Climate change and other environmental impacts severely threaten human well-being. The European Green Deal aims to reduce greenhouse gas emissions, decouple economic growth from resource use, and ensure an equitable transition. A key strategy is maximizing renewable technology deployment to fully decarbonize electricity supply. Ambitious targets for renewable capacity are set in national energy and climate plans, driven by monetary incentives and reduced capital costs. While increased renewable capacity offers benefits like reduced air pollution and new employment opportunities, it also creates burdens, including increased system costs, ecosystem impacts, and land-use conflicts. Renewable capacity deployment has been uneven across European regions, indicating unevenly distributed impacts. This necessitates investigation into regional impacts to minimize inequalities and ensure successful transition. While many models exist, few analyze regional impacts holistically, considering aspects like regional equality, hourly operation, transmission, and storage. This study fills this gap by quantifying regional impacts of the electricity sector transition in six Central European countries, modeling spatially explicit scenarios to analyze trade-offs between cost minimization, regional equality, and renewable energy maximization.

Existing research on European electricity sector transitions often focuses on technical and economic aspects like least-cost renewable capacity allocation and weather effects on costs and generation. Fewer studies consider regional equality, with some focusing on regionally equitable allocation of specific renewable technologies within single countries. However, these studies lack a holistic quantitative picture of regional impacts and trade-offs, neglecting aspects such as employment, land use, and technical system feasibility. This study addresses these limitations by providing a more comprehensive assessment.

This research uses a modeling approach that soft-links two optimization models: EXPANSE and PyPSA. EXPANSE, a spatially explicit, bottom-up model, applies the Modeling to Generate Alternatives (MGA) method to generate 100 scenarios of electricity generation capacity and locations across 650 NUTS-3 regions in six Central European countries. PyPSA, a model with hourly resolution, optimizes hourly electricity generation and long-term investment in storage and transmission capacity for each scenario generated by EXPANSE. This soft-linking approach balances computational feasibility with the realistic representation of electricity generation deployment and centralized transmission planning. The scenarios consider a broad portfolio of generation, storage, and transmission technologies, with data on electricity demand, renewable generation potentials, and existing capacities drawn from various sources. Techno-economic parameters for each technology are used to calculate costs. Regional impacts are assessed across different scenarios, including system costs, employment (direct and indirect), greenhouse gas and particulate matter emissions, and land use. Regional equality for each impact is measured using a modified Gini index, ranging from 0% (perfect equality) to 100% (perfect inequality). Four distinct scenarios are analyzed: frozen generation capacity (2018 levels), minimum system costs, maximum regional equality of system costs, and maximum renewable electricity generation. Each scenario (except the frozen generation capacity scenario) considers country-specific electricity targets for 2035. A constraint is included to ensure that each country meets its annual electricity demand from domestic generation, reflecting supply security considerations.

The 100 modeled scenarios show considerable variation in electricity generation from wind, solar PV, nuclear, and fossil fuels, highlighting flexibility in implementing national targets. Compared to a 'frozen generation capacity' scenario (2018 levels), scenarios meeting national targets show higher generation from renewables (offshore and onshore wind, open-field and rooftop solar PV) and lower generation from nuclear, coal, and lignite. Gas generation varies depending on other capacities. The four distinct scenarios differ significantly in technology-specific generation. The minimum system cost scenario relies heavily on centralized generation from coal, offshore wind, large hydropower, and biomass waste, leading to spatially concentrated impacts. The maximum regional equality scenario features decentralized generation from onshore wind, rooftop solar PV, and other distributed renewables, resulting in higher, more evenly distributed impacts. The maximum renewable electricity generation scenario has high renewable and nuclear generation, requiring substantial storage and transmission capacity expansion. Across the MGA scenarios, generation, storage, and transmission costs are consistently higher than the 'frozen generation' scenario. The minimum system cost scenario has the lowest costs, while the maximum regional equality and maximum renewable scenarios have significantly higher costs. The employment impact is significantly increased in all MGA scenarios compared to the frozen generation capacity scenario. Employment is highest under the maximum renewable electricity generation scenario. Greenhouse gas and particulate matter emissions are considerably lower in MGA scenarios, with the maximum renewable generation scenario showing the lowest emissions. Land use increases significantly in MGA scenarios due to higher renewable capacity, particularly in the scenarios prioritizing regional equality and renewable energy maximization. Regional impact analysis shows that minimizing system costs leads to spatially concentrated impacts, with cost increases near the coasts and decreases in regions with high existing nuclear and fossil fuel capacities. The maximum regional equality scenario shows more evenly distributed costs and employment. The maximum renewable scenario combines elements of both, with high costs near coasts and inland, but significant reductions in emissions and land use in coal-dominated regions. Analysis of the 100 MGA scenarios reveals a trade-off between minimizing total system costs, maximizing regional equality of system costs, and maximizing renewable electricity generation. These goals cannot be simultaneously optimized. Maximizing regional equality increases costs but improves renewable integration and reduces emissions. Maximizing renewables yields the lowest emissions but has high costs and land-use impacts. A further analysis using the Gini index shows that maximizing regional equality of system costs and maximizing renewable electricity generation lead to more equitable distributions of employment, emissions, and land use compared to cost minimization.

This study provides a detailed regional-level assessment of the electricity system transition in Central Europe, highlighting the trade-offs between cost efficiency, regional equality, and renewable energy maximization. The findings emphasize the significant spatial variations in impacts, demonstrating that minimizing system costs leads to spatially concentrated benefits and burdens. Conversely, maximizing regional equality and renewable generation leads to more equitable distribution of impacts. The complete phase-out of certain technologies (lignite, nuclear) within the modeled cost limits appears infeasible, particularly in Poland and France. The study’s key contribution is highlighting the interconnectedness of economic, social, and environmental goals in the energy transition, underscoring the need for integrated planning that considers multiple societal aims rather than simply cost optimization.

This research demonstrates the significant regional variations in impacts associated with achieving Central European electricity sector targets. The study reveals trade-offs between cost minimization, regional equality, and renewable energy maximization, showing that these goals are not mutually achievable. Policymakers must consider the diverse regional impacts when designing energy transition strategies to ensure a just and equitable transformation. Future research could further explore the role of specific policies in shaping technology choices and quantify their impact on regional distribution of costs and benefits. Expanding this analysis to encompass the whole energy system rather than just the electricity sector would also provide a more comprehensive understanding.

The study relies on certain key assumptions: the implicit treatment of policy instruments, the focus on domestic electricity generation to reflect supply security concerns, the limitation to the electricity sector, and the chosen short-to-medium-term horizon (2035). While these assumptions do not invalidate the key findings, they represent potential areas for future research to further refine the analysis and expand its scope. The reliance on model parameters might affect the results, and sensitivity analysis is needed to assess this issue.