In order to reasonably allocate the benefits among the stakeholders in the integrated energy system and promote the decarbonization of energy, this paper develops an optimal scheduling model of integrated energy system with carbon capture systems based on master-slave game framework, which reduces carbon emissions from combined heating and power (CHP) units and system operating costs. A joint operation model of carbon capture system (CCS), power-to-gas (P2G) and CHP is built, and a revenue model for each subject of the integrated energy system on the basis of considering comprehensive demand response is established. The Stackelberg game model with one master and multiple slaves is built. Due to the characteristics of high-dimensional, nonlinear and non-convex optimization, the numerical method is difficult to solve and the traditional heuristic algorithm is easy to fall into the local optimum and the convergence speed is slow. Therefore, a novel distributed algorithm combined the improved coyote algorithm with quadratic programming is proposed. An industrial park in the northern China is taken as an example to verify, and the analysis results show that the model and the algorithm proposed in this paper effectively reduce the operating costs and carbon emissions of the integrated energy system and enhance the accommodation capacity of renewable energy compared to the traditional model.