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A Study on Coordinated Optimization of Electric Vehicle Charging and Charging Pile Selection

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  • Lixing Chen

    (School of Electrical & Information Engineering, Jiangsu University of Technology, Changzhou 213001, China)

  • Xueliang Huang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Hong Zhang

    (School of Electrical & Information Engineering, Jiangsu University of Technology, Changzhou 213001, China)

  • Yinsheng Luo

    (School of Electrical & Information Engineering, Jiangsu University of Technology, Changzhou 213001, China)

Abstract

This paper was intended to explore the mutual influences between electric vehicle (EV) charging and charging facility planning, to establish a two-stage model for optimizing the EVs’ charging and charging piles’ selection. In the first stage, the distribution pattern of the demands for EV charging, and various EVs were effectively grouped, in order to reduce the amount of computation for solving the second stage model. The goal of the second stage was to minimize the annual investment and electricity purchasing costs on the charging piles, and the coordinated optimization was carried out for EV charging and charging pile selection. The CPLEX and IP_SOLVE packages were used in MATLAB (R2014a/64 bits) to solve the established optimization model. The simulation results showed that, compared with the scheme for selecting the charging pile under the typical charging pattern (TCP), the total cost of the charging pile could be reduced by 6.32% with a scheme under the optimized charging pattern (OCP), thereby promoting the coordinated development of both the EVs and charging facilities.

Suggested Citation

  • Lixing Chen & Xueliang Huang & Hong Zhang & Yinsheng Luo, 2018. "A Study on Coordinated Optimization of Electric Vehicle Charging and Charging Pile Selection," Energies, MDPI, vol. 11(6), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1350-:d:149041
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    References listed on IDEAS

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    3. Lixing Chen & Xueliang Huang & Zhong Chen & Long Jin, 2016. "Study of a New Quick-Charging Strategy for Electric Vehicles in Highway Charging Stations," Energies, MDPI, vol. 9(9), pages 1-20, September.
    4. Mingchao Xia & Qingying Lai & Yajiao Zhong & Canbing Li & Hsiao-Dong Chiang, 2016. "Aggregator-Based Interactive Charging Management System for Electric Vehicle Charging," Energies, MDPI, vol. 9(3), pages 1-14, March.
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    6. Lixing Chen & Zhong Chen & Xueliang Huang & Long Jin, 2016. "A Study on Price-Based Charging Strategy for Electric Vehicles on Expressways," Energies, MDPI, vol. 9(5), pages 1-18, May.
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    Cited by:

    1. Shahid Hussain & Subhasis Thakur & Saurabh Shukla & John G. Breslin & Qasim Jan & Faisal Khan & Ibrar Ahmad & Mousa Marzband & Michael G. Madden, 2022. "A Heuristic Charging Cost Optimization Algorithm for Residential Charging of Electric Vehicles," Energies, MDPI, vol. 15(4), pages 1-18, February.
    2. Bruno Pinto & Filipe Barata & Constantino Soares & Carla Viveiros, 2020. "Fleet Transition from Combustion to Electric Vehicles: A Case Study in a Portuguese Business Campus," Energies, MDPI, vol. 13(5), pages 1-24, March.

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