• DocumentCode
    2280833
  • Title

    Artificial neural network-based forecast for electricity consumption in Malaysia

  • Author

    Othman, M. S Mohamed ; Johari, D. ; Musirin, I. ; Rahman, Titik Khawa Abdul ; Ismail, N. F Nik

  • Author_Institution
    Univ. Technol. MARA, Shah Alam, Malaysia
  • fYear
    2010
  • fDate
    Nov. 29 2010-Dec. 1 2010
  • Firstpage
    24
  • Lastpage
    28
  • Abstract
    An essential element of electric utility resource planning is the long term forecast of the electricity consumption. This paper presents an approach to forecast annual electricity consumption by using artificial neural network based on historical data for Malaysia. It involves developing several ANN designs and selecting the best network that can produce the best results in terms of its accuracy. The network is developed by means of economical conditions and how the variables are going to be changed in the following years. After obtaining the most reliable model, ANN is used to forecast the electricity consumption. The developed ANN model yields very satisfactory results and as a result, the range of electricity consumption can be successfully obtained.
  • Keywords
    electricity supply industry; load forecasting; neural nets; power consumption; Malaysia; artificial neural network-based forecast; electric utility resource planning; electricity consumption; Artificial neural network; cross validation; electricity consumption; forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy (PECon), 2010 IEEE International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-8947-3
  • Type

    conf

  • DOI
    10.1109/PECON.2010.5697551
  • Filename
    5697551