Local resistance often hinders renewable energy technology developments, especially for onshore wind. In decentralized energy systems, the landscape impact of wind turbines or transmission lines is a key barrier to public acceptance. By using landscape scenicness as a proxy for public acceptance, we quantify its impact on the optimal energy systems of 11,131 German municipalities. In municipalities with high scenicness, it is likely that onshore wind will be rejected, leading to higher levelized costs of energy by up to about 7 €-cent/kWh. Onshore wind would be replaced mainly by solar photovoltaics and imports, and the cost-optimal energy systems would be associated with higher CO2 emissions of up to about 200 gCO2/kWh compared with an average of around 50 gCO2/kWh. The findings help to identify municipalities where public resistance to onshore wind could be particularly high and support the scientific and policy debate about the location of onshore wind farms.
Keywords: CO2 emissions; Gaussian process regression; cluster analysis; cost efficiency; energy system analysis; landscape esthetics; linear optimization; onshore wind; public acceptance; scenicness.
© 2021 The Authors.