• DocumentCode
    3587183
  • Title

    Management and coordination charging of smart park and V2G strategy based on Monte Carlo algorithm

  • Author

    Aryanezhad, Majid ; Ostadaghaee, Elahe ; Joorabian, Mahmood

  • Author_Institution
    Electr. Eng. Dept., Shahid Chamran Univ., Ahvaz, Iran
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Charging of plug-in-hybrid-electric vehicles (PHEVs) may adversely affect electric grid reliability because a large amount of additional electrical energy is required to charge the PHEVs. In this paper, a comprehensive method to evaluate the system reliability concerning the stochastic modeling of PHEVs, renewable resources, availability of devices, etc. is proposed. This method, which consists of managed charging and vehicle-to-grid (V2G) scenarios, can be practically implemented in smart grids because the bidirectional-power-conversion technologies and two-way of both the power and data are applicable. The results showed that the smart grid´s adequacy was jeopardized by using the PHEVs without any managed charging schedule. The sensitivity analyses results illustrated that by using the management scenarios, not only did the PHEVs not compromise the system reliability, but also in the V2G scenario acted as storage systems and improved the well-being criteria and adequacy indices.
  • Keywords
    Monte Carlo methods; hybrid electric vehicles; power system management; reliability; sensitivity analysis; smart power grids; stochastic processes; Monte Carlo algorithm; PHEV; V2G strategy; bidirectional power conversion technologies; plug-in hybrid electric vehicles; sensitivity analyses; smart electric grid reliability; smart park coordination charging; smart park management; stochastic modeling; vehicle-to-grid scenarios; Batteries; Load modeling; Power generation; Reliability; Schedules; Smart grids; System-on-chip; Management Charging; Monte Carlo Algorithm; PHEV; Reliability; V2G;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Smart Grid Conference (SGC), 2014
  • Print_ISBN
    978-1-4799-8313-1
  • Type

    conf

  • DOI
    10.1109/SGC.2014.7090887
  • Filename
    7090887