Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States
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.
Citation Formats
Sandia National Laboratories. (2021). Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States [data set]. Retrieved from https://dx.doi.org/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: N.p., 01 Apr, 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. https://dx.doi.org/10.25984/1812011
Gunda, Thushara, Jackson, Nicole. 2021. "Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States". United States. https://dx.doi.org/10.25984/1812011. https://data.openei.org/submissions/4055.
@div{oedi_4055, title = {Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States}, author = {Gunda, Thushara, 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}, url = {https://data.openei.org/submissions/4055}, journal = {}, number = , volume = , place = {United States}, year = {2021}, month = {04}}
https://dx.doi.org/10.25984/1812011
Details
Data from Apr 1, 2021
Last updated Jun 14, 2024
Submitted Apr 1, 2021
Organization
Sandia National Laboratories
Contact
Thushara Gunda
505.845.3440
Authors
Research Areas
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 zoneDOE Project Details
Project Name Operation and Maintenance of PV Systems: Data Science, Analysis, and Standards
Project Number 34172
