• DocumentCode
    1615554
  • Title

    Dispatch distributed generation and load forecasting by GSO algorithm and natural network optimized by genetic

  • Author

    Li Xintong ; Teng Fei ; Li Yushuai ; He Zhiqiang ; Wang Yingnan

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2013
  • Firstpage
    824
  • Lastpage
    829
  • Abstract
    This paper mainly discuss a problem that how to optimize the ways on electric system dispatching. The GSO algorithm and natural network optimized by genetic are used to solve the problem. The distributed generations and the loads can be seen as producer, requester and random dispersion members which is in the nature. Due to the electric system is a dynamic system, the load forecasting must be done by the natural network. This algorithm is optimized by genetic algorithm to solve the problem that need lots of data. Through previous algorithm can solve the electric system dispatching problem.
  • Keywords
    distributed power generation; genetic algorithms; load forecasting; power generation dispatch; GSO algorithm; dispatch distributed generation; electric system dispatching; genetic algorithm; load forecasting; natural network; producer members; random dispersion members; requester members; Distributed power generation; Genetic algorithms; Genetics; Heuristic algorithms; Linear programming; Sociology; Statistics; dispatch; distributed generation; electric system; genetic algorithm; natural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Chinese Automation Congress (CAC), 2013
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-0332-0
  • Type

    conf

  • DOI
    10.1109/CAC.2013.6775847
  • Filename
    6775847