1.Tsinghua Shenzhen International Graduate School, Shenzhen 518000, China;2.Lishui Power Supply Company of State Grid Zhejiang Electric Power Co., Ltd., Lishui 323000, China;3.State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 310027, China;4.Electric Power Research Institute of State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 310014, China

The escalating scale of electric vehicles (EVs) and renewable energy introduces uncertainties, posing severe challenges to the safe operation of distribution networks. In order to comprehensively consider multiple uncertainties and balance the operation cost with the system reliability, firstly, an EV-distribution network charging and discharging dispatching model based on the distributionally robust joint chance constrainted model is proposed. This model effectively manages the overall system reliability by jointly constraining nodal voltages, branch power, and reserve demand. Then, to solve the model, the joint chance constraint problem is transformed into a mixed-integer quadratic programming model based on the optimized Bonferroni approximation method. Notably, the risk level is also treated as a decision variable. Subsequently, the effectiveness and scalability of the proposed model are verified across various power systems. The results demonstrate that the proposed model overcomes the problems of classical stochastic and robust optimization, effectively balancing cost and reliability with high computational efficiency and good scalability. The model achieves approximately a 6.5% cost reduction compared to the Bonferroni approximation method.