A Multi-Agent Collaborative Operation Method for Enhancing the Comprehensive Load Capacity of Electric Vehicles in Distribution Networks

With the proposal of global low-carbon goals, research on new energy systems has become a major focus. As an emerging technology, electric vehicle (EV) can effectively reduce fossil energy consumption and enhance the integration of renewable energy sources. However, since EV usage patterns are highly dependent on human behavior, their uncertainty and complexity pose new challenges to the safe operation of distribution networks. Existing studies mainly focus on optimizing EV scheduling and orderly charging while overlooking the comprehensive carrying capacity of the distribution network for EV. Therefore, this paper proposes a method to enhance EV carrying capacity based on multi-agent cooperative control in the distribution network. First, a comprehensive EV carrying capacity index system is constructed, covering safety, stability, and quality aspects, and the Delphi method is used to integrate multiple indicators into a single optimization objective. Then, an improved particle swarm optimization (PSO) algorithm is applied to solve the multi-agent cooperative control model, aiming to enhance the EV hosting capacity of the distribution network. Finally, case studies based on the IEEE 33-bus system validate the effectiveness of the proposed method. The results demonstrate that the proposed approach significantly improves the maximum EV acceptance capacity and grid penetration rate while ensuring the safe, stable, and high-quality operation of the distribution network with minimal economic cost variation, providing effective support for the further development and deployment of EV.