U.S. Department of EnergyOffice of Scientific and Technical Information
Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States
Abstract
This dataset is a fusion of three data types (operations and maintenance tickets, weather data, and production data) that was used to support machine learning analysis and evaluation of drivers for low performance at photovoltaic (PV) sites during compound, extreme weather events. After being processed with machine learning, the data was used in the "Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States" manuscript. Additional details are captured in the associated manuscript.
- Publication Date:
- Other Number(s):
- 4055
- DOE Contract Number:
- 34172
- Research Org.:
- DOE Open Energy Data Initiative (OEDI); Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)
- Collaborations:
- Sandia National Laboratories
- Subject:
- Array
- Keywords:
- energy; power; pv; extreme weather; machine learning; data fusion; maintenance; hurricanes; snow; storm; photovoltaic; AI; artificial intelligence; solar; weather; data; production; analysis; wind; wind speed; rain; flood; flooding; lightning; climate region; temperature zone; humidity zone
- Geolocation:
- 48.802706834292,-67.8941|30.202354530849,-67.8941|30.202354530849,-125.1877|48.802706834292,-125.1877|48.802706834292,-67.8941
- OSTI Identifier:
- 1812011
- DOI:
- https://doi.org/10.25984/1812011
- Project Location:
-
Citation Formats
Gunda, Thushara, and Jackson, Nicole. Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States. United States: N. p., 2021.
Web. doi:10.25984/1812011.
Gunda, Thushara, & Jackson, Nicole. Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States. United States. doi:https://doi.org/10.25984/1812011
Gunda, Thushara, and Jackson, Nicole. 2021.
"Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States". United States. doi:https://doi.org/10.25984/1812011. https://www.osti.gov/servlets/purl/1812011. Pub date:Thu Apr 01 00:00:00 EDT 2021
@article{osti_1812011,
title = {Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States},
author = {Gunda, Thushara and Jackson, Nicole},
abstractNote = {This dataset is a fusion of three data types (operations and maintenance tickets, weather data, and production data) that was used to support machine learning analysis and evaluation of drivers for low performance at photovoltaic (PV) sites during compound, extreme weather events. After being processed with machine learning, the data was used in the "Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States" manuscript. Additional details are captured in the associated manuscript.},
doi = {10.25984/1812011},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2021},
month = {4}
}
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