With the rapid development of distribution networks in China and the increasing penetration of renewable and traditional energy sources, it is necessary to study the optimal allocation of capacity and optimal operation for the two stages of pre-planning and practical application of distribution networks. In this paper, the probability density function is used to model the uncertainty of “source” and “load” respectively, and the optimal allocation model of distributed power supply capacity of distribution network system is constructed by the equipment models of “wind generator”, “photovoltaic generator”, “diesel generator” and “battery”. Comprehensive cost and power supply security are taken as the objective function and constraints, respectively, to improve the distributed power supply capacity optimization, and adaptive sparrow search algorithm is applied to solve the model. In the comparative analysis of source-load synergy, source-load synergy and energy storage system joint optimization configuration scheme, the joint planning of DPV and ESS enhances the installed capacity of DPV by about 13.45%, and the average power generation of the joint planning scheme is 88.35 kW/h. The joint planning obviously enhances the installed capacity of DPV under the condition of slightly increasing the DPV curtailment. Examples are examined to verify the practical application of the proposed adaptive sparrow search algorithm in configuring the power supply capacity of the hybrid generation system, and the cost of using the cyclic charging operation scheme is 81,067 yuan lower than that of using the load-tracking scheme, and the economic effect has been significantly improved.