• DocumentCode
    3699992
  • Title

    Improved genetic algorithm and its application in power dispatch of wind turbines

  • Author

    Guo-Huang Li;Guo-Li Zhang;Le-Feng Zhang

  • Author_Institution
    Department of Mathematics &
  • Volume
    2
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    815
  • Lastpage
    819
  • Abstract
    The local search capability of classical genetic algorithm is weak, and hardly deals with constraints. To solve these problems, the adaptive crossover probability and mutation probability are developed, and a new genetic algorithm with quasi-simplex technique is proposed in this paper. An active power and reactive power dispatch model of wind farm turbine is established, and a better scheduling scheme can be worked out by using improved genetic algorithm. This scheduling scheme obtains less copper loss and shows that the improved genetic algorithm has a good application value.
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICMLC.2015.7340658
  • Filename
    7340658