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.