Optimization and Control of Energy Communities in the Energy Market

The large-scale integration of renewable energy sources represents the starting point for the energy transition aimed at reducing greenhouse gas emissions and mitigating climate change. However, the increasing penetration of non-programmable and intermittent renewable generation introduces significant challenges for power system operations. In this context, Renewable Energy Communities (RECs) have emerged as a promising solution to foster local renewable integration, % actively involve end users in the energy transition, enhance self-consumption, and eventually contribute to grid support through coordinated energy management. To address the challenges related to their operational management and maximize their potential, some optimization tools must be developed. In this context, this thesis focuses on the operational and management aspects of RECs within the Italian regulatory framework. Optimization-based methodologies are developed to support efficient and regulation-aware management of both internal and external REC operations. Internal operations address the management of a single community and its members, integrating traditional objectives, such as cost minimization, with community-level goals, most notably the maximization of shared energy. External operations investigate the participation of RECs in flexibility and balancing mechanisms through demand-side management strategies, considering the coordination of multiple RECs by an aggregator to provide grid services. Then, the last two chapters of this thesis are devoted to modeling and optimal management of complex REC participants, such as smart parking lots and hydrogen-based multi-vector energy hubs, whose flexibility potential can be further enhanced through appropriate control strategies. The multi-actor and multi-objective nature of RECs is addressed in this thesis by adopting multi-level optimization approaches, which are a valid solution when the problem involves multiple decision makers. To allow for scalable coordination, decentralized algorithms are developed to ensure efficient operation even when the size of the REC increases and in real-time applications. % These methods explicitly account for regulatory constraints, energy sharing mechanisms, and interactions with electricity markets. The results demonstrate that optimization-based Energy Management Systems can effectively support RECs in maximizing shared energy, improving economic performance, and providing flexibility services to the grid. Overall, the proposed approaches contribute to bridging the gap between regulatory frameworks, technological integration, and real-world operations, highlighting the role of RECs as active and flexible entities in future low-carbon energy systems.