Sensitivity Analysis and Validation of WRF-ARW Parameterizations for Potential Solar and Wind Energy Sources over Malaysia

Abstract

Abstract This study investigates how accurately the Weather Research and Forecasting (WRF) simulation anticipates the viability of renewable energy options in Malaysia, with specific attention paid to wind and solar power potential. Due to Malaysia’s transition toward sustainable energy, precise forecasting is essential for grid stability and efficient integration. The research used simulations across East and West Malaysia for October 2022 with varying parameterization schemes to determine the most suitable configurations for accurate energy predictions. Eleven unique scheme permutations were analyzed against Mesonet, ERA5-Land, and Centre for Marine and Coastal Studies (CEMACS) datasets. The results revealed that certain permutations, specifically run 9 and run 10, significantly reduced the root-mean-square error (RMSE) for predicting radiation and wind speed outputs, indicating higher accuracy in simulations. The two best runs were then validated for November 2022 and used to estimate wind (run 10: WRF single-moment 6-class microphysics, RRTMG longwave radiation, Dudhia shortwave radiation, unified Noah land surface model, MYJ PBL, Eta surface layer, and new Tiedtke cumulus schemes) and solar photovoltaic (run 9: Morrison 2-moment microphysics, CAM longwave radiation, RRTMG shortwave radiation, unified Noah land surface model, MYJ PBL, and Eta surface layer schemes) potential maps over CEMACS and Kuching locations. Solar photovoltaic energy was estimated at a total of 3165 and 3379 kWh for CEMACS and Kuching, respectively, and a good potential overall, ranging from about 5500 to 7881 kWh, while wind energy had a much more variability appearance of 115 936 and 6250 kWh for CEMACS and Kuching, respectively. This study highlights the potential for targeted weather forecasting models to enhance the reliability and integration of renewable energy sources into national grids. Significance Statement This study explores the effective use of weather forecasting models to enhance renewable energy generation in Malaysia, a region increasingly focusing on sustainable energy solutions. By analyzing and validating various weather model configurations, this research provides vital information for selecting optimal settings for accurate predictions of solar and wind energy potential. This crucial advancement, which effectively integrates renewable energy into power grids to reliably provide a steady and efficient flow of energy, is essential for moving progressively closer to a more sustainable and eco-friendly energy. The results of this study both enhance scientific comprehension of atmospheric simulations utilized in energy sectors and carry meaningful consequences for policy formation and renewable infrastructure evolution within tropical regions.