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Wind power is one of the most promising options for producing energy in a climate-friendly manner. However, besides its environmental benefits wind power generation causes externalities such as impacts on humans and biodiversity. All studies conducted so far show that these externalities can be substantial. The question is how this knowledge translates into a welfare-optimal spatial allocation of turbines that needs to consider both production and external costs. We present a modeling approach for the determination of the welfare-optimal spatial allocation of wind turbines (WT) and apply it to the planning region West Saxony in Germany. The approach combines choice experiments, a non-market valuation method used to measure externalities of wind power, and spatially explicit ecological-economic modeling within an optimization framework. Optimal is understood here as producing a given amount of wind power at lowest social costs. Social costs comprise (i) externalities measured by the (monetized) impact of WT on biodiversity, the distance of the WT to settlements, the height of the WT and size of wind farms, and (ii) the construction and operating costs associated with the WT. We show that the social costs of wind power production can be reduced substantially if externalities are taking into account.

Optimal Spatial Allocating of Wind Turbines Taking Externalities Into Account