Regarding stochastic disturbance in power system brought by grid-connected distributed generation (DG), generally considering operational effectiveness, along with timing characteristics of wind speed and sunlight intensity, taking economy, power quality and environmental efficiency as goals, the optimization model of stochastic chance-constrained programming is built. The hybrid intelligent algorithm is used, which simulates the uncertainty functions based on support vector machine (SVM) and solves the model by multi-objective particle swarm optimization (MOPSO), and then the Pareto non-inferior decision set is obtained. Simulation results show that the planning model can fully take into account randomness, timing characteristics and grid-connected probability distribution of DG, and improve the efficiency of the algorithm, then verify the rationality and validity of the proposed approach. Moreover, the introduction of Pareto front gives fully choices to policymakers and possesses more engineering value