Community-Based Energy Sharing using Game Theory Approaches for Benefit Distribution

This paper is centered on the concept of community-based energy sharing, focusing on the integration of electric vehicles and battery management systems. The study employs mixed integer linear programming optimization techniques to minimize the total energy costs of the entire community by maximizing energy sharing within it. The investigation focuses on exploring methods of distribution of benefits among community members considering BESS and EV demand. The paper explores the midmarket rate, supply-demand rate, Shapley value, and Nucleolus analysis as methods to distribute the benefits generated by the energy community. The analysis contributes to understanding how community-based energy sharing can vary depending on the distribution method. Moreover, the study presents two scenarios with a community of up to 20 agents: PV generation without batteries and PV with batteries, both considering forecasted EV demand. The influence of transactions in the energy community allows for a cost-benefit of around $6 \%$ to $13 \%$. When batteries are considered, the costs are reduced by up to $16 \%$. The benefit distribution schemes are also investigated, and their excess is analyzed for each case.