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Utilizing Local Flexibility Resources to Mitigate Grid Challenges at Electric Vehicle Charging Stations

Author

Listed:
  • Iliana Ilieva

    (Smart Innovation Norway, 1783 Halden, Norway)

  • Bernt Bremdal

    (Smart Innovation Norway, 1783 Halden, Norway
    Department of Computer Science and Computational Engineering, UiT The Arctic University of Norway, 9037 Tromsø, Norway)

Abstract

Charging of electric vehicles (EVs) on a large scale can cause problems for the grid. Utilizing local flexibility resources, such as smart charging, stationary battery, vehicle-to-grid applications, and local generation can be an efficient way to contain the grid challenges and mitigate the need for grid reinforcement. Focusing on the INSPIRIA charging station located in Norway, this paper investigates the possibility of coping with imminent grid challenges by means of local flexibility. First, the potential grid challenges are estimated with the help of Monte Carlo simulations. Second, cost and performance for the various local flexibility sources are presented. Third, an analysis of the choice of battery, charging process, and battery economy are provided. Finally, the paper discusses the optimal mix of flexibility resources to efficiently mitigate grid challenges at the INSPIRIA charging station.

Suggested Citation

  • Iliana Ilieva & Bernt Bremdal, 2021. "Utilizing Local Flexibility Resources to Mitigate Grid Challenges at Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(12), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3506-:d:574006
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    References listed on IDEAS

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    4. Wangsness, Paal Brevik & Halse, Askill Harkjerr, 2020. "The impact of electric vehicle density on local grid costs: Empirical evidence," Working Paper Series 1-2020, Norwegian University of Life Sciences, School of Economics and Business.
    5. Uddin, Kotub & Jackson, Tim & Widanage, Widanalage D. & Chouchelamane, Gael & Jennings, Paul A. & Marco, James, 2017. "On the possibility of extending the lifetime of lithium-ion batteries through optimal V2G facilitated by an integrated vehicle and smart-grid system," Energy, Elsevier, vol. 133(C), pages 710-722.
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    Cited by:

    1. Xiaogang Pan & Kangli Liu & Jianhua Wang & Yutao Hu & Jianfeng Zhao, 2023. "Capacity Allocation Method Based on Historical Data-Driven Search Algorithm for Integrated PV and Energy Storage Charging Station," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    2. Ana Carolina Kulik & Édwin Augusto Tonolo & Alberto Kisner Scortegagna & Jardel Eugênio da Silva & Jair Urbanetz Junior, 2021. "Analysis of Scenarios for the Insertion of Electric Vehicles in Conjunction with a Solar Carport in the City of Curitiba, Paraná—Brazil," Energies, MDPI, vol. 14(16), pages 1-15, August.

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