• DocumentCode
    1697004
  • Title

    Research in reservoir optimal operation based on modified ant colony optimization

  • Author

    Zhengchu, Wang ; Muxun, Zhou ; Jun, Li ; Jian, Fan ; Baishao, Zan

  • Author_Institution
    Sch. of Mech. Eng., Taizhou Coll., Taizhou, China
  • fYear
    2010
  • Firstpage
    5337
  • Lastpage
    5342
  • Abstract
    In this paper, the problem of single reservoir operation optimization is studied. Firstly, the background and mathematic model of single reservoir operation optimization are given. Then modified ant colony optimization (MACO) is presented. According to the ergodicity, stochastic property and regularity of chaos, search and optimization are carried out using the chaos variables. Population entropy is introduced to judge whether the algorithm falls in local peak or not, and catastrophe operation is also adopted. Then detailed solving steps of reservoir operation optimization based on MACO are given. Lastly, an instance is given. By calculations of the instance and comparison with other algorithms, it proves the algorithm has much stronger ability of local search and better search efficiency. It also can find better solution and certifies that this method is feasible and valid.
  • Keywords
    catastrophe theory; entropy; optimisation; reservoirs; search problems; stochastic processes; catastrophe operation; chaos regularity; ergodicity; modified ant colony optimization; population entropy; reservoir optimal operation; stochastic property; Algorithm design and analysis; Ant colony optimization; Chaos; Educational institutions; Entropy; Optimization; Reservoirs; ant colony optimization (ACO); chaos optimization algorithm; entropy; optimal operation; reservoir;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2010 8th World Congress on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-6712-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2010.5554809
  • Filename
    5554809