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  • 1.
    Sandström, Maria
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Building Engineering, Energy Systems and Sustainability Science, Energy Systems and Building Technology. Högskolan Dalarna.
    Huang, Pei
    Högskolan Dalarna.
    Bales, Chris
    Högskolan Dalarna.
    Dotzauer, Erik
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Building Engineering, Energy Systems and Sustainability Science, Energy Systems and Building Technology.
    Evaluation of hosting capacity of the power grid for electric vehicles – A case study in a Swedish residential area2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 284, article id 129293Article in journal (Refereed)
    Abstract [en]

    The deployment of electric vehicles (EVs) is growing significantly in recent years. The increasing EV charging loads pose great stress on power grids in Sweden, as many existing power grids are not designed to host such large shares of new electric loads. Hence, studies investigating the impact of EV charging are needed. This study conducts a case study based on an existing Swedish residential power grid using real-life EV charging data to estimate the local grid hosting capacity (HC) for EVs. A combined time-series and stochastic HC assessment method is used with voltage deviation, cable loading and transformer loading as the performance indices. Uncertainty in EV charging locations and individual charging behaviour have been considered via Monte Carlo simulations. The power grid HC is analysed and compared under three charging strategies and four EV penetration levels. Study results show that a charging strategy based on low electricity prices gave lower HC due to simultaneous EV loads compared to the other two strategies: charging directly after plugging in the EV and an even charging load through the plug-in session. This implies the need for coordinated charging controls of EV fleets or diversified power tariffs to balance power on a large scale.

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