• DocumentCode
    3665589
  • Title

    Examining the potential impact of plug-in electric vehicles on residential sector power demand

  • Author

    Brandon J. Johnson;Michael R. Starke;Aleksandar D. Dimitrovski

  • Author_Institution
    Electric Power Research Institute, Knoxville, TN, USA
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents a dynamic simulation tool for examining the future impact of plug-in electric vehicles (PEVs) on residential sector power demand. First, the modeling approach used during the development of this tool is described. Markov chain based occupant behavior models developed using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS) are used in conjunction with models of the most common residential loads to estimate residential demand on a one-minute time scale. Next, a detailed explanation of the methodology used to model PEV use and charging is given. Simulation results showing the differences in residential power demand, both with and without PEVs present in the system, are shown. Finally, future work will involve using these simulation results to conduct various probabilistic load flow studies.
  • Keywords
    "Load modeling","Power demand","Markov processes","Batteries","Data models","Electric vehicles"
  • Publisher
    ieee
  • Conference_Titel
    Power & Energy Society General Meeting, 2015 IEEE
  • ISSN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PESGM.2015.7286044
  • Filename
    7286044