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Investigating the Impact of Electric Vehicles Demand on the Distribution Network

Author

Listed:
  • Thamer Alquthami

    (Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Abdullah Alsubaie

    (King Abdulaziz City for Science and Technology, Riyadh 11442, Saudi Arabia)

  • Mohannad Alkhraijah

    (King Abdulaziz City for Science and Technology, Riyadh 11442, Saudi Arabia)

  • Khalid Alqahtani

    (King Abdulaziz City for Science and Technology, Riyadh 11442, Saudi Arabia)

  • Saad Alshahrani

    (King Abdulaziz City for Science and Technology, Riyadh 11442, Saudi Arabia)

  • Murad Anwar

    (Saudi Electricity Company, Riyadh 11416, Saudi Arabia)

Abstract

Deployment of Electric Vehicles (EV) is increasing in recent years due to economic and environmental advantages compared with fossil fuel-based vehicles. As the market of EVs grows, new challenges to the electric grid are emerging to accommodate the EVs demand, especially in the distribution networks. In this paper, we investigate the impact of EVs deployment on the electricity demand and distributed network. We propose a model to generate EV demand profiles that consider the EV users’ driving pattern such as daily energy consumption and charging schedule, in addition to the EV’s charging characteristics. The EV demand model uses data we obtained from a survey to evaluate the model’s parameters. We use the EV demand model to simulate and evaluate the impact of EVs demand on the distribution network. We present a case study with an actual model for a distribution network to evaluate the impact of EVs on the distribution network in Saudi Arabia. We analyze the simulation results and show how EVs impact the demand and the distribution network performance.

Suggested Citation

  • Thamer Alquthami & Abdullah Alsubaie & Mohannad Alkhraijah & Khalid Alqahtani & Saad Alshahrani & Murad Anwar, 2022. "Investigating the Impact of Electric Vehicles Demand on the Distribution Network," Energies, MDPI, vol. 15(3), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:1180-:d:743041
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    References listed on IDEAS

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    1. Neaimeh, Myriam & Wardle, Robin & Jenkins, Andrew M. & Yi, Jialiang & Hill, Graeme & Lyons, Padraig F. & Hübner, Yvonne & Blythe, Phil T. & Taylor, Phil C., 2015. "A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts," Applied Energy, Elsevier, vol. 157(C), pages 688-698.
    2. Fathabadi, Hassan, 2017. "Novel grid-connected solar/wind powered electric vehicle charging station with vehicle-to-grid technology," Energy, Elsevier, vol. 132(C), pages 1-11.
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    Cited by:

    1. Pampa Sinha & Kaushik Paul & Sanchari Deb & Sulabh Sachan, 2023. "Comprehensive Review Based on the Impact of Integrating Electric Vehicle and Renewable Energy Sources to the Grid," Energies, MDPI, vol. 16(6), pages 1-39, March.
    2. Seppo Borenius & Petri Tuomainen & Jyri Tompuri & Jesse Mansikkamäki & Matti Lehtonen & Heikki Hämmäinen & Raimo Kantola, 2022. "Scenarios on the Impact of Electric Vehicles on Distribution Grids," Energies, MDPI, vol. 15(13), pages 1-30, June.
    3. Vongdala Noudeng & Nguyen Van Quan & Tran Dang Xuan, 2022. "A Future Perspective on Waste Management of Lithium-Ion Batteries for Electric Vehicles in Lao PDR: Current Status and Challenges," IJERPH, MDPI, vol. 19(23), pages 1-22, December.
    4. Mohammed Goda Eisa & Mohammed A. Farahat & Wael Abdelfattah & Mohammed Elsayed Lotfy, 2024. "Multi-Objective Optimal Integration of Distributed Generators into Distribution Networks Incorporated with Plug-In Electric Vehicles Using Walrus Optimization Algorithm," Sustainability, MDPI, vol. 16(22), pages 1-37, November.
    5. Apostolos Vavouris & Benjamin Garside & Lina Stankovic & Vladimir Stankovic, 2022. "Low-Frequency Non-Intrusive Load Monitoring of Electric Vehicles in Houses with Solar Generation: Generalisability and Transferability," Energies, MDPI, vol. 15(6), pages 1-27, March.

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