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Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...
Jin, W. et al Idaho National Laboratory
Apr 15, 2022
4 Resources
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Dynamic Earth Energy Storage: Terawatt-year, Grid-scale Energy Storage Using Planet Earth as a Thermal Battery (GeoTES): Phase I Project Final Report

Final report for the DOE GTO funded research on geologic thermal energy storage (GeoTES), or commonly known as reservoir thermal energy storage (RTES). The results described in this report shed light on various aspects of RTES including project siting, operational performance, m...
Atkinson, T. et al Idaho National Laboratory
Sep 02, 2022
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Elevation Grid for top Columbia River Basalt (CRBG) in the Portland Basin used in DDU Feasibility Study

The Portland Basin is a prime location to assess the feasibility of DDU-TES because natural geologic conditions provide thermal and hydraulic separation from overlying aquifers that would otherwise sweep away stored heat. Under the Portland Basin, the lower Columbia River Basalt G...
Bershaw, J. and Scanlon, D. Portland State University
Dec 01, 2018
5 Resources
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Dynamic Earth Energy Storage: Terawatt-Year, Grid-Scale Energy Storage using Planet Earth as a Thermal Battery (GeoTES): Seedling Project Final Report

Grid-scale energy storage has been identified as a needed technology to support the continued build-out of intermittent renewable energy resources. As of April 2017, the U.S. had approximately 24.2 GW of energy storage on line, compared to 1,081 GW of installed generation capacity...
McLing, T. et al Idaho National Laboratory
May 31, 2019
11 Resources
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