Abstract: As the random fluctuation of renewable energy distribution and the uncertainty of user energy consumption lead to deviations between the planning of integrated energy system (IES) and the actual demand, the planning strategy is difficult to take into account multiple optimization objectives, and the role of IES in energy conservation, emission reduction and coordination of source load resources cannot be fully brought into play. In this paper, a multi-energy complementary IES planning scheme for electric heat is proposed, which integrates wind, solar, geothermal and other renewable energy sources. Based on regional natural resource endowment and different users' energy consumption characteristics, a bi-level optimization model is constructed considering multiple optimization objectives. An improved particle swarm optimization algorithm and Gurobi solver are used to calculate the optimal solution set and select the best solution according to the decision maker's guidance. Finally, a fuzzy evaluation method is used to evaluate the planning results , and multi-scenario case studies are conducted for experimental validation.The results demonstrate that the proposed model effectively balances various performance indicators, providing an optimized configuration that aligns with regional resource endowments and user energy consumption characteristics. This approach reduces the comprehensive operational cost, mitigates environmental pollution, and enhances the regional energy recycling rate.