A Distributed Model Predictive Coordination Strategy for Multi-Agent Systems

This paper investigates the optimization control methods for distributed battery energy storage systems and the balancing strategy of battery state of charge (SOC), proposing a cooperative control strategy based on SOC balancing. Utilizing multi- agent system (MAS) theory, the proposed method realizes coordinated control of battery energy storage systems. A distributed algorithm based on MAS is employed to achieve adaptive power command allocation, thereby achieving dynamic SOC balancing. To address the issue of low responsiveness in traditional multi-agent computing, a distributed model predictive control (MPC) algorithm is introduced to optimize traditional MAS algorithms, thus improving response speed. Finally, simulation verification using actual energy storage power data demonstrates the effectiveness and algorithmic responsiveness of the proposed strategy.