Which meteorological parameters influence extreme wind speed in a wind farm? A heterogeneous Granger causality approach

For an efficiently managed wind farm and wind power generation under adverse weather, knowledge of meteo-rological parameters influencing wind speed is of crucial importance for optimized and improved forecasts. Weinvestigate temporal effects of wind speed related processes such as wakes within the wind farm using the Hetero-geneous Graphical Granger model. The ERA5 meteorological reanalysis was used to generate wind farm powerproduction data in Eastern Austria. Method LiNGAM was selected for comparison. We evaluated six different sce-narios for the hydrological half year period, based on varying temporal intervals of low or high extreme wind speedas well as moderate wind speed as target variables. This splitting in scenarios allows us to carry out causal reason-ing about possible causes of extreme wind speed in a wind farm. The discovered set of causal parameters for eachof the scenarios provides information enabling future early warning as well as for taking management measures forwind farm power generation management under adverse weather conditions for wind power generation.