In order to improve the energy allocation efficiency of a high proportion of new energy integrated energy systems, an in-depth study of new energy uncertainty modeling and integrated energy system cooperative planning is conducted. This paper first describes the uncertain models of wind power output and electric vehicle charging load. Then a maximum entropy method based on a stochastic model is proposed to model the marginal probability distribution, and the principal component analysis method is used to extract typical operating scenarios. Finally, it considers the three scenarios of cooling period, heating period and transition period in a park to establish an integrated energy system cooperative planning model and use YALMIP tools to solve it. The results of simulation examples show that the method can obtain a cooperative planning scheme with higher economic value considering the uncertainty factors, and effectively improve the economy and flexibility of the integrated energy system. This work is supported by the National Natural Science Foundation of China (No. 52007193) and the Science and Technology Project of State Grid Zhejiang Electric Power Co., Ltd. (No. HZJTK09).