Generating Synthetic Time Series PV Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation

Muller, Matthew; Deceglie, Michael; Anderson, Kevin

doi:10.21948/1999772

Title: Generating Synthetic Time Series PV Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation

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Abstract

The publication describes the generation of the synthetic PV time series data set for real locations in the US, including satellite irradiance, rainfall, and a number of physical challenges introduced within the data.

Authors:

Muller, Matthew; Deceglie, Michael; Anderson, Kevin

National Renewable Energy Laboratory (NREL), Golden, CO (United States); National Renewable Energy Laboratory
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)

Publication Date:: Tue Sep 05 00:00:00 EDT 2023

DOE Contract Number:: AC36-08GO28308

Research Org.:: EMN-DURMAT (EMN-DuraMAT); National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office

Subject:: 14 SOLAR ENERGY; Photovoltaic; Synthetic Data; Time Series Data

OSTI Identifier:: 1999772

DOI:: https://doi.org/10.21948/1999772

Citation Formats


                    Muller, Matthew, Deceglie, Michael, and Anderson, Kevin. Generating Synthetic Time Series PV Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation.  United States: N. p., 2023. 
        Web.  doi:10.21948/1999772.

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                    Muller, Matthew, Deceglie, Michael, & Anderson, Kevin. Generating Synthetic Time Series PV Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation.  United States.  doi:https://doi.org/10.21948/1999772

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                    Muller, Matthew, Deceglie, Michael, and Anderson, Kevin. 2023.  
"Generating Synthetic Time Series PV Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation".  United States.  doi:https://doi.org/10.21948/1999772.  https://www.osti.gov/servlets/purl/1999772. Pub date:Tue Sep 05 00:00:00 EDT 2023

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@article{osti_1999772,

  title        = {Generating Synthetic Time Series PV Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation},

  author       = {Muller, Matthew and Deceglie, Michael and Anderson, Kevin},

  abstractNote = {The publication describes the generation of the synthetic PV time series data set for real locations in the US, including satellite irradiance, rainfall, and a number of physical challenges introduced within the data.},

  doi          = {10.21948/1999772},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Sep 05 00:00:00 EDT 2023},

  month        = {Tue Sep 05 00:00:00 EDT 2023}

}

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DOI: https://doi.org/10.21948/1999772

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