Quantifying trade-offs for the spatial allocation of onshore wind generation capacity: A case study for Germany

The deployment of onshore wind power is an important means to mitigate climate change. However, wind turbines also have negative impacts at the local scale, like disamenities to residents living nearby, changes in landscape quality, or conflicts with nature conservation. Our paper analyses how these impacts affect the optimal siting of wind turbines, as compared to a spatial allocation focused solely on minimizing generation costs. To quantify the spatial trade-offs between these criteria, we propose a novel approach using Pareto frontiers and a Gini-like potential trade-off indicator. Our analysis builds on a spatial optimization model using geographical information system data for Germany. We show that spatial trade-offs between the criteria under consideration are significant. The size of the trade-off varies substantially with the criteria under consideration, depending on the spatial heterogeneity of each criterion as well as on the spatial correlation between the criteria. Spatial trade-offs are particularly pronounced between nature conservation (measured by impacts on wind powersensitive birds) and other criteria.