Stefano Bracco

As Renewable Energy Communities (RECs) drive a shift toward decentralized power systems, innovative solutions to manage the inherent intermittency of distributed energy resources are essential. This paper investigates the potential of electric vehicles (EVs) as dynamic flexibility providers within the REC framework. By leveraging smart charging and Vehicle-to-Everything (V2X) technologies, EV fleets can act as key assets to facilitate the transition toward active distribution networks by providing upward and downward power reserves within local flexibility markets. This study presents a Mixed-Integer Linear Programming (MILP)-based Energy Management System (EMS) to optimally manage a case study REC in Northern Italy, characterized by renewable power plants and V2X-enabled EV charging stations for both electric cars and electric trucks. The proposed EMS model aims to simultaneously maximize the energy virtually shared within the REC and the provision of upward and downward reserves by the EV fleet over the considered time horizon. The EMS optimal results are analyzed for two distinct periods of the year, namely one week in spring and one in autumn, demonstrating that the flexibility guaranteed by the EVs can significantly impact the energy-sharing mechanism of the REC while at the same time providing additional revenues to the REC members.

Renewable Energy Communities (RECs), introduced by the RED-II EU Directive, represent a promising mechanism to facilitate the integration of Renewable Energy Sources (RESs) in compliance with European targets. Based on the principles of virtually shared energy and geographical proximity, RECs enable energy exchange among members without direct physical connections, relying instead on simultaneous energy injection and withdrawal through the public distribution network. This paper presents a comprehensive methodology for both the optimal design and management of RECs, improving their technical and economic performances. The optimal design identifies the best mix of REC members and determines the appropriate sizing of Photovoltaic (PV) and Battery Energy Storage Systems (BESS), aiming to minimise the total costs (purchase and installation costs, operation and maintenance costs, electricity costs) and to maximise the incentives on the shared energy, considering also Electric Vehicle (EV) charging infrastructure. Regarding the optimal management, a bi-level Energy Management System (EMS) is proposed. The upper level, controlled by the REC manager, seeks to maximize the shared energy, while the lower-level EMSs, located at members’ premises, perform detailed resource dispatch under both cooperative and non-cooperative behavioural models. Optimization results highlight that including mainly larger members improves economic viability, while the inclusion of a large number of residential users may not always generate benefits, due to increased REC management costs.

One of the ways to decarbonize cities and to enhance grid stability is to convert existing buildings into prosumers equipped with power plants able to supply electrical and thermal energy. The simulation of such multi-energy systems permits the analysis of their performance in steady-state and dynamic conditions, with the aim of defining effective operating strategies able to reduce emissions and costs. The present paper describes a dynamic simulation model, implemented in the Matlab/Simulink R2025a environment, developed to simulate the daily and weekly operation of a prosumer building equipped with a small-sized cogeneration unit, a Photovoltaic (PV) plant, a back-up boiler, a thermal storage system and some charging points for Electric Vehicles (EVs). The mathematical model is reported in detail, and the main results of the study are described, referring to operating days characterized by different weather conditions. Then, energy, economic and environmental performance indicators are defined and calculated for the different simulated scenarios. Over the considered time horizons, the simulation results highlight a significant increase in the electrical self-sufficiency of the facility up to 91.1% and an important reduction in total net operating costs up to 59.8%, compared to the AS-IS case (i.e., without the newly installed technologies).