To improve the reliability and economy of system operation, this paper introduces an integrated demand response on the basis of the optimal scheduling of an integrated energy system. It also uses the mutual transformation relationship between different forms of energy to realize peak shaving and valley filling and improve energy use efficiency. An integrated demand response strategy is considered. A power load demand response model based on electricity price and a heat load demand response model based on incentive are established. Taking the minimum operation cost as the objective function, an integrated energy system scheduling model considering the balance of supply and demand and the constraints of energy supply and storage equipment is proposed. The improved second-order oscillatory particle swarm optimization algorithm is used to analyze the model. The algorithm updates the velocity iteration formula based on a conventional particle swarm optimization algorithm. This overcomes the problem that a conventional particle swarm optimization algorithm easily falls into a local optimum. The effectiveness of the proposed model and algorithm is verified by the simulation of an actual example. This work is supported by the National Natural Science Foundation of China (No. 52077108).