• DocumentCode
    188558
  • Title

    Hybrid multi-agent based resilient control for EV connected micro grid system

  • Author

    Hintz, Andrew S. ; Prasanna, Udupi R. ; Rajashekara, Kaushik

  • Author_Institution
    Univ. of Texas at Dallas, Dallas, TX, USA
  • fYear
    2014
  • fDate
    15-18 June 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A hybrid control strategy for the energy management of the microgrid system consisting of a number of electric vehicles and other energy sources is proposed in this paper. The main focus of this paper is on optimal control of power flow by scheduling and demand side management of energy generation system and the load by utilizing electric vehicles´ energy storage system. The features of a centralized control and distributed control are combined into the proposed hybrid control strategy to improve the efficiency and reliability of the microgrid system consisting of electric vehicle charging stations. Cost of power generation and value of load equations are presented to compute a “situational aware” power balance. Simulated results utilizing these equations are presented for a residential scale proof-of-concept system.
  • Keywords
    battery storage plants; centralised control; demand side management; distributed control; distributed power generation; electric vehicles; intelligent control; load flow control; multi-agent systems; optimal control; power distribution control; power engineering computing; power generation control; power generation economics; power generation scheduling; robust control; centralized control; demand side management; distributed control; electric vehicle charging station; electric vehicle energy storage system; energy generation system; energy management; hybrid control strategy; hybrid resilient control; load equations; load scheduling; microgrid connected electric vehicle; multiagent based resilient control; optimal control; power flow; power generation cost; Batteries; Density estimation robust algorithm; Fuels; Generators; Load modeling; Mathematical model; Wind;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transportation Electrification Conference and Expo (ITEC), 2014 IEEE
  • Conference_Location
    Dearborn, MI
  • Type

    conf

  • DOI
    10.1109/ITEC.2014.6861832
  • Filename
    6861832