Supported by large-scale centralized charging stations of electric vehicles (EVs)

the battery swapping mode with battery leasing is a commercially competitive way for the development of EVs. Given this background

a network reconfiguration strategy taking the EV charging stations into account is presented. First

the capacity provided by the batteries in an EV charging station is modeled

and thus the capacity for restarting the non-black-start units can be obtained whenever a power outage occurs. Then

a bi-level optimization based model for the network reconfiguration is proposed. In the upper-level optimization model

the recovery time of a generating unit is determined by maximizing the restored generation capacity

while in the lower-level the restoration path is optimized by minimizing the charging capacitance of the recovered lines. A chance-constrained programming method is employed to address the risks arising from uncertain factors during the system restoration

and then a bi-level optimization model for the network reconfiguration based on chance-constrained programming is presented. An improved particle swarm optimization algorithm is employed to solve the model developed. Finally

a modified New England 10-unit 39-bus power system is employed to demonstrate the basic characteristics of the model and method developed. This work is supported by National Basic Research Program of China (973 Program) (No. 2013CB228202)

National Natural Science Foundation of China (No. 51177145

No. 51377005) and a project from State Grid Zhejiang Electric Power Company (No. 5211DF13500M).