Multi-objective locating of electric vehicle charging stations considering travel comfort in urban transportation system

Environmental concerns of using fossil fuel vehicles and recent developments in electric vehicle (EV) technology have attracted the attention of the international community to use EVs. A design strategy is proposed by simultaneously considering a distribution network and an urban transportation network, that maximises drivers' travel comfort in urban trips and reduces costs of both charging station (CS) installation and losses. The proposed strategy meets various constraints such as, properly locating CSs in the city, considering traffic volume, taking the shortest route, reducing charging waiting time, limits of bus voltages, power balance, the permissible loading of lines. The travel comfort index corresponds to a situation in which the driver does not experience a depleted battery and successfully finish the trip. Since the movement of vehicles over the course of a day does not follow any particular pattern, unscented transformation is used to investigate the uncertainty in different probabilistic parameters of EVs. Moreover, by clustering the locations of EVs, the optimal locations of EV CSs are determined over the course of the day (in several time steps) using a multi-objective function based on a GA. The simulation results of the sample urban transportation and distribution networks confirm the efficacy of the proposed method.

Automated summary

This study proposes a design strategy that enhances the comfort of electric vehicles in urban trips and reduces installation costs and losses of charging stations by considering a distribution network and an urban transportation network. Various constraints such as proper placement of charging stations, traffic volume, shortest route, and reducing waiting time are taken into account to optimize the design and improve drivers' travel experience.