The mixed Burr-Generalized Extreme Value distribution (BGEV) and Gaussian copulas were used in a two-step procedure for estimating the directional wind energy yield in 100 m above ground level in Germany. Ina first step, BGEV was fitted to the marginal distributions of ERA-5 reanalysis horizontal wind vector component data available from the European Centre for Medium-Range Weather Forecasts. Then, Gaussian copulas were fitted to the bivariate distributions of the wind vector components. It is demonstrated that the combination of BGEV and Gaussian copulas allows a very accurate simulation of the directional wind energy yield. Results from goodnessof-fit evaluation indicate very good fit to virtually all wind speed-wind direction regimes reproduced by the ERA5 data in the period 2010-2016. The directional mean annual wind energy yield was simulated for eight wind direction sectors by applying a 3.05 MW wind turbine power curve. The simulation results illustrate that Germany's available wind energy is highly dependent on the wind direction. Mainly southwestern and western flows contribute to the total mean annual wind energy yield. All other wind direction sectors contribute only to a minor extend to the amount of extractable wind energy. The areas where mean annual wind energy yield is highest are mostly located in Northern Germany at the North Sea and Baltic Sea coasts.