Integrated Optimal Planning and Life Cycle Assessment of Renewable Energy Communities in Agricultural Areas

Renewable Energy Communities (RECs) are increasingly recognized as a key instrument for enabling decentralized and low-carbon energy systems through the coordinated deployment of distributed energy resources. While existing planning approaches are predominantly driven by techno-economic objectives, the integration of comprehensive sustainability metrics remains limited, with most studies relying on simplified carbon accounting rather than detailed life cycle-based indicators. This work addresses this gap by proposing a multi-objective mixed-integer linear programming formulation for the optimal planning of RECs, explicitly embedding technology-specific Life Cycle Assessment (LCA) indicators for renewable generation and storage systems. The proposed framework simultaneously optimizes investment costs and life cycle environmental impacts, enabling a more comprehensive assessment of design trade-offs. A case study is presented to demonstrate the approach's effectiveness and highlight the influence of LCA integration on optimal technology selection and system configuration. Results show that incorporating life-cycle metrics significantly affects planning decisions, thereby supporting more sustainable and informed REC design.