Forecasting Day-Ahead Solar Irradiance for Puerto Rico Using the WRF Model and NSRDB

Research output: Contribution to conferencePaper


Accurately predicting solar energy resources is a major challenge in integrating photovoltaics generation on the electric grid. Numerical weather prediction has been recognized by the solar energy community as a major approach to provide solar resource forecasts at various locations and for a variety of timescales. In this study, as a part of the Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100), we develop day-head solar irradiance forecast data using the Weather Research and Forecasting (WRF) model at 3 km and hourly/5-minute. The global horizontal irradiance (GHI) and direct normal irradiance (DNI) forecasts simulated from the WRF model are postprocessed by a simple optimization method using satellite-derived gridded observations from the National Solar Radiation Data Base (NSRDB) to reduce error and bias of the solar irradiance forecasts covering 2018-2020. The NSRDB contributes to improving the GHI and DNI forecasts and also offers the opportunity for an in-depth analysis to evaluate their accuracy over a wide range of Puerto Rico regions. Preliminary results show overall improvements of GHI forecasts up to 37% (DNI: 15%) for mean absolute error and 97% (DNI: 76%) for mean bias error by applying a postprocessing technique to WRF model output.
Original languageAmerican English
Number of pages3
StatePublished - 2023
Event2023 IEEE 50th Photovoltaic Specialists Conference (PVSC) - San Juan, Puerto Rico
Duration: 11 Jun 202316 Jun 2023


Conference2023 IEEE 50th Photovoltaic Specialists Conference (PVSC)
CitySan Juan, Puerto Rico

NREL Publication Number

  • NREL/CP-5D00-88910


  • data models
  • photovoltaic systems
  • predictive models
  • probabilistic logic
  • renewable energy sources
  • solar energy
  • weather forecasting


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