• DocumentCode
    2018947
  • Title

    Evaluating the grid impact of plug-in electric vehicles using dynamic commuting profiles

  • Author

    Chakraborty, Soumyo V. ; Shukla, Sandeep K. ; Thorp, James

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Virginia Tech, Blacksburg, VA, USA
  • fYear
    2013
  • fDate
    16-20 June 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    We analyze the actual commuting profiles of vehicles in the US and develop a statistical model to fit the observed data. Subsequently, this model is leveraged in a simulation framework to simulate the behavior of fleets of Plug-in Electric Vehicles (PEV), analyze their impact on the grid and, compute the effective load carrying capacity (ELCC) contributed by PEVs. We develop methodologies to quantify ELCC impact of various scenarios, including (1) restrictions on when PEVs can be charged or discharged, and (2) how the commuting times are distributed throughout the day. The model is run with 4-year actual load data from New York City (NYC) and PEV performance specifications of Chevy Volt to obtain ELCC contribution figures for PEV fleet sizes going up to 50% penetration. Our results show that up to 7% of peak capacity in NYC can be supplied by PEVs at a 25% penetration level.
  • Keywords
    electric vehicles; power grids; Chevy Volt; ELCC; PEV; Uinted States; dynamic commuting profiles; effective load carrying capacity; grid impact; penetration level; plug-in electric vehicles; statistical model; Batteries; Computational modeling; Data models; Gaussian distribution; Load modeling; Mathematical model; Vehicles; Commuting Profile; Effective Load Carrying Capacity (ELCC); Grid-to-Vehicle (G2V); Plug-in Electric Vehicle (PEV); Vehicle-to-Grid (V2G);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech (POWERTECH), 2013 IEEE Grenoble
  • Conference_Location
    Grenoble
  • Type

    conf

  • DOI
    10.1109/PTC.2013.6652212
  • Filename
    6652212