• DocumentCode
    1876875
  • Title

    Forecasting of electricity consumption: a comparative analysis of regression and artificial neural network models

  • Author

    Fung, Y.H. ; Tummala, V. M Rao

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Hong Kong Univ., Hong Kong
  • fYear
    1993
  • fDate
    7-10 Dec 1993
  • Firstpage
    782
  • Abstract
    Several authors have formulated regression models to forecast electricity consumption. Also, more recently, several authors have attempted to formulate artificial neural network models to forecast electricity consumption. The authors have attempted in this paper to formulate and estimate both regression and artificial neural network models to forecast the electricity consumption for Hong Kong. They found that artificial neural network model forecasts are generally at least as good as those generated by the multiple linear regression model
  • Keywords
    load forecasting; neural nets; power consumption; power system analysis computing; statistical analysis; Hong Kong; artificial neural network models; electricity consumption; load forecasting; multiple linear regression model;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Advances in Power System Control, Operation and Management, 1993. APSCOM-93., 2nd International Conference on
  • Conference_Location
    IET
  • Print_ISBN
    0-85296-569-9
  • Type

    conf

  • Filename
    292624