Optimising Users Aggregation in Energy Communities: A Bi-Objective Approach for Collective Self-Consumption Districts

In response to the urgent need for sustainable energy solutions, energy communities have emerged as promising avenues. However, optimising user aggregation within these communities presents a multifaceted challenge. This study proposes a novel approach to this issue by formulating a bi-objective problem aimed at maximizing self-consumption and self-sufficiency within energy communities. Through meticulous mapping of buildings and predicting user electrical needs, the methodology systematically determines the best aggregation of users, categorizing them into building archetypes. Employing an optimisation routine, the study prioritises the enhancement of resilience and efficiency in energy management within communities. The findings, derived from a proof-of-concept analysis centred on a case study of a large office and residential building complex in Naples, with available installation area of 1265 m² for the roof and 1124 m² for the car-parking, reveal that the optimal energy community configuration achieves a self-consumption rate of 62% and a self-sufficiency rate of 37%. This marks a significant reduction in reliance on centralised grids and fossil fuels, fostering greater autonomy and sustainability within communities. Economic analyses further underscore the potential benefits, including reduced energy costs for consumers and quicker returns on investment for prosumers. This research highlights the critical role of energy communities in advancing sustainable energy practices. By optimising energy community configurations, a foundation is laid for a more resilient, efficient, and sustainable energy future. The actionable insights provided hold significance for policymakers, industry stakeholders, and communities navigating the transition towards greener energy districts.