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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 consum and to 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. Joining a community can allow participants to reduce their energy bill and environmental footprint. However the distribution of gains generated through collective self consumption is one of the main obstacles. An interesting possibility comes from the game theory, especially from cooperative game, as solutions concepts already exist to solve this kind of problem. In this paper, a payoff distribution is proposed through a collaborative game. Two parrallel optimizations are established in order to compare the benefits of collective self consumption to individual self consumption. It is shown that the coordination of flexible devices to maximize the collective self-consumption rate generates gains on the electricity bill and environmental footprint. The aim of the study is then to explore ways to distribute these 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 will be established. A methodology is proposed to permit a fairer distribution of payoffs according to specific energy management parameters such as efficiency and flexibility.

Environmental issues are leading to rethink the way energy issues are approached. The integration of renewables energies into the energy mix is one of the long-term solutions for electricity production. Their intermittency forces utility companies to reconsider the way energy is consumed. Indeed, consumers will not remain regarding the electricity networks but will be asked to participate in the daily management of electricity. Several solutions are emerging around smart grids and demand side management, but they are mainly focused on technological solutions. Human behaviors are rarely considered in energy management algorithms. Similarly, the environmental impacts of the whole system are rarely quantified. Recently, legal incentives such as energy communities have appeared. These aim to include different actors to participate in economic operations regarding energy while reducing their environmental impacts. In this context, energy sharing, and self-consumption become at the heart of energy issues. In this paper, we propose to integrate hypotheses from the social and human sciences into an energy management of a community. Its environmental impact will also be integrated into this management through calculations of carbon emissions based on LCA methods. The gain/loss of stakeholders if they participate in a collective self-consumption operation regarding their sensibilities on energy consumptions will be discussed.