Smart-grid development calls for effective solutions, such as electric vehicles (EVs), to meet the energy and environmental challenges. To facilitate large-scale EV applications, optimal locating and sizing of charging stations in smart grids have become essential. This paper proposes a multiobjective EV charging station planning method which can ensure charging service while reducing power losses and voltage deviations of distribution systems. A battery capacity-constrained EV flow capturing location model is proposed to maximize the EV traffic flow that can be charged given a candidate construction plan of EV charging stations. The data-envelopment analysis method is employed to obtain the final optimal solution. Subsequently, the well-established cross-entropy method is utilized to solve the planning problem. The simulation results have demonstrated the effectiveness of the proposed method based on a case study consisting of a 33-node distribution system and a 25-node traffic network system. © 1986-2012 IEEE.
Wang, G., Xu, Z., Wen, F., & Wong, K. (2013). Traffic-constrained multiobjective planning of electric-vehicle charging stations. IEEE Transactions on Power Delivery, 28(4), 2363-2372. https://doi.org/10.1109/TPWRD.2013.2269142