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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...

Beckers, K. et al National Renewable Energy Laboratory

Oct 20, 2021
6 Resources
0 Stars
Publicly accessible

PV Rooftop Database for Puerto Rico (PVRDB-PR)

The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded a...

Mooney, M. and Waechter, K. National Renewable Energy Laboratory (NREL)

Dec 16, 2020
5 Resources
0 Stars
Curated

PV Rooftop Database

The National Renewable Energy Laboratory's (NREL) Photovoltaic (PV) Rooftop Database (PVRDB) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for 128 metropolitan regions in the United States. The PVRDB data are organized...

Mooney, M. National Renewable Energy Laboratory (NREL)

Jan 01, 2016
5 Resources
0 Stars
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National Solar Radiation Database (NSRDB)

The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations for 1998-2023. The NSRDB is updated annually and provides foundational information t...

Sengupta, M. et al National Renewable Energy Laboratory

Sep 28, 2018
7 Resources
2 Stars
Curated

National Climate Database (NCDB)

The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI) as well as other meteorological dat...

Yang, J. et al National Renewable Energy Laboratory (NREL)

Sep 30, 2024
5 Resources
0 Stars
Curated

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...

Siler, D. et al United States Geological Survey

Oct 01, 2021
6 Resources
0 Stars
Publicly accessible