A multi-objective distributed generation(DG)planning model based on the chance constrained programming theory is established

whose objective functions are minimizing the annual comprehensive cost and system risk

and the constraints are the correlation restrictions

the DG investment restrictions and various electrical restrictions. The model can take into account the correlations among the uncertainties. The non-dominated sorting genetic algorithm-Ⅱ together with correlation-handled distribution network probabilistic power flow

are applied to solve the model and get the Pareto optimal solution sets for the policy-maker to choose. Case studies are carried out on IEEE 33-bus distribution network and a practical 61-bus distribution network

with emphasis on the effects of correlations on the planning results.