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US Geothermal Electricity and Heat Market Analysis and Report

The power production data from FY19 is provided for U.S. geothermal power plants. The spreadsheet includes the plant name and type, nameplate capacity, summer capacity, winter capacity, and net generation for each power plant.

Robins, J. et al National Renewable Energy Laboratory

Jun 30, 2020
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GRC 2019 Initial Results Presentation

The Report is being developed by NREL and the GRC, with financial support from the Geothermal Technologies Office of the U.S. DOE and the GRC. It is intended to provide geothermal policymakers, regulators, developers, researchers, and other stakeholders with up-to-date information...

Robins, J. National Renewable Energy Laboratory

Oct 01, 2020
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Geothermal Project Database Supporting Barriers and Viability Analysis for Development by 2020 Timeline

This data provides the underlying project-level analysis and data sources complied in response to the DOE request to determine the amount of geothermal capacity that could be available to meet the President's request to double renewable energy capacity by 2020. The enclosed dat...

Wall, A. and Young, K. National Renewable Energy Laboratory

Oct 21, 2014
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Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data

EIA previously collected sales and revenue data in a category called "Other." This category was defined as including activities such as public street highway lighting, other sales to public authorities, sales to railroads and railways, and interdepartment...

Aabakken, J. and Laboratory, N. National Renewable Energy Laboratory

Nov 25, 2014
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In curation

GEOPHIRES Simulations for Deep Direct Use (DDU) Projects

This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investiga...

Beckers, K. National Renewable Energy Laboratory

Jun 30, 2020
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...

Beckers, K. et al National Renewable Energy Laboratory

Feb 18, 2021
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...