Wind energy is the most important renewable energy source in Germany. To effectively integrate wind power into the energy system, it is crucial to understand its temporal and spatial characteristics on both micro and macro scales. Existing methods for large-scale yield calculations often rely on simplified models that use fixed values or empirical formulations for energy losses. This study presents an approach that analyses different losses at the individual wind turbine level while enabling national-scale simulations. A model chain was developed that utilizes high-resolution spatial and temporal input data, combines them with loss calculation models, and provides specific losses and yields for individual turbines. The models were applied to onshore wind turbines in Germany, including a wake loss model and a model for shutdowns due to bat protection. Results demonstrate that this model chain effectively calculates large-scale losses from microscale data, revealing significant regional variations in loss types across different federal states. The developed model chain is suitable for various applications, particularly in the simulation, planning, and optimization of energy systems at regional and local levels.
Hirschmann et al. (Sun,) studied this question.