The transition towards decentralized and low-carbon energy systems, driven by the increasing penetration of renewable energy sources (RES), has intensified the need for planning methodologies to size distributed energy resources (DERs). At the same time, energy communities (ECs) have emerged as key enablers of local energy management, fostering collective self-consumption, while boosting RES integration. Beyond economic and environmental benefits, ECs can potentially contribute to improved grid operation and planning by providing flexibility services. However, most existing EC planning approaches primarily focus on self-consumption, neglecting the impact of flexibility provision on optimal DER sizing. Since flexibility is defined relative to a baseline that depends on DER sizing, flexibility potential becomes an endogenous variable, leading to a nonlinear and high-dimensional planning problem.

This paper proposes an optimization framework for EC planning that explicitly accounts for revenues from flexibility provision. A metaheuristic methodology using a genetic algorithm (GA) is developed to jointly optimize DER sizing and operational flexibility. Each candidate solution encodes the sizing of photovoltaic (PV) and battery energy storage systems (BESS) and is evaluated through operational simulations computing both baseline and flexible operation. The contracted power is derived from the resulting net consumption profile of each EC member and incorporated into the fitness evaluation together with investment and operational costs. The fitness function is evaluated across different time horizons and EC configurations, allowing the GA to iteratively evolve solutions through selection, crossover, and mutation operators. The framework considers flexibility provision from both conventional and cross-sector DERs, including electric vehicles (EVs) and electric water heaters (EWHs).

Results show that, compared to conventional EC planning approaches, explicitly accounting for flexibility provision during the planning stage can significantly reduce the overall costs of the EC. In the analysed case studies, cost reductions of up to 45% are observed compared with conventional sizing under flexibility operation. Additionally, flexibility provision increases investment in storage assets, with BESS capacity rising by up to 65%. The proposed framework enables a more accurate characterization of flexibility and supports improved planning decisions, providing a scalable approach aligned with energy sustainability and sovereignty goals.