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Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak
The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model:
brady_som_output.gri, brady_som_output.grd, brady_som_output.*
desert_som_output.gri, desert_som_output.grd, desert_som_outpu...
Moraga, J. et al Colorado School of Mines
Sep 01, 2020
16 Resources
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Publicly accessible
16 Resources
0 Stars
Publicly accessible
Low Temperature Geothermal Resource Assessment for Desalination in United States
This data is a compilation of well observations from the Southern Methodist University (SMU) and Association of American State Geologists (AASG), location of identified low temperature geothermal systems from United States Geological Survey (USGS), and low temperature geothermal w...
Akar, S. and Turchi, C. National Renewable Energy Laboratory
Sep 30, 2016
6 Resources
0 Stars
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6 Resources
0 Stars
Publicly accessible
Appendices for Geothermal Exploration Artificial Intelligence Report
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Duzgun, H. et al Colorado School of Mines
Jan 08, 2021
12 Resources
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12 Resources
0 Stars
Publicly accessible
ARPA-E Grid Optimization (GO) Competition Challenge 2
The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and l...
Elbert, S. et al Pacific Northwest National Laboratory
Sep 20, 2024
29 Resources
0 Stars
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29 Resources
0 Stars
Publicly accessible
Low-Income Energy Affordability Data LEAD Tool 2018 Update
The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low and moderate-income (LMI) communities t...
Ma, O. U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy
Jul 01, 2020
57 Resources
0 Stars
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57 Resources
0 Stars
Publicly accessible
Low-Income Energy Affordability Data LEAD Tool 2022 Update
The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low and moderate-income (LMI) communities t...
Ma, O. and Vimont, A. U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy
Aug 01, 2024
63 Resources
0 Stars
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63 Resources
0 Stars
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Efficiency and Demand Flexibility in Large Office Buildings
Data is associated with Report "Efficiency and Demand Flexibility in Large Office Buildings" by Joyce McLaren, Thomas Bowen, and Chioke Harris (https://doi.org/10.2172/1989231). Results are created from repos GEB_ECM_Impact_Estimator (https://github.nrel.gov/tbowen/GEB_ECM_Impact_...
McLaren, . et al National Renewable Energy Laboratory
Jan 13, 2023
51 Resources
0 Stars
Publicly accessible
51 Resources
0 Stars
Publicly accessible