Kernel-based estimation of wind farm power probability density considering wind speed and wake effects due to wind direction

This study compares the probability density function (PDF) of the power generated by a wind farm obtained analytically with the PDF considering the wake effect between wind turbines, a phenomenon that reduces the power generation capacity of wind farms. Instead of considering the wake effect in the analytical method, which is complex and difficult to solve, it has been proposed to use kernel estimators to obtain the PDF. To calculate it, a wind farm power output data set has been used. This data set was generated using historical wind speed and direction data and the Katic multiple wake model. Discrepancies between the analytical PDF and PDF fitted with the kernel estimators, can lead to an overstatement of the annual available energy by 4 an 9 %, depending on the complexity of the wind farm layout. These inconsistencies can have significant implications for production planning, wind farm design, and integration of wind power into the grid. Therefore, this analysis underscores the necessity of incorporating the wake effect in wind farm modelling, to guarantee more precise projections of generation and energy availability.