OPTIMIZATION AND FLEXIBILITY OF RENEWABLE ENERGY COMMUNITIES

Renewable Energy Communities, introduced by recent European directives, are emerging as key actors in the energy transition by fostering cooperation among electricity users through shared energy resources. Italy has been at the forefront of renewable energy communities implementation, establishing a regulatory framework with governance models and incentive mechanisms to promote energy sharing within communities. This PhD thesis investigates the optimization and flexibility of renewable energy communities using the Julia-based tool EnergyCommunity.jl. The open-source model is used to model energy flows and the energy shared within the community. The model gives the flexibility to integrate residential building loads and electric mobility infrastructures. Members of a community can install photovoltaic and storage systems to meet their energy needs and charge electric vehicles under flexible recharging conditions. Beyond energy sharing, renewable energy communities have the potential to act as flexibility providers by integrating various energy assets—such as generation, storage, and controllable loads—within a unified ecosystem. Part of this research involved applied studies on renewable energy communities, supported by the collaboration with EnGreen, which enabled the field validation of the proposed models and methodologies. These experiences helped refine the theoretical framework and adapt it to real implementation conditions, strengthening the link between academic research and practical applications in the evolving context of community-based energy systems. The present research was conducted with the support of a doctoral scholarship co-funded by the University of Pisa and EnGreen. The doctoral scholarship was cofinanced with resources from the European Union - NextGeneration EU National Recovery and Resilience Plan Mission 4 Component 2 "From Research to Business" Investment 3.3 of the PNRR which provides for "the introduction of innovative doctorates that meet the innovation needs of businesses and promote the hiring of researchers by businesses."