The construction and component of integrated energy system has changed with fast development of new energy emergence. Under the background, a multi-objective scheduling model is proposed which takes into account source and load uncertainty and multiple types of energy storage demand response. Firstly, an uncertain model of distributed wind power and electric heating gas load is established. The multiple types of energy storage incentives and price demand response models of electricity, gas and heat are then determined. Secondly, the purchase cost of electricity and gas energy, the cost of abandoning wind and the cost of environmental pollution are chosen as the objective of multi-objective optimization. Under the uncertainty of source & load side and the response of multiple types of energy storage demand, the constraints of multiple types of energy power balance, conversion and coupling between cooling and heating systems are considered to establish a source, grid and storage multi-objective optimal scheduling model for integrated energy system. Then the multi-objective Particle Swarm Optimization algorithm is utilized to optimize the constructed model. Finally, a park energy system is simulated. The results show that the proposed optimization is effective. The model can provide a new strategy for the mutual energy service of the park's comprehensive energy source storage and demand.