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.