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Towards reservation-based E-mobility service via hybrid of V2V and G2V charging modes

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  • Liu, Shuohan
  • Cao, Yue
  • Ni, Qiang
  • Xu, Lexi
  • Zhu, Yongdong
  • Zhang, Xin

Abstract

Due to the growing greenhouse effect, reducing greenhouse gas emissions is becoming increasingly important. Electric Vehicles (EVs), thanks to their lower carbon footprint, therefore are seen as the mainstream transportation of the future. However, single charging mode cannot accommodate a large number of parallel EV charging requests with limited charging infrastructures. To guarantee the Quality of Experience (QoE) of the charging service, this paper proposes a hybrid charging management scheme, by facilitating stable and fast charging from plug-in charging and flexible charging from V2V charging. Here, an optimization objective, charging cost is introduced as an optimization indicator. It considers charging price, charging waiting time and charging energy, to jointly optimize EV charging in price–time–energy dimensions. Each influencing factor is assigned a value through the Analytic Hierarchy Process (AHP) to identify its importance for EV charging. Meanwhile, due to the high mobility of EVs, charging reservation (including arrival time, required energy) is introduced, to optimize the charging selection with accurate information. Simulation results based on the Helsinki road topology show that the proposed scheme flexibly utilizes both charging modes and guarantees QoE for EV charging, in terms of increasing average charging energy and reducing charging price and charging waiting time.

Suggested Citation

  • Liu, Shuohan & Cao, Yue & Ni, Qiang & Xu, Lexi & Zhu, Yongdong & Zhang, Xin, 2023. "Towards reservation-based E-mobility service via hybrid of V2V and G2V charging modes," Energy, Elsevier, vol. 268(C).
    • Handle: RePEc:eee:energy:v:268:y:2023:i:c:s0360544223001317
    DOI: 10.1016/j.energy.2023.126737
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    References listed on IDEAS

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    1. Liu, Lu & Zhou, Kaile, 2022. "Electric vehicle charging scheduling considering urgent demand under different charging modes," Energy, Elsevier, vol. 249(C).
    2. Chao Luo & Yih-Fang Huang & Vijay Gupta, 2018. "Stochastic Dynamic Pricing for EV Charging Stations with Renewables Integration and Energy Storage," Papers 1801.02128, arXiv.org.
    3. Vaidya, Omkarprasad S. & Kumar, Sushil, 2006. "Analytic hierarchy process: An overview of applications," European Journal of Operational Research, Elsevier, vol. 169(1), pages 1-29, February.
    4. Haider, Sajjad & Rizvi, Rida e Zahra & Walewski, John & Schegner, Peter, 2022. "Investigating peer-to-peer power transactions for reducing EV induced network congestion," Energy, Elsevier, vol. 254(PB).
    5. Kaile Zhou & Lulu Wen, 2022. "Electric Vehicle Charging Scheduling Considering Different Charging Demands," Springer Books, in: Smart Energy Management, chapter 0, pages 223-249, Springer.
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    Cited by:

    1. 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.

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