Synergizing academia and industry in a Renewable Energy Community: Toward a sustainable energy transition

• Synergy between university and industry is explored to foster energy transition. • Scenarios show up to 39.6 % energy self-sufficiency, reducing CO2 emissions. • Financial analysis shows high NPV, making renewable energy projects viable. • RECs enable industry to benefit from lower costs and enhanced competitiveness. • Matching energy supply and consumption profiles optimizes REC models. Renewable Energy Communities (RECs) are increasingly promoted as a driver for decarbonization and sustainable energy transition. However, evidence remains limited for mixed institutional contexts where a university acts as an anchor member and shares locally generated renewable electricity with nearby industry under regulatory and practical constraints. This study evaluates an academia-industry REC configuration through a replicable, scenario-based workflow that integrates photovoltaic (PV) yield modelling, high-resolution demand matching, regulatory feasibility survey, and combined energy, environmental and financial assessment. Three scenarios with constant installed PV capacity are analyzed to quantify self-consumption and self-sufficiency, surplus allocation for energy sharing, CO 2 mitigation, and investment performance over a 25-year horizon. Results indicate that feasible orientation strategies can improve the temporal match between PV generation and institutional demand, increasing self-consumption and self-sufficiency relative to a yield-maximizing configuration while maintaining economic viability. This study further illustrates how the decarbonization goals of higher education institutions can be promoted while accommodating heritage-related constraints, and how PV benefits can be shared with local manufacturing partners to support cost reduction and competitiveness. Beyond this specific case, this paper provides a potentially transferable decision-support model and operational-logic for academia-industry RECs to inform energy policy and support early-stage planning and replication in comparable institutional and industrial environments.