Optimal Scheduling for Multiple Virtual Power Plants Based on ADMM and Peer-to-Peer Trading Mechanism

With the continuous development of low-carbon energy, virtual power plant (VPP) plays a crucial role in the global energy transition. The core challenge of VPP nowadays lies in how to realize efficient scheduling and reasonable revenue distribution. In this paper, we propose an optimal scheduling framework for multiple VPPs based on the alternating direction multiplier method (ADMM) and the peer-to-peer (P2P) trading mechanism, aiming to address the limitations of the traditional scheduling methods in energy transmission and sharing. First, by introducing the ADMM algorithm, the framework can efficiently solve multi-subject, multi-constraint optimization problems, especially in real-time scheduling demonstrating efficiency and robustness. Secondly, this paper incorporates a P2P trading mechanism to dynamically adjust the revenue distribution of each participant to ensure that the energy supplier receives a reasonable reward based on its contribution, thus solving the distribution fairness problem in the traditional cooperative game model.