Under the background of energy conservation

the intermittent distributed generator has been developed rapidly. It is represented by distributed wind turbine generator and photovoltaic generator. Based on the chance constrained programming

this paper proposes a model for optimal siting and sizing of intermittent distributed generator with the objective of minimizing annual comprehensive cost. The proposed model can take the correlations among wind speed

illumination intensity and load demand into account. The correlations are characterized by rank correlation coefficient matrix

Latin hypercube sampling and Cholesky decomposition are applied to generate the correlated samples. Dynamic niche differential evolution algorithm is used to solve the model. Case studies are carried out on the IEEE 33-bus distribution network

and the results verify the feasibility of the proposed model. This work is supported by National Key Technology R&D Program (No. 2013BAA01B04) and National Natural Science Foundation of China (No. 51261130473).