DETECTION OF METEOROLOGICAL VARIABLES IN A WIND FARM INFLUENCING THE EXTREME WIND SPEED BY HETEROGENEOUS GRANGER CAUSALITY (Papers Track)
Katerina Schindlerova (UniVie); Irene Schicker (Geos); Kejsi Hoxhallari (UniVie); Claudia Plant (University of Vienna, Austria)
Abstract
For an efficiently managed wind farm and wind power generation under adverse weather, knowledge of meteorological parameters influencing wind speed is of crucial importance for optimized and improved forecasts. We investigate temporal effects of wind speed related processes such as wakes within the wind farm using the Heterogeneous Graphical Granger model. The ERA5 meteorological reanalysis was used to generate wind farm power production data in Eastern Austria. We evaluated six different scenarios for the hydrological half-year period, based on moderate wind speed and varying temporal intervals of low or high extreme wind speed This allows to carry out causal reasoning about possible causes of extreme wind speed in a wind farm. A set of causal parameters for each of the scenarios was discovered enabling future early warning and for taking management measures for wind farm power generation management under adverse weather conditions.