IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i6p2487-d1358639.html
   My bibliography  Save this article

Smart and Sustainable Wireless Electric Vehicle Charging Strategy with Renewable Energy and Internet of Things Integration

Author

Listed:
  • Sheeraz Iqbal

    (Department of Electrical Engineering, University of Azad Jammu and Kashmir, Muzaffarabad 13100, AJK, Pakistan)

  • Nahar F. Alshammari

    (Department of Electrical Engineering, Faculty of Engineering, Jouf University, Sakaka 72388, Saudi Arabia)

  • Mokhtar Shouran

    (Libyan Center for Engineering Research and Information Technology, Bani Walid, Libya
    Department of Control Engineering, College of Electronics Technology, Bani Walid P.O. Box 38645, Libya)

  • Jabir Massoud

    (School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

Abstract

This study addresses the challenges associated with electric vehicle (EV) charging in office environments. These challenges include (1) reliance on manual cable connections, (2) constrained charging options, (3) safety concerns with cable management, and (4) the lack of dynamic charging capabilities. This research focuses on an innovative wireless power transfer (WPT) system specifically designed for use in office parking areas. This system incorporates renewable energy resources (RERs) and uses the transformative power of the Internet of Things (IoT). It employs a mix of solar energy systems and battery storage solutions to facilitate a sustainable and efficient energy supply to EVs. The integration of IoT technology allows for the automatic initiation of charging as soon as an EV is parked. Additionally, the implementation of the Blynk application offers users real-time access to information regarding the operational status of the photovoltaic system and the battery levels of their EVs. The system is further enhanced with IoT and RFID technologies to provide dynamic updates on the availability of charging slots and to implement strict security protocols for user authentication and protection. The research also includes a case study focusing on the application of this charging system in office settings. The case study achieves a 95.9% IRR, lower NPC of USD 1.52 million, and 56.7% power contribution by RERs, and it reduces annual carbon emissions to 173,956 kg CO 2 .

Suggested Citation

  • Sheeraz Iqbal & Nahar F. Alshammari & Mokhtar Shouran & Jabir Massoud, 2024. "Smart and Sustainable Wireless Electric Vehicle Charging Strategy with Renewable Energy and Internet of Things Integration," Sustainability, MDPI, vol. 16(6), pages 1-25, March.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:6:p:2487-:d:1358639
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/6/2487/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/6/2487/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhao, Zhonghao & Lee, Carman K.M. & Huo, Jiage, 2023. "EV charging station deployment on coupled transportation and power distribution networks via reinforcement learning," Energy, Elsevier, vol. 267(C).
    2. Ullah, Zia & Wang, Shaorong & Wu, Guan & Hasanien, Hany M. & Rehman, Anis Ur & Turky, Rania A. & Elkadeem, Mohamed R., 2023. "Optimal scheduling and techno-economic analysis of electric vehicles by implementing solar-based grid-tied charging station," Energy, Elsevier, vol. 267(C).
    3. Rehman, Anis Ur & Ullah, Zia & Shafiq, Aqib & Hasanien, Hany M. & Luo, Peng & Badshah, Fazal, 2023. "Load management, energy economics, and environmental protection nexus considering PV-based EV charging stations," Energy, Elsevier, vol. 281(C).
    4. Ullah, Zia & Rehman, Anis Ur & Wang, Shaorong & Hasanien, Hany M. & Luo, Peng & Elkadeem, Mohamed R. & Abido, Mohammad A., 2023. "IoT-based monitoring and control of substations and smart grids with renewables and electric vehicles integration," Energy, Elsevier, vol. 282(C).
    5. Zhang, Xizheng & Wang, Zeyu & Lu, Zhangyu, 2022. "Multi-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 306(PA).
    Full references (including those not matched with items on IDEAS)

    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. Ullah, Zia & Rehman, Anis Ur & Wang, Shaorong & Hasanien, Hany M. & Luo, Peng & Elkadeem, Mohamed R. & Abido, Mohammad A., 2023. "IoT-based monitoring and control of substations and smart grids with renewables and electric vehicles integration," Energy, Elsevier, vol. 282(C).
    2. Dong, Xiao-Jian & Shen, Jia-Ni & Liu, Cheng-Wu & Ma, Zi-Feng & He, Yi-Jun, 2024. "Simultaneous capacity configuration and scheduling optimization of an integrated electrical vehicle charging station with photovoltaic and battery energy storage system," Energy, Elsevier, vol. 289(C).
    3. Mohd Bilal & Pitshou N. Bokoro & Gulshan Sharma & Giovanni Pau, 2024. "A Cost-Effective Energy Management Approach for On-Grid Charging of Plug-in Electric Vehicles Integrated with Hybrid Renewable Energy Sources," Energies, MDPI, vol. 17(16), pages 1-35, August.
    4. Paulo M. De Oliveira-De Jesus & Jose M. Yusta, 2024. "Optimal Power Dispatch for Maximum Energy Community Welfare by Considering Closed Distribution Systems and Renewable Sources," Energies, MDPI, vol. 17(18), pages 1-21, September.
    5. Hosseini Dehshiri, Seyyed Jalaladdin & Amiri, Maghsoud, 2023. "Evaluating the risks of the internet of things in renewable energy systems using a hybrid fuzzy decision approach," Energy, Elsevier, vol. 285(C).
    6. Tan, Bifei & Lin, Zhenjia & Zheng, Xiaodong & Xiao, Fu & Wu, Qiuwei & Yan, Jinyue, 2023. "Distributionally robust energy management for multi-microgrids with grid-interactive EVs considering the multi-period coupling effect of user behaviors," Applied Energy, Elsevier, vol. 350(C).
    7. Li, Da & Zhang, Zhaosheng & Zhou, Litao & Liu, Peng & Wang, Zhenpo & Deng, Junjun, 2022. "Multi-time-step and multi-parameter prediction for real-world proton exchange membrane fuel cell vehicles (PEMFCVs) toward fault prognosis and energy consumption prediction," Applied Energy, Elsevier, vol. 325(C).
    8. Zhang, Y.Q. & Chen, J.J. & Wang, Y.X. & Feng, L., 2024. "Enhancing resilience of agricultural microgrid through electricity–heat–water based multi-energy hub considering irradiation intensity uncertainty," Renewable Energy, Elsevier, vol. 220(C).
    9. Muhamad Subhi Apriantoro & Rizki Dwi Putra Rosadi & Arminda Cahya Ramdhani & Ninik Andriyani, 2024. "Shaping the Future of Environmental Economics: A Bibliometric Review of Current Trends and Future Directions," International Journal of Energy Economics and Policy, Econjournals, vol. 14(3), pages 549-559, May.
    10. Lim, Yee Kai & Tan, Inn Shi & Foo, Henry Chee Yew & Tan, Yie Hua & Lam, Man Kee & Wong, Mee Kee, 2024. "Exergetic and exergoeconomic analyses of Eucheuma cottoni residue biorefinery for co-production of polylactic acid and electricity," Energy, Elsevier, vol. 300(C).
    11. Jiankai Gao & Yang Li & Bin Wang & Haibo Wu, 2023. "Multi-Microgrid Collaborative Optimization Scheduling Using an Improved Multi-Agent Soft Actor-Critic Algorithm," Energies, MDPI, vol. 16(7), pages 1-21, April.
    12. Adetunji, Kayode E. & Hofsajer, Ivan W. & Abu-Mahfouz, Adnan M. & Cheng, Ling, 2022. "An optimization planning framework for allocating multiple distributed energy resources and electric vehicle charging stations in distribution networks," Applied Energy, Elsevier, vol. 322(C).
    13. Rehman, Anis Ur & Ullah, Zia & Shafiq, Aqib & Hasanien, Hany M. & Luo, Peng & Badshah, Fazal, 2023. "Load management, energy economics, and environmental protection nexus considering PV-based EV charging stations," Energy, Elsevier, vol. 281(C).
    14. Aghajan-Eshkevari, Saleh & Ameli, Mohammad Taghi & Azad, Sasan, 2023. "Optimal routing and power management of electric vehicles in coupled power distribution and transportation systems," Applied Energy, Elsevier, vol. 341(C).
    15. Paudel, Diwas & Das, Tapas K., 2023. "A deep reinforcement learning approach for power management of battery-assisted fast-charging EV hubs participating in day-ahead and real-time electricity markets," Energy, Elsevier, vol. 283(C).
    16. Zeng, Bo & Luo, Yangfan, 2022. "Potential of harnessing operational flexibility from public transport hubs to improve reliability and economic performance of urban multi-energy systems: A holistic assessment framework," Applied Energy, Elsevier, vol. 322(C).
    17. Yu, Shiwei & Zhou, Shuangshuang & Chen, Nan, 2024. "Multi-objective optimization of capacity and technology selection for provincial energy storage in China: The effects of peak-shifting and valley-filling," Applied Energy, Elsevier, vol. 355(C).
    18. Luo, Zhiqiang & Liu, Hui & Wang, Ni & Zhao, Teyang & Tian, Jiarui, 2024. "Optimal adaptive decentralized under-frequency load shedding for islanded smart distribution network considering wind power uncertainty," Applied Energy, Elsevier, vol. 365(C).
    19. Zhang, Chao & Yin, Wanjun & Wen, Tao, 2024. "An advanced multi-objective collaborative scheduling strategy for large scale EV charging and discharging connected to the predictable wind power grid," Energy, Elsevier, vol. 287(C).
    20. Li, Da & Zhang, Lei & Zhang, Zhaosheng & Liu, Peng & Deng, Junjun & Wang, Qiushi & Wang, Zhenpo, 2023. "Battery safety issue detection in real-world electric vehicles by integrated modeling and voltage abnormality," Energy, Elsevier, vol. 284(C).

    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:jsusta:v:16:y:2024:i:6:p:2487-:d:1358639. 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.