With the gradual increase of distributed generation (DG) and electric vehicle (EVs) integrated in the distribution network

traditional models for reconfiguration can hardly reflect the randomness and volatility. For this reason

a probabilistic scenario model of reconfiguration considering wind power and electric vehicle is developed first. Then

the probabilistic load flow of each scenario is calculated respectively. The model is simplified on the precondition of ensured accuracy to avoid combinatorial explosion

embodying the adaptability of the ever-increasing DGs and EVs. Finally

distribution network reconfiguration using the improved biogeography-based optimization algorithm is proposed

the improved codification strategy

the cosine migration model and the mutation operation are introduced to improve the search efficiency and bypass local optima. The proposed algorithm has shown advantages over other traditional artificial intelligence algorithms in 20 times of simulation of the IEEE 69-bus case. This work is supported by State Grid Corporation of China (No. 5211011400BT).