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Abstract Resistance of the local population to new energy infrastructure may hinder achieving the European Union's goal that 32% of energy consumption come from renewable sources. A vast literature is available on the social acceptance of specific renewable energy technologies, but existing research lacks assessments regarding comprehensive transformations to local energy systems. Moreover, the promising energy storage technology power-to-gas has not yet been addressed in acceptance studies. This paper fills these gaps by analysing data from a choice experiment survey with 2000 respondents across four nations (Germany, Austria, Italy, and Switzerland). Results from the analysis show that solar farms and power-to-gas infrastructure increase acceptance of local energy communities, while wind farms have an ambiguous effect, and gas power plants and power lines decrease acceptance. The derived monthly willingness to pay estimates for the acceptance-increasing technologies ranges from 8.5€ for power-to-gas to 29.5€ for photovoltaics. Additionally, we investigate whether stated support from political opinion leaders at the local, national, and EU levels can increase the acceptance of renewable energy systems. Results suggest that Italian choices are influenced by the opinions of EU and national governmental bodies (+3.5% and +2.7%), and that Swiss choices are sensitive to the opinions of local politicians (+2.3%).
social acceptance, choice experiment, Power-to-gas, renewable energy, local energy community
social acceptance, choice experiment, Power-to-gas, renewable energy, local energy community
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 187 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
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| downloads | 90 |

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