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An EV Charging Scheduling Mechanism Based on Price Negotiation

Author

Listed:
  • Baocheng Wang

    (School of Computer, North China University of Technology, Beijing 100144, China)

  • Yafei Hu

    (School of Computer, North China University of Technology, Beijing 100144, China)

  • Yu Xiao

    (School of Computer, North China University of Technology, Beijing 100144, China)

  • Yi Li

    (School of Computer, North China University of Technology, Beijing 100144, China)

Abstract

Scheduling EV user’s charging behavior based on charging price and applying renewable energy resources are the effective methods to release the load pressure of power grids brought about by the large-scale popularity of electric vehicles (EVs). This paper presents a novel approach for EV charging scheduling based on price negotiation. Firstly, the EV charging system framework based on price negotiation and renewable energy resources is discussed. Secondly, the price negotiation model is presented, including the initial price models and the conditions of transactions. Finally, an EV charging scheduling mechanism based on price negotiation (CSM-PN), including the price adjustment strategies of both the operator and EV users is proposed to seek a final transaction during multi-round price negotiation. Simulation results show that this novel approach can effectively improve the charging station operator’s income, reduce the EV users’ costs, and balance the load of the power grid while improving the efficiency of the EV charging system.

Suggested Citation

  • Baocheng Wang & Yafei Hu & Yu Xiao & Yi Li, 2018. "An EV Charging Scheduling Mechanism Based on Price Negotiation," Future Internet, MDPI, vol. 10(5), pages 1-11, May.
    • Handle: RePEc:gam:jftint:v:10:y:2018:i:5:p:40-:d:144424
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    References listed on IDEAS

    as
    1. Muhammad Aziz & Takuya Oda & Takashi Mitani & Yoko Watanabe & Takao Kashiwagi, 2015. "Utilization of Electric Vehicles and Their Used Batteries for Peak-Load Shifting," Energies, MDPI, vol. 8(5), pages 1-19, April.
    2. Yusuf A. Sha’aban & Augustine Ikpehai & Bamidele Adebisi & Khaled M. Rabie, 2017. "Bi-Directional Coordination of Plug-In Electric Vehicles with Economic Model Predictive Control," Energies, MDPI, vol. 10(10), pages 1-20, September.
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    Cited by:

    1. Qin Chen & Komla Agbenyo Folly, 2022. "Application of Artificial Intelligence for EV Charging and Discharging Scheduling and Dynamic Pricing: A Review," Energies, MDPI, vol. 16(1), pages 1-26, December.
    2. Obeid, Hassan & Ozturk, Ayse Tugba & Zeng, Wente & Moura, Scott J., 2023. "Learning and optimizing charging behavior at PEV charging stations: Randomized pricing experiments, and joint power and price optimization," Applied Energy, Elsevier, vol. 351(C).

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