Journal
IEEE TRANSACTIONS ON POWER DELIVERY
Volume 28, Issue 4, Pages 2363-2372Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRD.2013.2269142
Keywords
Charging station; cross-entropy; data-envelopment analysis; distribution systems; electric vehicle (EV); locating and sizing; traffic flow
Categories
Funding
- National Basic Research Program (973 Program) [2013CB228202]
- Hong Kong Polytechnic University [51107114, 51177145, G-U962, A-SA73]
- Shenzhen Government Fundamental Research Program [JC201006040906A]
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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.
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