Multi-Criteria Decision Analysis Framework for Evaluating Tools Supporting Renewable Energy Communities

Renewable energy communities are emerging as key players in the sustainable energy transition, yet there is a lack of systematic approaches for evaluating the digital tools that support their development and operation. This study proposes a comprehensive methodology for assessing tools for supporting renewable energy communities, based on a system of key performance indicators and the multi-criteria decision analysis framework method. Twenty-three specific sub-criteria were defined and scored for each tool, and a weighted sum model was applied to aggregate performance. To ensure robust comparison, criteria weights were derived using both expert judgement (pairwise comparisons of ranking and analytical hierarchy process) and objective data-driven methods (the entropy-based method and the criteria importance through intercriteria correlation weighting method). The framework was applied to a diverse sample of contemporary renewable energy community’s tools, including open-source, commercial, and European Union project tools. Key findings indicate that some of the tools have shown noticeable rank shifts between expert-weighted and data-weighted evaluations, reflecting that expert opinions emphasize technical and operational features while objective variability elevates environmental and economic criteria. This assessment enables stakeholders to compare energy community tools based on structured criteria, offering practical guidance for tool selection and highlighting areas for future improvement.