随着以风电、光伏为主的分布式电源在终端能源消费中的占比不断提升，充分调用电网内部的灵活性资源，提升主动配电网（Active Distribution Networks，ADN）的调控能力具有重要意义。为此，本文提出一种考虑5G基站可调度备用储能和智能软开关的ADN协同优化调度方法。首先，对5G基站功耗模型进行分析，建立了计及5G基站通信负载和ADN供电节点可靠性的备用储能容量评估模型。在此基础上，以最小化ADN综合运行费用为目标函数，综合考虑风电、光伏出力和负荷需求的不确定性，构建了基于机会约束的ADN协同优化调度模型。为提高模型求解效率，采用二阶锥松弛转凸法和基于拉丁超立方采样的机会约束确定性转化法，将模型转化为混合整数二阶锥规划问题。最后，通过IEEE-33节点ADN算例，验证了本文所提方法的可行性和有效性。

As the proportion of distributed generation, mainly wind turbine and photovoltaic, in terminal energy consumption increases, it is of great significance to fully utilize the flexibility resources within the power grid and enhance the regulation capability of active distribution networks (ADN). To this end, this paper proposes an ADN collaborative optimization scheduling method considers dispatchable backup battery of 5G base station (BS) and soft open point. Firstly, an analysis of the power consumption model of 5G BS is conducted, leading to the establishment of a backup battery capacity evaluation model that considers the communication load of 5G BS and the reliability of ADN nodes. On this basis, taking minimizing the comprehensive operating cost of ADN as the objective function and considering the uncertainty of wind power, photovoltaic output and load demand, an ADN collaborative optimal scheduling model based on chance constraints was constructed. To enhance the model's solution efficiency, a second-order cone relaxation to convex method and a chance-constrained determinization approach based on Latin hypercube sampling are employed. These methods transform the model into a mixed-integer second-order cone programming problem. Finally, the feasibility and effectiveness of the proposed method are verified by the IEEE-33 bus ADN case.