Research on Peer-to-peer Energy Trading within Community Microgrids

As the penetration rate of distributed energy in the distribution network continues to increase, new power trading models in the microgrid environment have become an important way to improve the efficiency of new energy consumption. This study, targeting community microgrids with distributed generation and energy storage, has constructed a market-oriented operation framework based on peer-to-peer ($\mathbf{P 2 P}$) trading. This model adopts a continuous two-way auction mechanism, allowing microgrid users to achieve two-way trading of electricity through bidding. In terms of the participation of the energy storage system, the model uses a predictive control method to dynamically optimize the charging and discharging strategies, providing scientific bidding decision-making basis for market entities. At the same time, an improved zero-information bidding algorithm with adaptive learning ability is introduced to effectively enhance the autonomous decision-making ability of each participant. Simulation results based on actual microgrid cases show that the proposed distributed trading mechanism can significantly improve the comprehensive economic benefits of community users and provide strong support for the large-scale development of new energy.