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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
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    References listed on IDEAS

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    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).
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    Cited by:

    1. Alexander Mutiso Mutua & Ruairí de Fréin, 2024. "Sustainable Mobility: Machine Learning-Driven Deployment of EV Charging Points in Dublin," Sustainability, MDPI, vol. 16(22), pages 1-37, November.
    2. Peng Gu & Shibo Wang & Bowen Zhou, 2024. "Analysis and Design of a Recyclable Inductive Power Transfer System for Sustainable Multi-Stage Rocket Microgrid with Multi-Constant Voltage Output Characteristics—Theoretical Considerations," Sustainability, MDPI, vol. 16(22), pages 1-15, November.

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