A combination of MILP and game theory methods for P2P energy trading by considering network constraints

Peer-to-peer energy trading is one of the new approaches in the field of energy management. In this approach, participants who have the ability to generate energy can directly interact with other individuals who need energy and engage in energy exchange. One of the challenges in this area is the lack of a suitable framework for interaction and energy exchange. In this paper, a new approach based on game theory and MILP optimization is proposed for market settlement in P2P energy trading. In the designed game, each buyer's strategy is to determine their desired price for each unit of energy. On the other hand, each seller's strategy is to determine the amount of energy (in response to the price declared by each buyer) that they are willing to sell. The price and amount of energy at which the utility function of buyers and sellers reaches its maximum value are considered as the best response (Nash equilibrium). The MILP optimization method has been employed to maximize the overall social welfare. In fact, buyers and sellers are matched in a way that maximizes the total social welfare. Also, in order to prevent overload and congestion in lines, a constraint has been considered in the MILP optimization structure. It means that if there is a constraint on the capacity of the lines for power transmission, energy buying and selling strategies change in a way that each line passes power up to its allowed capacity. The results obtained from simulation on 12, 20 and 60 bus test systems demonstrate the effective performance of the proposed approach.