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Electric vehicle charging scheduling considering infrastructure constraints

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  • Wu, Ji
  • Su, Hao
  • Meng, Jinhao
  • Lin, Mingqiang

Abstract

The impacts of large-scale electric vehicles (EVs) charging on the power grid and the lack of charging infrastructure may directly hinder the promotion of EVs. With the limited number of charging piles and maximum instantaneous power at the charging station, how to effectively charge scheduling for EVs and reduce the charging cost for users becomes an important issue. To address this problem, we propose an EV charging scheduling strategy in response to time-of-use price. Here, the least cost of charging is set as the objective function and the limitations of charging piles number and instantaneous power of the stations are constraints. EV charging behavior characteristic is simulated using the Monte Carlo method based on 876,012 sets of historical charging data. Then, after solving the optimization problem by the adaptive genetic algorithm, each EV is assigned a specific charging pile that can meet its charging demand. The experimental results show that the proposed method can achieve better results than the comparative methods while ensuring the safe operation of charging stations. The effect of peak and valley reduction on the grid side is also realized.

Suggested Citation

  • Wu, Ji & Su, Hao & Meng, Jinhao & Lin, Mingqiang, 2023. "Electric vehicle charging scheduling considering infrastructure constraints," Energy, Elsevier, vol. 278(PA).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:pa:s0360544223012008
    DOI: 10.1016/j.energy.2023.127806
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Qingyuan Yan & Yang Gao & Ling Xing & Binrui Xu & Yanxue Li & Weili Chen, 2024. "Optimal Scheduling for Increased Satisfaction of Both Electric Vehicle Users and Grid Fast-Charging Stations by SOR&KANO and MVO in PV-Connected Distribution Network," Energies, MDPI, vol. 17(14), pages 1-36, July.
    2. Zaidi, I. & Oulamara, A. & Idoumghar, L. & Basset, M., 2024. "Maximizing the number of satisfied charging demands of electric vehicles on identical chargers," Omega, Elsevier, vol. 127(C).
    3. Mingyi Liu & Bin Zhang & Jiaqi Wang & Han Liu & Jianxing Wang & Chenghao Liu & Jiahui Zhao & Yue Sun & Rongrong Zhai & Yong Zhu, 2023. "Optimal Configuration of Wind-PV and Energy Storage in Large Clean Energy Bases," Sustainability, MDPI, vol. 15(17), pages 1-23, August.
    4. Heping Jia & Qianxin Ma & Yun Li & Mingguang Liu & Dunnan Liu, 2023. "Integrating Electric Vehicles to Power Grids: A Review on Modeling, Regulation, and Market Operation," Energies, MDPI, vol. 16(17), pages 1-18, August.
    5. Zhang, Rui & Yu, Jilai, 2024. "Evaluating multi-dimensional response capability of electric bus considering carbon emissions and traffic index," Energy, Elsevier, vol. 286(C).
    6. Zoutendijk, M. & Mitici, M., 2024. "Fleet scheduling for electric towing of aircraft under limited airport energy capacity," Energy, Elsevier, vol. 294(C).
    7. Yin, Wanjun & Jia, Leilei & Ji, Jianbo, 2024. "Energy optimal scheduling strategy considering V2G characteristics of electric vehicle," Energy, Elsevier, vol. 294(C).

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