IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i13p3494-d1693272.html
   My bibliography  Save this article

Empirical EV Load Model for Distribution Network Analysis

Author

Listed:
  • Quang Bach Phan

    (Australian Power Quality Research Centre, University of Wollongong, Wollongong 2522, Australia
    These authors contributed equally to this work.)

  • Obaidur Rahman

    (Australian Power Quality Research Centre, University of Wollongong, Wollongong 2522, Australia
    These authors contributed equally to this work.)

  • Sean Elphick

    (Australian Power Quality Research Centre, University of Wollongong, Wollongong 2522, Australia
    These authors contributed equally to this work.)

Abstract

Electric vehicles (EVs) have introduced new operational challenges for distribution network service providers (DNSPs), particularly for voltage regulation due to unpredictable charging behaviour and the intermittent nature of distributed energy resources (DERs). This study focuses on formulating an empirical EV load model that characterises charging behaviour over a broad spectrum of supply voltage magnitudes to enable more accurate representation of EV demand under varying grid conditions. The empirical model is informed by laboratory evaluation of one Level 1 and two Level 2 chargers, along with five EV models. The testing revealed that all the chargers operated in a constant current (CC) mode across the applied voltage range, except for certain Level 2 chargers, which transitioned to constant power (CP) operation at voltages above 230 V. A model of a typical low voltage network has been developed using the OpenDSS software package (version 10.2.0.1) to evaluate the performance of the proposed empirical load model against traditional CP load modelling. In addition, a 24 h case study is presented to provide insights into the practical implications of increasing EV charging load. The results demonstrate that the CP model consistently overestimated network demand and voltage drops and failed to capture the voltage-dependent behaviour of EV charging in response to source voltage change. In contrast, the empirical model provided a more realistic reflection of network response, offering DNSPs improved accuracy for system planning.

Suggested Citation

  • Quang Bach Phan & Obaidur Rahman & Sean Elphick, 2025. "Empirical EV Load Model for Distribution Network Analysis," Energies, MDPI, vol. 18(13), pages 1-25, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3494-:d:1693272
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/13/3494/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/13/3494/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jason David & Philip Ciufo & Sean Elphick & Duane Robinson, 2022. "Preliminary Evaluation of the Impact of Sustained Overvoltage on Low Voltage Electronics-Based Equipment," Energies, MDPI, vol. 15(4), pages 1-16, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nihal Kularatna, 2023. "Power Conditioning and Power Protection for Electronic Systems," Energies, MDPI, vol. 16(6), pages 1-4, March.
    2. Jackson Hannagan & Rhys Woszczeiko & Thomas Langstaff & Weixiang Shen & John Rodwell, 2022. "The Impact of Household Appliances and Devices: Consider Their Reactive Power and Power Factors," Sustainability, MDPI, vol. 15(1), pages 1-11, December.
    3. Sean Elphick & Jonathan C. Knott & Gerrard Drury & Tom Langstaff & Duane A. Robinson, 2024. "Quantifying the Economic Impact of Supply Voltage Magnitude on Consumers," Energies, MDPI, vol. 17(22), pages 1-21, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3494-:d:1693272. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.