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Forecasts of wind-power\udproduction are necessary to facilitate the integration of wind energy into\udpower grids, and these forecasts should incorporate the impact of\udwind-turbine wakes. This paper focuses on a case study of four diurnal cycles\udwith significant power production, and assesses the skill of the wind farm\udparameterization (WFP) distributed with the Weather Research and Forecasting\ud(WRF) model version 3.8.1, as well as its sensitivity to model configuration.\udAfter validating the simulated ambient flow with observations, we quantify\udthe value of the WFP as it accounts for wake impacts on power production of\uddownwind turbines. We also illustrate with statistical significance that a\udvertical grid with approximately 12 m\udvertical resolution is necessary for reproducing the observed power\udproduction. Further, the WFP overestimates wake effects and hence\udunderestimates downwind power production during high wind speed, highly\udstable, and low turbulence conditions. We also find the WFP performance is\udindependent of the number of wind turbines per model grid cell and the\udupwind–downwind position of turbines. Rather, the ability of the WFP to\udpredict power production is most dependent on the skill of the WRF model in\udsimulating the ambient wind speed

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data