In response to the gap that the existing methods do not fully consider the random characteristics of the distributed photovoltaic generation (DPVG) outputs and the electric vehicle charging station (EVCS) charging loads,probabilistic power flow is analyzed based on the scenario probability method,and a chance constraint based DPVG-EVCS joint planning model is developed. The locations and capacities of EVCSs and DPVGs are optimized to minimize energy loss in the distribution systems under a premise of ensuring that the operating conditions of the distribution system meet the chance constraints. Then,co-evolutionary algorithm (CA) based on the genetic algorithm (GA) is used in the DPVG-EVCS joint planning model calculation. The optimization is decomposed into an EVCS planning sub-optimization and an DPVG planning sub-optimization. Two sub-optimizations are solved by GA in parallel. And cooperate with two GA populations to evolve through the ecosystem until the optimal solution to the optimization problem to be sought is obtained. Finally,the IEEE 33 bus distribution system is built for simulation. The results show that the proposed model can obtain a reasonable planning scheme. And the solution efficiency of CA is high,which can significantly improve the work efficiency of planners.