• DocumentCode
    1711696
  • Title

    Short Term Load Forecasting Using Artificial Neural Network

  • Author

    Banda, E. ; Folly, K.A.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Cape Town, Cape Town
  • fYear
    2007
  • Firstpage
    108
  • Lastpage
    112
  • Abstract
    This paper presents a method of short term load forecasting using artificial neural network (ANN). A three layered feed-forward neural network, trained by scaled conjugate back-propagation, is used. Two models of ANN were tested and compared. The models are applied to real data from the Cape Town Control Centre.
  • Keywords
    feedforward neural nets; load forecasting; power engineering computing; Cape Town Control Centre; artificial neural network; scaled conjugate back-propagation; short term load forecasting; three layered feed-forward neural network; Artificial intelligence; Artificial neural networks; Cities and towns; Demand forecasting; Fuzzy logic; Load forecasting; Load modeling; Predictive models; Testing; Weather forecasting; Artificial Intelligence; Artificial Neural Networks; Short-term load forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Tech, 2007 IEEE Lausanne
  • Conference_Location
    Lausanne
  • Print_ISBN
    978-1-4244-2189-3
  • Electronic_ISBN
    978-1-4244-2190-9
  • Type

    conf

  • DOI
    10.1109/PCT.2007.4538301
  • Filename
    4538301
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1711696