• DocumentCode
    3517579
  • Title

    Power load forecasting based on elman neural network

  • Author

    Heng, Zhang ; Huanqi, Tao

  • Author_Institution
    Coll. of Electron. & Inf. Eng., Wuhan Univ. of Sci. & Eng., Wuhan, China
  • Volume
    4
  • fYear
    2009
  • fDate
    8-9 Aug. 2009
  • Firstpage
    374
  • Lastpage
    376
  • Abstract
    The article forecasts the power load with Elman neural network. First of all, it gives the basic principle of Elman neural network, and then it determines the structure parameters, transfer function and training times of model, normalizes the data. It gets a good result with forecasting actual history data of a certain electric network; it shows that forecasting power load with Elman neural network is available.
  • Keywords
    load forecasting; neural nets; power engineering computing; transfer functions; Elman neural network; power load forecasting; transfer function; Economic forecasting; Educational institutions; Load forecasting; Neural networks; Neurons; Nonlinear dynamical systems; Power engineering and energy; Power generation economics; Recurrent neural networks; Transfer functions; Elman neural network; forecast; forecast accuracy; normalization; power load;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-4247-8
  • Type

    conf

  • DOI
    10.1109/CCCM.2009.5270429
  • Filename
    5270429