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

Conference · Mon Dec 25 00:00:00 EST 2023

DOI:https://doi.org/10.1109/PVSC48320.2023.10359648· OSTI ID:2310896

Sengupta, Manajit ; Yang, Jaemo; Xie, Yu

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.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Electricity (OE)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 2310896
• Report Number(s): NREL/CP-5D00-88910; MainId:89689; UUID:c680aa1e-0a7d-4388-bcec-55d6caf5a75f; MainAdminId:71903
• Resource Relation: Conference: Presented at the 2023 IEEE 50th Photovoltaic Specialists Conference (PVSC), 11-16 June 2023, San Juan, Puerto Rico
• Country of Publication: United States
• Language: English

Related Subjects

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