Abstract: With the continuous development of the integrated energy systems, the traditional source-following-load model has changed its developig trend to the source-load interaction model. Therefore, a multi-objective bi-level planning approach for the integrated energy systems considering the source-load interactions is proposed. First, the interruptible and transferable loads of electricity, heating and cooling are introduced to participate in the integrated demand response. A dynamic pricing strategy is developed to match the renewable generation with the equivalent load. Then, a multi-objective bi-level planning and operation model of an integrated energy system containing the electric vehicle charging stations is established. The economic cost, the carbon emissions, and the autonomy of the system are taken as the objectives at the upper level of the planning model. The lower level model minimizes the total operating cost of the integrated energy system and the electric vehicle charging station. Finally, the non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) and the commercial solver CPLEX are used to obtain the Pareto frontier solution set, and the optimal solution is selected by using the Topsis method. The numerical studies indicate that the approach is able to reduce the economic costs and the carbon emissions, and improve the system autonomy.