With the large-scale participation of distributed resources such as 5G base stations and distributed photovoltaic (DPV) systems in multi-objective optimal dispatch of distribution networks, covering economic performance and power quality, the complexity of decision variables and the computational burden of distribution network control models have become increasingly prominent. To address these challenges, this paper proposes a hierarchical and zonal optimization method for distribution networks considering the regulation potential of 5G base stations and multi-resource coordination. First, considering the fluctuation characteristics of 5G base station traffic, a 5G base station regulation potential model is established, incorporating constraints on the idle state of charge (SOC). On this basis, a hierarchical and zonal optimization model for the distribution network is developed. At the upper layer, centralized dispatch is performed to optimize the overall benefits of the distribution network, thereby determining the operation schemes of intrinsic network resources such as switch capacitor banks and static reactive power generators. The lower level focuses on zonal dispatch: physical partitioning of the distribution network is carried out based on voltage-power sensitivity and a source-load mismatch index that considers the communication load of 5G base stations. A zonal coordinated optimization model is then established, oriented toward the idle SOC of 5G base stations and the residual capacity of DPV systems. This model is solved using a hybrid algorithm that combines second-order cone programming and the synchronous alternating direction method of multipliers. Finally, an improved IEEE 33-bus distribution network is used as a test case to verify the effectiveness of the proposed method. The results show that the proposed approach enhances the solvability of distribution network control models and improves both the economic performance and voltage quality of the distribution network.