针对当前有源配电网调控资源和调控能力不足的问题，提出了一种电动汽车(Electric Vehicle， EV)参与有源配电网优化的两阶段调控方法，该方法考虑了EV用户出行存在不确定背景下的EV调控对用户充电需求的影响，旨在降低调控对车主出行影响的前提下充分释放EV的调控潜力。首先建立了表征对EV用户充电影响的电量偏差指标并进行考虑电量偏差的EV聚合，接着进行含EV聚合体、储能及分布式电源的有源配电网优化调控，最后将EV充电调控指令按照最小化对用户出行影响的方式进行分解。在改进IEEE33系统的仿真中验证了所提策略的有效性，数值实验表明所提策略在兼顾了EV的调控能力及用户充电需求，相比传统方法EV电量偏差降低了25%，消纳能力提高了47%。

To address the issue of insufficient regulation resources and capabilities in the current active distribution networks (ADNs), a two-stage regulation method for Electric Vehicle (EV) participation in active distribution network optimization is proposed. The method considers the travel factors of EV users, and aims to fully release the regulation potential of EV on the premise of reducing the impact of regulation on the travel of owners. Focusing on the electric vehicle (EV) resources, a charging deviation index was first established to characterize the impact on EVs' charging. Then, EV aggregation considering charging deviation was carried out, followed by ADN optimal scheduling of EV aggregation, energy storage and distributed generations. Finally, the overall EV charging command is decomposed to each EV by minimizing the impact on EV users. The effectiveness of the proposed strategy was verified in the simulation of improving the IEEE33 system. Numerical experiments demonstrate that the proposed strategy effectively considers both the regulation capability of EVs and the charging demands of users. Compared to traditional methods, it reduces EV power deviation by 25% and increases consumption capacity by 47%.