A review of data sources for electric vehicle integration studies

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    The sales of electric vehicles (EVs) are rapidly increasing and their integration in the power system is becoming
    a crucial issue. However, there is a scarcity of necessary data to derive charging profiles and analyze their
    impact on the power system. The purpose of this manuscript is to provide a comprehensive review of published
    data sources that can be useful for EV studies in the context of smart grids and power systems. The manuscript
    focuses on the last two decades of published data, as this is more complete and reliable in terms of user and
    vehicle behavior. Data sources are categorized into three classes: surveys, internal combustion engine vehicles
    and EVs trials, and charger trials. Data from the different sources are summarized, including information
    regarding how and what kind of data has been collected and their availability. Based on the reviewed sources,
    five parameters are identified as essential to derive charging profiles: battery capacity, charging power, plug-in
    state of charge, plug-in/out time and charged energy. In order to observe individual behavior it is important to
    consider sets of charging sessions per charger, otherwise important correlations may be neglected. Depending
    on the source and data availability, in many cases this is not possible. To this end, this manuscript discusses
    how to use data from various sources to complement missing information and concludes with guidelines and
    limitations about data usage in EV studies.
    Original languageEnglish
    Article number111518
    JournalRenewable and Sustainable Energy Reviews
    Volume151
    Number of pages18
    ISSN1364-0321
    DOIs
    Publication statusPublished - 2021

    Keywords

    • Charging profiles
    • EV data sources
    • EV integration

    Fingerprint

    Dive into the research topics of 'A review of data sources for electric vehicle integration studies'. Together they form a unique fingerprint.

    Cite this