• DocumentCode
    2915073
  • Title

    Optimal Power Flow Based on Modified Genetic Algorithm

  • Author

    Moasheri, Seyed Reza ; Khazraei, Masoud

  • Author_Institution
    Islamic Azad Univ., Gonabad, Iran
  • fYear
    2011
  • fDate
    25-28 March 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Cost minimization is one of the main goals in electric market so economic dispatch and load allocating, named as optimal power flow (OPF), are more interesting concerns. In this paper a Modified Genetic Algorithm (MGA) is presented for the solution of the OPF. The control variables are unit active power outputs, generator-bus voltages and discrete transformer-tap settings. To overcome the operating constraints such as line flow limits, generator capabilities, and bus voltage amplitude limits, are all included in MGA fitness function. The simulation results have shown the MGA is more efficient and more convergence in compare with other attempts.
  • Keywords
    genetic algorithms; load flow; power systems; power transformers; MGA fitness function; control variables; cost minimization; discrete transformer-tap settings; electric market; generator-bus voltages; modified genetic algorithm; optimal power flow; power system; Fuels; Gallium; Generators; Genetic algorithms; Load flow; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
  • Conference_Location
    Wuhan
  • ISSN
    2157-4839
  • Print_ISBN
    978-1-4244-6253-7
  • Type

    conf

  • DOI
    10.1109/APPEEC.2011.5747746
  • Filename
    5747746