• DocumentCode
    2629504
  • Title

    Forecasting of electricity consumption: a comparison between an econometric model and a neural network model

  • Author

    Liu, X.Q. ; Ang, B.W. ; Goh, T.N.

  • Author_Institution
    Dept. of Ind. & Syst. Eng., Nat. Univ. of Singapore, Singapore
  • fYear
    1991
  • fDate
    18-21 Nov 1991
  • Firstpage
    1254
  • Abstract
    The authors compare two forecasting models, an econometric model and a neural network model, through a case study on electricity consumption forecasting for Singapore. The results show that the two models forecast the historical consumption from 1960 to 1984 equally well but, when used to make forecasts for 1985-90, they give very different results. This anomaly arises partly from the differences in the structure of the two models, and the problem is examined using the concept of elasticity in econometric studies. The results also show that a fully trained neural network model with a good fitting performance for the past may not give a good forecasting performance for the future
  • Keywords
    load forecasting; neural nets; power engineering computing; Singapore; econometric model; electricity consumption forecasting; forecasting models; load forecasting; neural network model; Econometrics; Economic forecasting; Economic indicators; Elasticity; Energy consumption; Neural networks; Predictive models; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991. 1991 IEEE International Joint Conference on
  • Print_ISBN
    0-7803-0227-3
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.170569
  • Filename
    170569