2020/07/03 by Yue Zhang, Yanbo Shen, Zhang, Yue +5
Computer Science · Earth and Planetary Sciences · Energy · #Atmospheric and Oceanic Physics (physics.ao-ph) #FOS: Physical sciences #Meteorological Phenomena and Simulations #Solar Radiation and Photovoltaics #Solar Thermal and Photovoltaic Systems
paper · pdf · doi:10.48550/arxiv.2007.01639
openalex publication_date 2020/07/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper provides a benchmark to evaluate operational day-ahead solar irradiance forecasts of Global Forecast System (GFS) for solar energy applications in China. First, GFS day-ahead solar irradiance forecasts are validated quantitatively with hourly observations at 17 first-class national solar monitoring stations and 1 Baseline Surface Radiation Network (BSRN) station all over China. Second, a hybrid forecast method based on Gradient Boosting (GB) and GFS product is proposed to improve forecasts accuracy. Both GFS forecasts and GB-based forecasts are compared with persistence forecasts. The results demonstrate persistence model is more accurate than GFS forecasts, and the hybrid method has the best performance. Besides, parameter optimization of direct-diffuse separation fails to reduce the errors of direct normal irradiance (DNI) forecasts.