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EVs’ Integration Impact on the Reliability of Saudi Arabia’s Power System

Author

Listed:
  • Wael Softah

    (Electrical Engineering Department, Umm Al-Qura University, Makkah, Saudi Arabia)

  • Hani A. Aldhubaib

    (Electrical Engineering Department, Umm Al-Qura University, Makkah, Saudi Arabia)

Abstract

This paper investigates the effect of involving electric vehicles (EVs) in the load profile on the generation system. The impact was studied from a reliability perspective on Saudi Arabia’s total generation system capacity as one source supplying the expected load for the year 2030. The EV load profile was then added. The outcomes were examined considering the gradual penetration percentage to the total load. The reliability indices measured are the loss of load probability (LOLP) and the expected energy not supplied (EENS). The results show that the estimated generation system of Saudi Vision 2030 will not withstand the estimated number of EVs without negatively impacting reliability. Similarly, the reliability assessment was conducted for the central region considering EVs in Riyadh City to verify Saudi Vision 2030. The results show that EV integration will greatly affect the electrical network’s reliability. Furthermore, a sensitivity analysis was conducted for Saudi Arabia and the central region to assess the generation system better. The study shows that investing in the generation infrastructure is essential to handle EV growth for the upcoming years. The work introduced in this paper will also help decision-makers make appropriate planning decisions in the future.

Suggested Citation

  • Wael Softah & Hani A. Aldhubaib, 2023. "EVs’ Integration Impact on the Reliability of Saudi Arabia’s Power System," Energies, MDPI, vol. 16(12), pages 1-24, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:12:p:4579-:d:1166197
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    References listed on IDEAS

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    1. Matthias D. Galus & Marina González Vayá & Thilo Krause & Göran Andersson, 2013. "The role of electric vehicles in smart grids," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 2(4), pages 384-400, July.
    2. 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.
    3. Pol Olivella-Rosell & Roberto Villafafila-Robles & Andreas Sumper & Joan Bergas-Jané, 2015. "Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks," Energies, MDPI, vol. 8(5), pages 1-28, May.
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