Fairness and reward in Energy Communities: Game-theory versus simplified approaches

The energy transition requires huge investments. However, increasing citizen participation in the energy system by providing flexibility and decentralized generation and storage could provide relief and reduce the total system costs. In this regard, several governments are promoting the development of aggregations of users, sometimes in the form of Energy Communities, to foster the desired socio-economic and environmental goals. Energy Communities are expected to attract local investors and induce positive behavioural change that lowers the burden on the power grid. However, business models and fairness in the reward schemes are matters of concern that cannot be disregarded in the optimal planning of Energy Communities. In this framework, this paper proposes a comparison of different schemes that can be used to share revenues and rewards among the members of a Community. The cooperative optimization problem, calculated using Mixed-Integer Linear Programming (MILP), is compared to non-cooperative approaches where users do not cooperate. Simple rewarding schemes, e.g. proportional to the shared energy and investment costs, are compared to game-theory approaches using Shapley Value, Nucleolus, and VarLeast-Core. A numerical case study suggests that the procedure can be implemented in practice and suggests approximate techniques to address reward distribution schemes for Energy Communities.