In the relentless pursuit of a fully renewable energy future, recent research underscores a critical yet often overlooked element: the preferences of citizens. As countries strive to meet the ambitious targets set forth by the Paris Agreement—aiming for 100 percent renewables by the 2030s—public acceptance remains a formidable barrier. The expansion of renewable infrastructure, particularly wind and solar farms, necessitates significant land use changes which frequently meet with local opposition. A collaborative effort among researchers from ETH Zurich, the University of Erlangen-Nuremberg, and the Research Institute for Sustainability (RIFS) at the Helmholtz Centre Potsdam has yielded novel insights into integrating societal preferences directly into energy system modeling—promising a pathway towards more socially viable, technically sound, and economically feasible energy futures for Europe.
Traditionally, energy systems modeling has concentrated on technical optimization and cost efficiency, producing solutions that minimize expenses while ensuring reliable electricity supply. However, these models often disregard the social dynamics that shape real-world energy deployment. This disconnect risks implementing technically optimal plans that might fail due to public resistance and lack of social acceptance. The team’s innovative approach combines extensive decision-making experiments capturing European citizens’ preferences with high-resolution techno-economic modeling, creating scenarios that resonate with the public’s values and technical constraints simultaneously. This integration addresses a fundamental gap in energy planning by bridging the technical-economic perspective and the social dimension.
Using data gathered from controlled experiments conducted across four European countries, researchers quantitatively assessed how populations weigh various aspects of renewable electricity systems—such as energy sourcing, geographic distribution, and import dependency. These preference data were then systematically incorporated into national and sub-national energy system models, enabling the prediction of which energy configurations Europeans would most likely endorse if given a direct choice. By reflecting genuine public preferences, the models reveal crucial trade-offs between cost, energy mix, and system decentralization that are often invisible in conventional analyses.
One particularly striking finding is the pronounced preference among Europeans for solar power relative to wind energy, despite solar not being the cheapest option in many scenarios. Contrary to strictly cost-driven outcomes, participants favored decentralized energy systems emphasizing solar photovoltaic generation, reduced wind power installations, and minimized reliance on electricity imports from abroad. The geopolitical tensions following Russia’s invasion of Ukraine have heightened public desire for import independence, further shifting preferences towards more localised production and energy security. This societal appetite for decentralization challenges the prevailing rhetoric centered solely on cost-optimal network-scale projects.
The research also illuminated the contentious nature of transmission infrastructure siting. For example, in Hungary and Romania, the models identified a technically optimal transmission corridor, depicted in vivid blue on regional maps, which nonetheless faced significant public opposition. This discrepancy between cost-effective technical solutions and social acceptability exemplifies the necessity of incorporating social data into infrastructure planning to prevent conflict and delay. Integrating citizen preferences enables planners to anticipate and mitigate resistance, potentially by rerouting infrastructure or adapting technology portfolios.
Lead author Tim Tröndle elaborates on the significance of these findings: while energy models have become increasingly detailed and accurate in showcasing how renewable systems can operate efficiently, they run the risk of irrelevance if they omit social constraints. Acceptance and opposition dynamics, crucial for successful implementation, are typically studied separately and lack integration with modeling outputs. Their approach harmonizes social science with energy systems engineering to produce scenarios that are both feasible and reflect societal aspirations.
From a policy perspective, the implications are profound. The researchers advocate for institutionalizing mechanisms that actively capture and embed citizens’ preferences into energy planning frameworks. This could take the form of decision-making experiments, representative surveys, or other participatory tools feeding directly into modeling inputs. Such democratization of energy planning does not merely ensure acceptance but also enriches the decision-making process by revealing diverse priorities and concerns, leading to more resilient and adaptive energy systems.
The evidence that populations do not inherently prioritize cost minimization challenges longstanding assumptions underpinning energy policy. Instead, social factors—from landscape aesthetics and local benefits to national autonomy and energy security—play an equally vital role. Political decisions therefore must transcend narrow economic metrics and embrace multidimensional criteria reflecting the complexities of societal values. This paradigm shift can pave the way for smoother energy transitions by preempting conflicts and fostering trust.
Moreover, the study highlights the technical viability of socially preferred scenarios. Contrary to fears that incorporating preferences might compromise system performance or feasibility, the research demonstrates that scenarios incorporating citizen inputs can still satisfy technical and economic requirements. This finding assuages concerns of policy-makers that integrating social factors could impede the cost-effective deployment of renewables and underscores the complementary nature of social acceptance and technical optimization.
Ultimately, the harmonization of social preferences with techno-economic modeling represents a breakthrough in energy sciences. It fosters a more democratic, transparent, and inclusive approach to energy planning. By acknowledging that energy systems do not exist in a vacuum but are embedded within societal contexts, this methodology offers unprecedented insights for crafting transition pathways that garner widespread support while meeting stringent environmental goals.
As Europe and the world accelerate toward net-zero targets, this research provides a beacon guiding policy and industry toward energy futures that are not only sustainable and affordable but also socially legitimate and acceptable. The transition to renewables is as much a social challenge as a technological one, and embracing this duality is essential for achieving deep decarbonization equitably and efficiently. The integration of public preferences into modeling will likely become an indispensable standard in energy planning across jurisdictions globally.
The publication of this study in Energy Research & Social Science highlights the critical intersection of technology and society in the energy domain. It is a call to action for energy modelers, planners, and policy-makers to reconceptualize how scenarios are designed and evaluated. By embedding citizen voices at the heart of energy strategy, the research charts a more optimistic, participatory, and pragmatic course toward a renewable-powered future.
Subject of Research: Integration of citizen preferences into energy system modeling for renewable energy planning in Europe.
Article Title: Socially preferable and technically feasible: European citizens choose solar power and import independence over lower costs.
News Publication Date: 9 October 2025.
Web References: http://dx.doi.org/10.1016/j.erss.2025.104364
Image Credits: Tim Tröndle
Keywords: Renewable energy, energy system modeling, citizen preferences, solar power, wind power, decentralized energy, energy transition, public acceptance, European energy policy, Paris Agreement.
