IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i4p1585-d754703.html
   My bibliography  Save this article

Reliability Assessment under High Penetration of EVs including V2G Strategy

Author

Listed:
  • Mohamed Mokhtar

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Mostafa F. Shaaban

    (Department of Electrical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • Mahmoud H. Ismail

    (Department of Electrical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates
    Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Cairo University, Giza 12613, Egypt)

  • Hatem F. Sindi

    (Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Muhyaddin Rawa

    (Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia
    Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

With the increase in the penetration of battery electric vehicles (BEVs) all over the world, utilities should start considering their increased demand as part of their electric demand. Generally, the literature lacks works that consider the impact of transportation electrification on the reliability of the power system. Thus, this paper proposes a new mechanism for reliability assessment including BEVs, with both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) modes. Three charging strategies: uncontrolled, controlled unidirectional, and controlled bidirectional are considered in this paper to model the interactions between the transportation and electric power systems. A dynamic stochastic consumption model for a fleet of BEVs is developed to be used in the reliability assessment for the distribution networks. This dynamic model takes into consideration the variability and uncertainty of different trip purposes, starting and ending trip times, as well as the corresponding battery consumption in weather conditions. Furthermore, it is composed of two sequential submodels: travel behavior and battery depletion. The first submodel considers trip-related information while the second considers battery-depleted energy. Simulation results on a benchmark test system show the negative impacts of uncontrolled charging on the power system’s reliability. However, they also show that controlled charging can significantly reduce or mitigate these impacts.

Suggested Citation

  • Mohamed Mokhtar & Mostafa F. Shaaban & Mahmoud H. Ismail & Hatem F. Sindi & Muhyaddin Rawa, 2022. "Reliability Assessment under High Penetration of EVs including V2G Strategy," Energies, MDPI, vol. 15(4), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1585-:d:754703
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/4/1585/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/4/1585/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guan, Ting & Sun, Shun & Gao, Yunzhi & Du, Chunyu & Zuo, Pengjian & Cui, Yingzhi & Zhang, Lingling & Yin, Geping, 2016. "The effect of elevated temperature on the accelerated aging of LiCoO2/mesocarbon microbeads batteries," Applied Energy, Elsevier, vol. 177(C), pages 1-10.
    2. Sina Shojaei & Andrew McGordon & Simon Robinson & James Marco, 2017. "Improving the Performance Attributes of Plug-in Hybrid Electric Vehicles in Hot Climates through Key-Off Battery Cooling," Energies, MDPI, vol. 10(12), pages 1-28, 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. Gustavo L. Aschidamini & Gederson A. da Cruz & Mariana Resener & Maicon J. S. Ramos & Luís A. Pereira & Bibiana P. Ferraz & Sérgio Haffner & Panos M. Pardalos, 2022. "Expansion Planning of Power Distribution Systems Considering Reliability: A Comprehensive Review," Energies, MDPI, vol. 15(6), pages 1-29, March.
    2. Weiqi Pan & Bokang Zou & Fengtao Li & Yifu Luo & Qirui Chen & Yuanshi Zhang & Yang Li, 2024. "Collaborative Operation Optimization Scheduling Strategy of Electric Vehicle and Steel Plant Considering V2G," Energies, MDPI, vol. 17(11), pages 1-14, May.
    3. Abdulaziz Almutairi, 2022. "Impact Assessment of Diverse EV Charging Infrastructures on Overall Service Reliability," Sustainability, MDPI, vol. 14(20), pages 1-16, October.

    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. Xiong, Rui & Pan, Yue & Shen, Weixiang & Li, Hailong & Sun, Fengchun, 2020. "Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    2. Chen, Jianguo & Han, Xuebing & Sun, Tao & Zheng, Yuejiu, 2024. "Analysis and prediction of battery aging modes based on transfer learning," Applied Energy, Elsevier, vol. 356(C).
    3. Sina Shojaei & Andrew McGordon & Simon Robinson & James Marco, 2017. "Improving the Performance Attributes of Plug-in Hybrid Electric Vehicles in Hot Climates through Key-Off Battery Cooling," Energies, MDPI, vol. 10(12), pages 1-28, December.
    4. Li, Hao & Zhang, Weige & Sun, Bingxiang & Cai, Xue & Fan, Xinyuan & Zhao, Bo & Zhang, Caiping, 2023. "The degradation characteristics and mechanism of Li[Ni0.5Co0.2Mn0.3]O2 batteries with high frequency current ripple excitation," Applied Energy, Elsevier, vol. 343(C).
    5. James Jeffs & Truong Quang Dinh & Widanalage Dhammika Widanage & Andrew McGordon & Alessandro Picarelli, 2020. "Optimisation of Direct Battery Thermal Management for EVs Operating in Low-Temperature Climates," Energies, MDPI, vol. 13(22), pages 1-35, November.

    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:4:p:1585-:d:754703. 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.