Smart Charging: A Comprehensive Review

Deb Sanchari*, Mikko Pihlatie, Mohammed Al-Saadi

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    44 Citations (Scopus)

    Abstract

    Large scale adoption and public acceptance of Electric Vehicles (EVs) require availability of charging stations. Electrification of transport has been identified as the one of the significant factors that would increase the power demand. Management of charger load has become a matter of concern for the power system engineers. Uncoordinated charging can be detrimental to the smooth operation of the power grid. On the contrary, smart charging gives certain amount of control over the charging process with respect to the power grid. Hence, adaptivity of the charging process of EVs in smart charging assists to meet the needs of power system as well as EV users. A smart charger can adjust the charging power according to the power available from the grid, EV user needs, and also support the grid during emergency. Smart charging enables EVs to act as flexible grid resources thereby providing ancillary services to the grid in case of emergency. Further, EV users can gain significant financial benefits through smart timing of their charging against spot market prices. This work presents a comprehensive overview of smart charging thereby explaining its perception, impact, user acceptance, global status and pilot projects. Also, case studies highlighting the benefits of smart charging are presented. This detailed elucidation of smart charging will assist the researchers, and experts of power industry as well as transport to find research initiatives on smart charging at one platform thereby promoting adoption of smart charging.

    Original languageEnglish
    Pages (from-to)134690-134703
    JournalIEEE Access
    Volume10
    DOIs
    Publication statusPublished - 2022
    MoE publication typeA1 Journal article-refereed

    Funding

    This work was supported in part by the European Research Consortium of Informatics and Mathematics (ERCIM), and in part by the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie Grant 945380. The work of Mikko Pihlatie and Mohammed Al-Saadi was supported by the European Union’s Horizon 2020 Research and Innovation Programme through project ASSURED under Grant 769850.

    Keywords

    • Charging
    • Electric Vehicle
    • Electric vehicles
    • Hidden Markov models
    • Optimization
    • Power systems
    • Prediction
    • Reliability
    • Review
    • Smart charging
    • Transformers

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