications to complete the uncertainty analyses. ReadMe files that describe additions to GEOPHIRES, the GEOPHIRES input data, and the output data are all provided, and references are provided to the code repository. Figures that summarize the reservoir heat production, temperature drawdown, and the probability of meeting targeted building heating demands with the produced heat and fluid temperatures are provided.

This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production from two potential geothermal reservoirs that were evaluated for the Cornell University Deep Direct-Use project. These potential reservoirs are the Trenton-Black River (TBR) from 2.27-2.3 km depth, and basement rocks from 3.0-3.5 km depth and 3.5-4.0 km depth. Several utilization scenarios consisting of different injection fluid temperatures and flow rates were evaluated for each reservoir. Uncertainty in geologic properties, thermal properties, economic costs, and utilization efficiencies were evaluated using a Monte Carlo analysis of the reservoir simulations. Some reservoir simulations of the TBR were completed using the TOUGH2 software, as implemented in PetraSIM. The PetraSIM run files and associated data are provided with this submission. All other reservoir simulations were completed using the GEOPHIRES software, with some modifications to complete the uncertainty analyses. ReadMe files that describe additions to GEOPHIRES, the GEOPHIRES input data, and the output data are all provided, and references are provided to the code repository. Figures that summarize the reservoir heat production, temperature drawdown, and the probability of meeting targeted building heating demands with the produced heat and fluid temperatures are provided.

This spreadsheet with US geothermal district heating system data includes the system year, location, size, cost, technical specs and funding sources.