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P2P as a Smarter Way of Energy Trading: A Game Theoretic Case Study for Multi-microgrids

This paper focuses on performing peer-to-peer (P2P) energy trading in a grid-tied multi-microgrid system (MMS). To do so, three microgrids, each consisting of distributed energy resources (DERs) such as wind turbines (WTs), solar photovoltaic (PV) systems, and battery storage systems, are considered. A game theory-based structure, supported by the Nash equilibrium, is then formulated to derive, and solve the multi-objective function (MoF) with the intention of allocating the correct sizing of each DER and finding out the optimum payoff values. The proposed optimisation model is also integrated with reliability index (IR) and levelised cost of energy (LCOE) in order to cut down the energy costs during intermittent periods of DERs. The developed framework is analysed and compared with other benchmark techniques on particle swarm optimisation (PSO) algorithm-facilitated MATLAB environment to conduct both P2P and peer-to-grid (P2G) energy trading. The simulation results: 1) verify the proposed MOF against various constant coefficients' combination, and 2) determine the most financially viable model for each DER through sensitivity analysis.