Influence of Wind Direction Variability on Power Prediction in the OpenFAST with Corrected Meteorological Data

Time-varying wind conditions, on which wind turbines depend, significantly influence power generation performance. Accordingly, this study proposes an approach to improve the accuracy of wind power generation prediction by incorporating time-varying wind conditions into the OpenFAST wind turbine model. An OpenFAST wind turbine model was constructed using wind speed and wind direction data collected from the weather station near the wind farm. The numerical model was composed of cases where only wind speed was considered and cases where the time-varying wind direction was considered. And the hourly and daily power generation prediction results were compared and analyzed with the actual power generation through indicators such as correlation coefficient, RMSE (Root Mean Square Error) and NRMSE (Normalized Root Mean Square Error). As a result, in the model that reflects time-varying wind direction, errors were reduced and linear correlation was improved, both in comparison with actual power generation. Therefore, it can be concluded that this model enhances the accuracy of power generation prediction. Consequently, this study highlights the importance of considering time-varying wind direction in OpenFAST wind turbine simulation.