Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23532
Title: Traffic-constrained multiobjective planning of electric-vehicle charging stations
Authors: Wang, G
Xu, Z 
Wen, F
Wong, KP
Keywords: Charging station
Cross-entropy
Data-envelopment analysis
Distribution systems
Electric vehicle (EV)
Locating and sizing
Traffic flow
Issue Date: 2013
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on power delivery, 2013, v. 28, no. 4, 6555966, p. 2363-2372 How to cite?
Journal: IEEE transactions on power delivery 
Abstract: 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.
URI: http://hdl.handle.net/10397/23532
ISSN: 0885-8977
EISSN: 1937-4208
DOI: 10.1109/TPWRD.2013.2269142
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