The impact of public acceptance on cost efficiency and environmental sustainability in decentralized energy systems

Abstract

The impact of public acceptance on cost efficiency and environmental sustainability in decentralized energy systems Highlights d Determine cost-optimal energy systems of 11,131 German municipalities in 2050 d Combine cluster and regression analyses with mathematical optimization methods d Apply nationwide scenicness data to estimate the landscape impact of onshore wind d Rejecting onshore wind leads to a significant increase in costs and CO 2 emissions

The feasibility of energy autonomy for municipalities: local energy system optimisation and upscaling with cluster and regression analyses

“…The methodology can also be applied to any other problem in which optimisation results from computationally expensive problems should be transferred to an entire population of these problems. One example is the recent study by Weinand et al (2021), in which the methodology is applied to determine the cost-optimal energy systems of all German municipalities in relation to public acceptance for onshore wind. Therefore, the approach developed in Weinand (2020a) should help decision makers, policy makers and researchers to estimate optimal results for a variety of energy systems using practical computational expenses.…”

Scaling Energy System Optimizations: Techno-Economic Assessment of Energy Autonomy in 11000 German Municipalities

“…• 𝐍𝐨𝐆𝐫𝐢𝐝 𝐚𝐜𝐜𝐞𝐩𝐭𝐚𝐧𝐜𝐞 : Unlike the 𝑁𝑜𝐺𝑟𝑖𝑑 𝑟𝑒𝑓 scenario, the expansion of onshore wind is dictated by a restrictive scenario with minimum distances of 1000 m each to inner and outer residential areas in order to estimate the maximum impact of social acceptance towards onshore wind on cost-optimal autonomous energy systems. This scenario is defined to reflect the public opposition towards onshore wind [61] and the resulting decrease in expansion numbers in Germany [62,63]. rooftop PV.…”

Reviewing local and integrated energy system models: insights into flexibility and robustness challenges

“…Stakeholder engagement also includes the clarity of tools as stakeholders were found to be less likely to use more complex tools [33,34]. Recent research also considers additional options to integrate social acceptance in ESMs such as scenicness ratings of landscapes for onshore wind installations [35] or an enforced equitable distribution of renewable generation capacity [36]. In optimization models, it is further important to add heterogeneity in the representation of actors to avoid the so-called "bang-bang effect", whereby a small change in model assumptions results in an outsized impact on the model outputs [37].…”