Research on peer-to-peer transaction strategy based on optimal matching mechanism considering user participation

Abstract:
With the wider application range of microgrid and more and more users of microgrid, it is a general trend for microgrid energy to join the P2P(peer-to-peer) market according to user needs and environmental needs. In view of the low enthusiasm of users to participate in P2P market, a psychological motivation model is proposed to formulate electricity pricing strategies and user priority strategies for different scenarios to meet the psychological mechanism model and improve consumers' participation. Considering the volatility of energy and the constraints of local communities, when energy is traded among scattered consumers, there is a problem of energy imbalance in the trading market. Therefore, microgrid users rely heavily on the power grid. This paper proposes a microgrid optimal alliance matching mechanism in intelligent distribution system, determines the optimal alliance between microgrids, and designs a hierarchical alliance formation mechanism to form microgrid user alliance. By matching the optimal alliance, the transaction matching degree between users is improved, and the energy transfer within the alliance is maximized to improve the energy efficiency. Through simulation and analysis, when users are optimized and the optimal model is selected, the transaction matching degree between users can be effectively improved. By modeling users and their constraints, the adopted transaction scheme can improve users' economic and environmental benefits. At the same time, the above benefits can give a positive feedback to the psychological motivation model, so as to form a virtuous circle and achieve the purpose of continuously encouraging users to participate.