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Seedling Project Report: A Novel Heat Pump Integrated Underground Thermal Energy Storage for Shaping Electric Demand of Buildings

This report presents a preliminary assessment of the technical feasibility of utilizing underground thermal energy storage (UTES) and electric-driven heat pumps (EDHPs) to enable flexible behind-the-meter electric demand of buildings while meeting their thermal demands in an energ...

Liu, X. et al Oak Ridge National Laboratory

May 31, 2019
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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
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Dataset and SUTRA model used to evaluate Reservoirs for Thermal Energy Storage in the Portland Basin, Oregon.

This is a link to the open access, published dataset and modeling that supports a feasibility study of Reservoir Thermal Energy Storage (RTES) in the Portland Basin, Oregon, USA. Citation: Burns, E.R., 2020, SUTRA model used to evaluate Saline or Brackish Aquifers as Reservoirs f...

Bershaw, J. et al Portland State University

Jun 29, 2020
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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
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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
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