IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v10y2018i5p40-d144424.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/10/5/40/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/10/5/40/
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aziz, Muhammad & Oda, Takuya & Ito, Masakazu, 2016. "Battery-assisted charging system for simultaneous charging of electric vehicles," Energy, Elsevier, vol. 100(C), pages 82-90.
    2. 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.
    3. Zhenya Ji & Xueliang Huang & Changfu Xu & Houtao Sun, 2016. "Accelerated Model Predictive Control for Electric Vehicle Integrated Microgrid Energy Management: A Hybrid Robust and Stochastic Approach," Energies, MDPI, vol. 9(11), pages 1-18, November.
    4. Yunna Wu & Meng Yang & Haobo Zhang & Kaifeng Chen & Yang Wang, 2016. "Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method," Energies, MDPI, vol. 9(3), pages 1-20, March.
    5. Alessandro Ciocia & Angela Amato & Paolo Di Leo & Stefania Fichera & Gabriele Malgaroli & Filippo Spertino & Slavka Tzanova, 2021. "Self-Consumption and Self-Sufficiency in Photovoltaic Systems: Effect of Grid Limitation and Storage Installation," Energies, MDPI, vol. 14(6), pages 1-24, March.
    6. Anamarija Falkoni & Antun Pfeifer & Goran Krajačić, 2020. "Vehicle-to-Grid in Standard and Fast Electric Vehicle Charging: Comparison of Renewable Energy Source Utilization and Charging Costs," Energies, MDPI, vol. 13(6), pages 1-22, March.
    7. 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.
    8. Bin Ye & Jingjing Jiang & Lixin Miao & Peng Yang & Ji Li & Bo Shen, 2015. "Feasibility Study of a Solar-Powered Electric Vehicle Charging Station Model," Energies, MDPI, vol. 8(11), pages 1-19, November.
    9. Keumju Lim & Justine Jihyun Kim & Jongsu Lee, 2020. "Forecasting the future scale of vehicle to grid technology for electric vehicles and its economic value as future electric energy source: The case of South Korea," Energy & Environment, , vol. 31(8), pages 1350-1366, December.
    10. Robby Dwianto Widyantara & Muhammad Adnan Naufal & Poetro Lebdo Sambegoro & Ignatius Pulung Nurprasetio & Farid Triawan & Djati Wibowo Djamari & Asep Bayu Dani Nandiyanto & Bentang Arief Budiman & Muh, 2021. "Low-Cost Air-Cooling System Optimization on Battery Pack of Electric Vehicle," Energies, MDPI, vol. 14(23), pages 1-14, November.
    11. Scheepers, Martin & Palacios, Silvana Gamboa & Jegu, Elodie & Nogueira, Larissa P. & Rutten, Loes & van Stralen, Joost & Smekens, Koen & West, Kira & van der Zwaan, Bob, 2022. "Towards a climate-neutral energy system in the Netherlands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    12. Mohamed Abdel-Monem & Omar Hegazy & Noshin Omar & Khiem Trad & Sven De Breucker & Peter Van Den Bossche & Joeri Van Mierlo, 2016. "Design and Analysis of Generic Energy Management Strategy for Controlling Second-Life Battery Systems in Stationary Applications," Energies, MDPI, vol. 9(11), pages 1-25, October.
    13. Yuttana Kongjeen & Krischonme Bhumkittipich, 2018. "Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis," Energies, MDPI, vol. 11(6), pages 1-16, June.
    14. Karam Hwang & Jaeyong Cho & Dongwook Kim & Jaehyoung Park & Jong Hwa Kwon & Sang Il Kwak & Hyun Ho Park & Seungyoung Ahn, 2017. "An Autonomous Coil Alignment System for the Dynamic Wireless Charging of Electric Vehicles to Minimize Lateral Misalignment," Energies, MDPI, vol. 10(3), pages 1-20, March.
    15. George Baure & Matthieu Dubarry, 2020. "Durability and Reliability of EV Batteries under Electric Utility Grid Operations: Impact of Frequency Regulation Usage on Cell Degradation," Energies, MDPI, vol. 13(10), pages 1-11, May.
    16. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
    17. Tobias Porsinger & Przemyslaw Janik & Zbigniew Leonowicz & Radomir Gono, 2017. "Modelling and Optimization in Microgrids," Energies, MDPI, vol. 10(4), pages 1-22, April.
    18. S. Muhammad Bagher Sadati & Jamal Moshtagh & Miadreza Shafie-khah & João P. S. Catalão, 2017. "Risk-Based Bi-Level Model for Simultaneous Profit Maximization of a Smart Distribution Company and Electric Vehicle Parking Lot Owner," Energies, MDPI, vol. 10(11), pages 1-16, October.
    19. Ana Pavlićević & Saša Mujović, 2022. "Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses," Energies, MDPI, vol. 15(19), pages 1-24, September.
    20. Su Su & Hao Li & David Wenzhong Gao, 2017. "Optimal Planning of Charging for Plug-In Electric Vehicles Focusing on Users’ Benefits," Energies, MDPI, vol. 10(7), pages 1-15, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:10:y:2018:i:5:p:40-:d:144424. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.