• DocumentCode
    176805
  • Title

    Reactive power optimization by genetic algorithm integrated with reduced gradient method

  • Author

    Zhao Dongmei ; Wang Pei ; Zhang Xu

  • Author_Institution
    Dept. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
  • fYear
    2014
  • fDate
    29-30 Sept. 2014
  • Firstpage
    838
  • Lastpage
    841
  • Abstract
    The optimal control of voltage and reactive power is one of the essential issues for power grids´ security and the economical operation. Having elaborated the model of reactive power optimization in regional power grids, this paper advances an improved genetic algorithm integrated with reduced gradient technique for solving of ORP problem in regional power networks. It is implemented repeatedly on IEEE 30-bus system and an actual regional power grid. Compared with several other algorithms, the testing results demonstrate its effectiveness. It is showed that the proposed hybrid algorithm can gain better voltage profile and less active power loss simultaneously within permissible limits.
  • Keywords
    IEEE standards; genetic algorithms; gradient methods; power grids; power system security; reactive power control; IEEE 30-bus system; ORP problem; active power loss; genetic algorithm; hybrid algorithm; improved genetic algorithm; optimal control; power grid security; reactive power; reactive power optimization; reduced gradient method; reduced gradient technique; regional power grid; regional power grids; regional power networks; voltage power; voltage profile; Genetic algorithms; Gradient methods; Hybrid power systems; Power grids; Power system stability; Reactive power; Genetic algorithm; reactive power optimization; reduced gradient method; regional power grids;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Research and Technology in Industry Applications (WARTIA), 2014 IEEE Workshop on
  • Conference_Location
    Ottawa, ON
  • Type

    conf

  • DOI
    10.1109/WARTIA.2014.6976403
  • Filename
    6976403