• DocumentCode
    1805782
  • Title

    Artificial neural networks in short term load forecasting

  • Author

    Reinschmidt, K.F. ; Ling, B.

  • Author_Institution
    Stone & Webster Eng. Corp., Boston, MA, USA
  • fYear
    1995
  • fDate
    28-29 Sep 1995
  • Firstpage
    209
  • Lastpage
    214
  • Abstract
    Discusses the use of artificial neural networks to the short term forecasting of loads. In this system there are two types of neural networks. Nonlinear and linear neural networks. The nonlinear neural network is used to capture the highly nonlinear relation between the load and various input parameters. A neural network-based ARMA model is mainly used to capture the load variation over a very short time period. The authors´ system can achieve a good accuracy in short term load forecasting
  • Keywords
    load forecasting; artificial neural networks; linear neural networks; load variation; neural network-based ARMA model; nonlinear neural network; short term load forecasting; Artificial neural networks; Humidity; Intelligent networks; Load forecasting; Load management; Neural networks; Power system modeling; Predictive models; Temperature; Wind speed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications, 1995., Proceedings of the 4th IEEE Conference on
  • Conference_Location
    Albany, NY
  • Print_ISBN
    0-7803-2550-8
  • Type

    conf

  • DOI
    10.1109/CCA.1995.555704
  • Filename
    555704