【摘要】 在车-能互动背景下，大规模分布式能源与电动汽车（EV）集群规模化接入综合能源系统（IES），导致了IES运营商（IESO）、EV集群及用户之间的利益均衡问题。为此，提出一种基于改进灰狼算法的主从博弈优化运行策略。首先，构建以IESO为领导者、EV集群与用户为跟随者的主从博弈模型；其次，通过Tent混沌映射优化初始种群分布，调整收敛因子增强全局搜索能力，并融合差分进化策略以避免算法陷入局部最优；同时通过动态定价机制引导EV集群与用户参与需求响应，挖掘EV集群可调度潜力。算例分析表明，所提策略在提升算法性能的同时，能有效协调IES设备出力与经济利益均衡，降低系统运行成本，并优化EV集群的充放电行为。更多还原

【Abstract】 Under the vehicle-energy interaction paradigm,the large-scale integration of distributed energy resources and electric vehicle(EV) clusters into the integrated energy system(IES) has led to the challenge of balancing interests among the IES operator(IESO),EV clusters,and end-users. To address this,an optimized operation strategy based on an improved grey wolf algorithm within a Stackelberg game framework is proposed. First,a Stackelberg game model is established with the IESO as the leader and EV clusters along with users as followers. Second,the Tent chaotic mapping is employed to optimize the initial population distribution,the convergence factor is adjusted to enhance global search capability,and a differential evolution strategy is integrated to avoid local optima. Meanwhile,a dynamic pricing mechanism is introduced to guide EV clusters and users in participating in demand response,thereby unlocking the dispatchable potential of EV clusters. Case study results demonstrate that the proposed strategy not only improves the performance of the algorithm but also effectively coordinates the output of IES equipment with economic interest equilibrium,reduces system operating costs,and optimizes the charging and discharging behavior of EV clusters.更多还原