The virtual power plant technology provides a new path for userside demand response to enhance the potential of distributed energy consumption and fill the blind area of grid dispatching. In order to guide users to participate in power dispatching, a virtual energy storage model including smart home load and building phasechange energy storage system with combined cooling and heating was constructed based on the incentive demand response power purchase agreement, and the schedulable margin of various resources was quantitatively analyzed; Taking user response characteristics as an indicator, using entropy weight method to evaluate the dynamic response performance of various user loads, setting the dynamic response priority of virtual energy storage participating in dispatching; taking the maximum benefit of virtual power plants as the goal, comprehensively considering resource power purchase costs, electric heating Based on factors such as balance, a terminal virtual power plant optimal scheduling model that integrates distributed power sources and smart community incentive response loads is proposed, and an improved light optimization algorithm is used to solve the model. The results verify the effectiveness of the proposed method.