IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i18p6735-d915168.html
   My bibliography  Save this article

An OCPP-Based Approach for Electric Vehicle Charging Management

Author

Listed:
  • Sara Hsaini

    (TICLab, International University of Rabat, Rabat 11103, Morocco)

  • Mounir Ghogho

    (TICLab, International University of Rabat, Rabat 11103, Morocco
    School of EEE, University of Leeds, Leeds LS2 9JT, UK)

  • My El Hassan Charaf

    (LaRI Laboratory, Faculty of Sciences, Ibn Tofail University, Kenitra 14000, Morocco)

Abstract

This paper proposes a smart system for managing the operations of grid-connected charging stations for electric vehicles (EV) that use photovoltaic (PV) sources. This system consists of a mobile application for EV drivers to make charging reservations, an algorithm to optimize the charging schedule, and a remote execution module of charging operations based on the open charge point protocol (OCPP). The optimal charging schedule was obtained by solving a binary integer programming problem. The merits of our solution are illustrated by simulating different charging demand scenarios.

Suggested Citation

  • Sara Hsaini & Mounir Ghogho & My El Hassan Charaf, 2022. "An OCPP-Based Approach for Electric Vehicle Charging Management," Energies, MDPI, vol. 15(18), pages 1-14, September.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6735-:d:915168
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/18/6735/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/18/6735/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Simone Orcioni & Massimo Conti, 2020. "EV Smart Charging with Advance Reservation Extension to the OCPP Standard," Energies, MDPI, vol. 13(12), pages 1-21, June.
    2. George S. Fernandez & Vijayakumar Krishnasamy & Selvakumar Kuppusamy & Jagabar S. Ali & Ziad M. Ali & Adel El-Shahat & Shady H. E. Abdel Aleem, 2020. "Optimal Dynamic Scheduling of Electric Vehicles in a Parking Lot Using Particle Swarm Optimization and Shuffled Frog Leaping Algorithm," Energies, MDPI, vol. 13(23), pages 1-26, December.
    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. Abdul Ghani Olabi & Enas Taha Sayed, 2023. "Developments in Hydrogen Fuel Cells," Energies, MDPI, vol. 16(5), pages 1-5, March.
    2. Giovanni Gino Zanvettor & Marco Casini & Antonio Giannitrapani & Simone Paoletti & Antonio Vicino, 2022. "Optimal Management of Energy Communities Hosting a Fleet of Electric Vehicles," Energies, MDPI, vol. 15(22), pages 1-16, November.
    3. Shariatio, O. & Coker, P.J. & Smith, S.T. & Potter, B. & Holderbaum, W., 2024. "An integrated techno-economic approach for design and energy management of heavy goods electric vehicle charging station with energy storage systems," Applied Energy, Elsevier, vol. 369(C).
    4. Pegah Alaee & Julius Bems & Amjad Anvari-Moghaddam, 2023. "A Review of the Latest Trends in Technical and Economic Aspects of EV Charging Management," Energies, MDPI, vol. 16(9), pages 1-28, April.
    5. Konstantina Dimitriadou & Nick Rigogiannis & Symeon Fountoukidis & Faidra Kotarela & Anastasios Kyritsis & Nick Papanikolaou, 2023. "Current Trends in Electric Vehicle Charging Infrastructure; Opportunities and Challenges in Wireless Charging Integration," Energies, MDPI, vol. 16(4), pages 1-28, February.

    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. Konstantina Dimitriadou & Nick Rigogiannis & Symeon Fountoukidis & Faidra Kotarela & Anastasios Kyritsis & Nick Papanikolaou, 2023. "Current Trends in Electric Vehicle Charging Infrastructure; Opportunities and Challenges in Wireless Charging Integration," Energies, MDPI, vol. 16(4), pages 1-28, February.
    2. Suchitra Dayalan & Sheikh Suhaib Gul & Rajarajeswari Rathinam & George Fernandez Savari & Shady H. E. Abdel Aleem & Mohamed A. Mohamed & Ziad M. Ali, 2022. "Multi-Stage Incentive-Based Demand Response Using a Novel Stackelberg–Particle Swarm Optimization," Sustainability, MDPI, vol. 14(17), pages 1-25, September.
    3. Emad M. Ahmed & Rajarajeswari Rathinam & Suchitra Dayalan & George S. Fernandez & Ziad M. Ali & Shady H. E. Abdel Aleem & Ahmed I. Omar, 2021. "A Comprehensive Analysis of Demand Response Pricing Strategies in a Smart Grid Environment Using Particle Swarm Optimization and the Strawberry Optimization Algorithm," Mathematics, MDPI, vol. 9(18), pages 1-24, September.
    4. Cong Chen & Yibai Li & Guangqiao Cao & Jinlong Zhang, 2023. "Research on Dynamic Scheduling Model of Plant Protection UAV Based on Levy Simulated Annealing Algorithm," Sustainability, MDPI, vol. 15(3), pages 1-20, January.

    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:jeners:v:15:y:2022:i:18:p:6735-:d:915168. 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.