Integration of disamenity costs and equality regarding onshore wind power expansion and distribution into energy system optimization models

Abstract

Abstract Background Social acceptance of energy infrastructure projects impacts public support for the energy transition and is essential for its sustainability and success. Despite extensive research on the social acceptance of renewable energy, particularly onshore wind power, energy system models have primarily emphasized techno-economic aspects. This focus has created a gap between model results and decision-makers’ needs. In this study, we offer recommendations on how to integrate disamenity costs and the consideration of equality in the distribution, two critical social aspects related to onshore wind power, into the optimization of an energy system. Therefore, we use a spatially distributed model of climate-neutral Germany and test various implementations of these two aspects. Results We identify effective linear formulations as model extensions for both aspects, notably outperforming quadratic alternatives, which require longer solution times (+ 50%-115%). Our findings reveal that endogenously considered disamenity costs can reduce the human population’s exposure to wind turbines in model results by -53%. Additionally, by applying the concept of social welfare functions to onshore wind power distribution, we establish a connection with welfare economics, which offers mathematical methods to consider equality in the spatial distribution in energy system models. Conclusion Disamenity costs become a predominant factor in the distribution of onshore wind power in energy system optimization models. However, existing plans for onshore wind power distribution in Germany highlight equality as the driving factor. The inclusion of social aspects into energy system models enables the establishment of socially better-accepted wind turbine locations. Neglecting these aspects results in an overestimation of the practical solution space for decision-makers and, consequently, energy system designs.