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Energy communities (ECs) are currently seen as an important pathway to increase the participation of citizens in the energy transition. The present work proposes a mixed integer linear programming (MILP) optimization model that provides the optimal design of a renewable energy community (REC) in terms of best technologies and chosen members. Different objective functions are investigated so that the REC’s design can be studied from different perspectives. The first objective is related to the minimization of total annualized costs (TAC) while the second one regards the maximization of the shared energy. The model considers one year as time horizon with a timestep of one hour. A case study is defined by considering the municipality of Plodio, located in the northwest of Italy, as the host of a potential REC. A total of 11 possible users are introduced, including municipality and residential users. In cost-optimized scenarios, the REC design is characterized by fewer users but has the maximum installation of PV modules. However, most of the revenues are obtained due to the selling of electricity and not due to its sharing. When the shared energy is maximized, all the candidate members are chosen and technologies such as wind turbines and batteries are exploited to increase the number of periods characterized by the injection of electricity into the grid. It is also noted that higher electricity prices increase the profitability of the investment. Finally, it is shown that the inclusion of an industrial user positively influences energy-sharing indicators.
Laurini et al. (Tue,) studied this question.