GIS-driven planning of energy communities: optimising renewables, storage, and demand aggregation in urban areas

Aggregating the energy demand of multiple users and optimising the design and operation of renewable energy assets have become key concerns within the framework of decentralised energy systems. This paper presents a comprehensive methodology for planning, modelling, and evaluating renewable energy communities, with a focus on urban areas. The proposed framework integrates GIS-based spatial analysis, urban building energy modelling, and algorithms for aggregating users’ energy demand. The analysis explores different virtual building aggregations within the regulatory framework for RECs, optimising for self-consumption, self-sufficiency, and life cycle costs. This study builds on the current development of frameworks for energy planning at urban scales, providing a methodology to investigate the development of energy communities and their user aggregation at a larger scale. Applied to a medium-high density urban cluster, the results indicate that urban areas benefit more from multiple smaller communities rather than a few large ones, leading to greater renewable energy utilisation and lower life cycle costs. A target focused on balancing the use of locally produced energy results in moderate REC development, whereas a target aimed at minimizing urban users' life cycle costs favours the deep integration of communities. In the first scenario, the urban area achieves 60 % of renewable energy penetration, while in the second case, life cycle costs are reduced by 80 M€ over 20 years. However, in case of uncontrolled development, the economic benefits may be unevenly distributed among users.