P2P Energy Trading Among Microgrids Under Partial-Decision Information

As the number of microgrids(MGs) continues to increase, multi-micro grids peer-to-peer (P2P) energy trading plays a crucial role in promoting regional energy interconnection and the local consumption of clean energy. Since each MG operates as an independent entity, there is often an information gap between them under partial-decision information, which may lead to inefficient or suboptimal transactions. To address this challenge, this paper proposes a distributed optimization method for P2P energy trading under partial-decision information. First, multi-micro grids transaction model is established, accounting for limited information exchange. Then, the model is enhanced based on estimations between participants, followed by parallel computation using the inexact alternating direction multiplier method (I-ADMM). Finally, through case analysis, it is demonstrated that after more than 10 iterations, the transactions between MGs converge to a consistent state.