Investigation of aggregation and clustering approaches for modelling onshore wind energy generators

In context of energy transition, investigations into wind generation units are becoming increasingly important. Requirements for generators and generator capabilities are evolving and (expected) behaviour of the systems is therefore directly related to connection level and connection year. Capabilities and behaviour of individual generators and wind farms are of increased interest in this context, while high-resolution modelling is faced with high complexity and computing time. Various modelling, clustering and aggregation approaches are therefore used. However, while compressing information this can also cause loss of meaningful data. The german core energy market data register (MaStR) offers publicly available open data containing information on generators, such as rated power, type, wind farm affiliation, voltage level and location. Even more properties like FRT capabilities can be attributed via correlations.