Dataset for Evaluating the Impact of Wildfire Smoke on Solar Photovoltaic Production
Abstract
This dataset was used to support machine learning model development for wildfire impacts on utility-scale solar in the United States. The dataset includes information regarding energy generation, PM2.5, clearness index, temperature, wind speed, precipitation, and site size.
- Authors:
-
- Sandia National Laboratories
- Publication Date:
- Other Number(s):
- 5862
- Research Org.:
- DOE Open Energy Data Initiative (OEDI); Sandia National Laboratories
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)
- Collaborations:
- Sandia National Laboratories
- Subject:
- Array; Excel; PM2.5; PV; energy; processed data; raw data; solar energy; solar photovoltaic; wildfire risk
- OSTI Identifier:
- 1988650
- DOI:
- https://doi.org/10.25984/1988650
Citation Formats
Gilletly, Samuel, Jackson, Nicole, and Staid, Andrea. Dataset for Evaluating the Impact of Wildfire Smoke on Solar Photovoltaic Production. United States: N. p., 2023.
Web. doi:10.25984/1988650.
Gilletly, Samuel, Jackson, Nicole, & Staid, Andrea. Dataset for Evaluating the Impact of Wildfire Smoke on Solar Photovoltaic Production. United States. doi:https://doi.org/10.25984/1988650
Gilletly, Samuel, Jackson, Nicole, and Staid, Andrea. 2023.
"Dataset for Evaluating the Impact of Wildfire Smoke on Solar Photovoltaic Production". United States. doi:https://doi.org/10.25984/1988650. https://www.osti.gov/servlets/purl/1988650. Pub date:Mon May 15 04:00:00 UTC 2023
@article{osti_1988650,
title = {Dataset for Evaluating the Impact of Wildfire Smoke on Solar Photovoltaic Production},
author = {Gilletly, Samuel and Jackson, Nicole and Staid, Andrea},
abstractNote = {This dataset was used to support machine learning model development for wildfire impacts on utility-scale solar in the United States. The dataset includes information regarding energy generation, PM2.5, clearness index, temperature, wind speed, precipitation, and site size.},
doi = {10.25984/1988650},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon May 15 04:00:00 UTC 2023},
month = {Mon May 15 04:00:00 UTC 2023}
}
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