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A Review on the Allocation of Sustainable Distributed Generators with Electric Vehicle Charging Stations

Author

Listed:
  • Abdullah Aljumah

    (Department of Electrical Engineering, College of Engineering, Majmaah University, Al-Majmaah 11952, Saudi Arabia
    School of Engineering, Lancaster University, Lancaster LA1 4YR, UK)

  • Ahmed Darwish

    (School of Engineering, Lancaster University, Lancaster LA1 4YR, UK
    Faculty of Engineering & Digital Technologies, University of Bradford, Bradford BD7 1AZ, UK)

  • Denes Csala

    (School of Engineering, Lancaster University, Lancaster LA1 4YR, UK)

  • Peter Twigg

    (Faculty of Engineering & Digital Technologies, University of Bradford, Bradford BD7 1AZ, UK)

Abstract

Environmental concerns and the Paris agreements have prompted intensive efforts towards greener and more sustainable transportation. Persistent expansion of electric vehicles (EV) in the transportation sector requires electric vehicle charging stations (EVCSs) to accommodate the increased demand. Offsetting demand and alleviating the resultant electrical grid stress necessitates establishing grid-integrated renewable energy sources (RESs) where these sustainable strategies are accompanied by variable-weather-related obstacles, such as voltage fluctuations, grid instability, and increased energy losses. Strategic positioning of EVCSs and RES as distributed generation (DG) units is crucial for addressing technical issues. While technical constraints have received considerable attention, there is still a gap in the literature with respect to incorporating the additional complex optimization problems and decision-making processes associated with economic viability, social acceptance, and environmental impact. A possible solution is the incorporation of an appropriate multi-criteria decision analysis (MCDA) approach for feasible trade-off solutions. Such methods offer promising possibilities that can ease decision-making and facilitate sustainable solutions. In this context, this paper presents a review of published approaches for optimizing the allocation of renewable energy DG units and EVCSs in active distribution networks (ADNs). Promising published optimization approaches for the strategic allocation of multiple DG units and EVCSs in ADNs have been analyzed and compared.

Suggested Citation

  • Abdullah Aljumah & Ahmed Darwish & Denes Csala & Peter Twigg, 2024. "A Review on the Allocation of Sustainable Distributed Generators with Electric Vehicle Charging Stations," Sustainability, MDPI, vol. 16(15), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6353-:d:1442286
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    References listed on IDEAS

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    1. Park, Sung-Won & Cho, Kyu-Sang & Hoefter, Gregor & Son, Sung-Yong, 2022. "Electric vehicle charging management using location-based incentives for reducing renewable energy curtailment considering the distribution system," Applied Energy, Elsevier, vol. 305(C).
    2. Min, Dehao & Song, Zhen & Chen, Huicui & Wang, Tianxiang & Zhang, Tong, 2022. "Genetic algorithm optimized neural network based fuel cell hybrid electric vehicle energy management strategy under start-stop condition," Applied Energy, Elsevier, vol. 306(PB).
    3. 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).
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    Cited by:

    1. Ahmed Darwish & George A. Aggidis, 2025. "A Modular Step-Up DC–DC Converter Based on Dual-Isolated SEPIC/Cuk for Electric Vehicle Applications," Energies, MDPI, vol. 18(1), pages 1-24, January.
    2. Ahmed Darwish, 2024. "A Modular Step-Up DC/DC Converter for Electric Vehicles," Energies, MDPI, vol. 17(24), pages 1-22, December.

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