The penetration level of electric vehicles is closely related to the convenience of charging service provided by charging infrastructures. Additionally

the construction of charging infrastructures should be coordinated with the expansion planning of the power distribution system associated. Given this background

a strategy for deploying scattered charging posts based on the nodal charging demand of electric vehicles is presented first. Subsequently

a multi-objective optimization model

which is capable of minimizing the overall annual cost of investment and energy losses and maximizing the captured traffic flow by the fast charging stations (FCSs) simultaneously

is developed to address the coordinated planning problem of the power distribution system and electric vehicle charging systems. In the proposed model

the user equilibrium based traffic assignment model (UETAM) is applied to determining the traffic flow captured by FCSs. Furthermore

the queuing theory is utilized to determine the size of each FCS based on the principle that the average waiting time for charging service during the rush hour is less than or equal to the predefined threshold. Finally

the well-established non-dominant sorting genetic algorithm Ⅱ (NSGA-Ⅱ) with modified crossover and mutation operators is employed to seek the approximated Pareto frontier of the coupled 54-bus distribution system and 25-bus transportation testing system. Simulation results illustrate the basic characteristics of the model and solving method presented. This work is supported by National Basic Research Program of China (973 Program) (No. 2013CB228202) and National Natural Science Foundation of China (No. 51477151

No. 51361130152).