Optimization and evaluation of the Weather Research and Forecasting (WRF) model for wind energy resource assessment and mapping in Iran

Abstract

AbstractThe main purpose of this study is to optimize the Weather Research and Forecasting (WRF) model regarding the choice of the best planetary boundary layer (PBL) physical schemes and to evaluate its performance for wind energy assessment and mapping in Iran. For this purpose, five PBL and surface layer parameterization schemes were tested and their performance was evaluated via comparison with observational wind data. Then the model was run for seventeen years (2004–2020) in order to assess the model's ability to estimate the wind energy production in Iran. Although no specific PBL scheme showed the best performance in all situations and stations, the asymmetrical convection model version 2 (ACM2) PBL scheme was considered as the one with the best performance on an annual basis. On the other hand, the quasi-normal scale elimination (QNSE) PBL scheme showed better performance over cold seasons, while the ACM2 scheme exhibited less uncertainty in the warm periods. It was also found that the WRF model errors depend on the horizontal resolution of the terrain data used and that WRF performance is weaker in simulating wind speeds below 3 ms− 1and above 10 ms− 1. Overall, by comparing WRF simulations with wind observations in Iranian areas where wind farms are currently in operation, it is concluded that WRF enables to provide accurate and reliable wind speed and direction data for realistic wind energy assessment studies in Iran. WRF model results showed that the Sistan Basin in the eastern part of Iran presents the highest wind energy capacity and the aeolian potential is also high in southwest Iran during summer and along the Zagros Mountains.