• DocumentCode
    2096936
  • Title

    Online Solving Of Economic Dispatch Problem Using Neural Network Approach And Comparing It With Classical Method

  • Author

    Mohammadi, Amir ; Varahram, Mohammad Hadi ; Kheirizad, Iraj

  • Author_Institution
    Sci. & Res. Branch, Islamic Azad Univ.
  • fYear
    2006
  • fDate
    13-14 Nov. 2006
  • Firstpage
    581
  • Lastpage
    586
  • Abstract
    In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and lambda iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for convergence is considerably smaller compared to classical methods
  • Keywords
    Hopfield neural nets; convergence; iterative methods; power generation dispatch; power generation economics; power system analysis computing; Hopfield neural network; convergence; economic dispatch problem; lambda iteration method; Fuel economy; Hopfield neural networks; Neural networks; Neurons; Power generation; Power generation economics; Power system economics; Power system modeling; Power systems; Propagation losses;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies, 2006. ICET '06. International Conference on
  • Conference_Location
    Peshawar
  • Print_ISBN
    1-4244-0502-5
  • Electronic_ISBN
    1-4244-0503-3
  • Type

    conf

  • DOI
    10.1109/ICET.2006.335922
  • Filename
    4136890