• DocumentCode
    3447511
  • Title

    Power Load Forecast Model of Genetic Neural Network Based on Tabu Search

  • Author

    Mian, Xing ; Shu-ling, Wang ; Zhi-Hong, Gu ; Zhen-tao, Li

  • Author_Institution
    North China Electr. Power Univ., Baoding
  • fYear
    2007
  • fDate
    23-25 May 2007
  • Firstpage
    1903
  • Lastpage
    1906
  • Abstract
    The neural network has been applied to the area of power load forecast successfully, but it has such disadvantages of local optimization and slow convergence speed. A new kind of genetic neural network forecast model based on tabu search was proposed for overcoming those disadvantages. Utilizing the global optimizing ability of genetic algorithm and the memory function and ability of mountain climbing of tabu search, it defined a tabu aberrance operator and constructed a mixed genetic tabu algorithm, which can solve the above disadvantages of neural network and the premature problems of genetic algorithm, to train the weights and thresholds of neural network. Comparing with normal genetic algorithms, this genetic neural network based on tabu search achieved better forecast result.
  • Keywords
    genetic algorithms; load forecasting; neural nets; power engineering computing; genetic algorithm; genetic neural network; global optimizing ability; local optimization; memory function; power load forecast model; slow convergence speed; tabu aberrance operator; tabu search; Artificial neural networks; Convergence; Genetic algorithms; Load forecasting; Load modeling; Mathematics; Neural networks; Predictive models; Publishing; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-0737-8
  • Electronic_ISBN
    978-1-4244-0737-8
  • Type

    conf

  • DOI
    10.1109/ICIEA.2007.4318741
  • Filename
    4318741