• DocumentCode
    45181
  • Title

    PEV Charging Control Considering Transformer Life and Experimental Validation of a 25 kVA Distribution Transformer

  • Author

    Qiuming Gong ; Midlam-Mohler, Shawn ; Serra, Emmanuele ; Marano, Vincenzo ; Rizzoni, Giorgio

  • Author_Institution
    Ford Motor Co., Dearborn, MI, USA
  • Volume
    6
  • Issue
    2
  • fYear
    2015
  • fDate
    Mar-15
  • Firstpage
    648
  • Lastpage
    656
  • Abstract
    When considering the characteristics of electric power systems in the U.S., the local distribution is the most likely part to be adversely affected by the unregulated plug-in electric vehicle (PEV) charging. The increased load that can result from unregulated charging of PEVs could dramatically accelerate the aging of electrical transformers. In this paper, the control strategies that can mitigate or eliminate the accelerated aging that could result from load peaks caused by PEV charging is developed. The aging model makes it possible to develop charging control strategies that protect the transformer system while maximizing overall PEV charging quality. The charging control policy makes use of load prediction algorithms using data-driven models that are based on actual electricity consumption data. The experimental tests are done to calibrate the thermal model of a 25 kVA distribution transformer and validate the effectiveness of the control strategy.
  • Keywords
    ageing; electric vehicles; load forecasting; power consumption; power transformers; secondary cells; PEV; accelerated aging elimination; apparent power 25 kVA; charging control; data driven model; distribution transformer; electrical transformers; electricity consumption data; load prediction; plug-in electric vehicle; thermal model; transformer life; Aging; Load modeling; Oil insulation; Predictive models; System-on-chip; Temperature measurement; Windings; Distribution transformer; grid interaction; plug-in electric vehicles (PEVs); smart charging;
  • fLanguage
    English
  • Journal_Title
    Smart Grid, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3053
  • Type

    jour

  • DOI
    10.1109/TSG.2014.2365452
  • Filename
    6960069