Considering the Variability of Soiling in Long-Term PV Performance Forecasting: Preprint

Matthew Muller, Faisal Rashed

Research output: Contribution to conferencePaper


This study presents the development of a methodology for evaluating the variability associated with soiling on long-term PV forecasting. Independent engineering firms typically build P50 forecasts for large PV plants through the use of the PVsyst software, where monthly soiling losses are one of many inputs to the P50 model. Subsequently, long-term performance distributions, or Pvalues, are constructed through a Monte Carlo analysis that includes various factors such as: satellite irradiance modeling uncertainty, uncertainty in the PVsyst model, and long-term irradiance variability. Often the PVsyst model uncertainty is increased to account for sites with significant soiling concerns but no systematic method has been presented in the literature to specifically include soiling variability within Pvalues. In this work soiling information from 16 sites in the U.S. Southwest are combined with 20 years of rainfall data to generate 20 years of energy production with soiling losses and then subsequently generate Pvalues. The results show that the spread of Pvalues (P1-P99) can increase from 0-13% when interannual soiling variability is included.
Original languageAmerican English
Number of pages6
StatePublished - 2023
Event50th IEEE Photovoltaic Specialists Conference - San Juan, Puerto Rico
Duration: 11 Jun 202316 Jun 2023


Conference50th IEEE Photovoltaic Specialists Conference
CitySan Juan, Puerto Rico

Bibliographical note

See NREL/JA-5K00-87429 for related article published in IEEE Journal of Photovoltaics

NREL Publication Number

  • NREL/CP-5K00-85776


  • interannual variability
  • performance forecasting
  • photovoltaic soiling
  • Pvalues
  • uncertainty


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