Coalitional game-based gain generation and distribution for collective self-consumption in an energy community.

Climate change is requiring changes in energy use. The integration of renewable energy sources into the energy mix is a viable solution for electricity generation, but their intermittence forces us to imagine new ways to consume and distribute electricity. Thus, new economic models and new organizations have to be established. Energy communities are a recent legal solution to share renewable energy among local actors. These structures facilitate the set-up of collective self-consumption operations. Collective self-consumption is an interesting tool to increase local renewable energy consumption and limit energy losses on the distribution grid. Consequently, energy communities are pursuing a dual objective: reducing energy bills and the environmental footprint of the participants. However, the distribution of gains generated through collective self-consumption is one of the main obstacles to the implementation of energy communities. An interesting possibility comes from game theory, especially from cooperative games, as solutions concepts already exist to solve this kind of problem. In this paper, a payoff distribution is proposed through a collaborative game. The aim of the study is to explore ways to distribute gains generated by collective self consumptions on individual self consumptions. These gains are 8% on the total energy bill and 25% on the self-consumption rate, assuming a collective objective based on the self-consumption rate and individual objectives based on the price of energy. In order to distribute the financial gains, two major concepts in cooperative game theory are studied in this paper: the Shapley Value and the Nucleolus. The advantages and drawbacks of these concepts in an energy community context are identified, as these concepts are based on two different philosophies: The properties of individual fairness of the Shapley Value and collective fairness of the Nucleolus for energy management are therefore discussed. Furthermore, a methodology is proposed to enable a fairer distribution of payoffs according to specific energy management parameters, such as efficiency and flexibility. [ABSTRACT FROM AUTHOR]