• DocumentCode
    1318144
  • Title

    Weekly peak load forecasting for fast-developing cities

  • Author

    El-Razaz, Z. ; Al-Mohawes, N.

  • Author_Institution
    Dept. of Electr. Eng., King Saud Univ., Riyadh, Saudi Arabia
  • Volume
    11
  • Issue
    4
  • fYear
    1986
  • Firstpage
    184
  • Lastpage
    187
  • Abstract
    The fast pace of the development activities in the Kingdom of Saudi Arabia (KSA) has resulted in the pressing need for more dependable forecasts for expanding industrial and residential electrical demands. Rapid-developing countries like the KSA experience a large, varying load growth rate, which has dynamic rather than static characteristics. The authors present a method for developing adequate time series models for the dynamic characteristics of the electrical power demands of a typical rapid-developing electric utility from actual five-year load demand time series. Two models have been developed. The first uses a long-trend component modelled by a polynomial function and a seasonal-cyclic component modelled by Fourier expansion. The second uses an autoregressive time series model for the seasonal-cyclic component. These models have been used to generate weekly peak-load forecasts for one year ahead.
  • Keywords
    electricity supply industry; load forecasting; Fourier expansion; KSA; Kingdom of Saudi Arabia; autoregressive time series; dynamic characteristics; electric utility; electrical power demands; fast-developing cities; polynomial function; seasonal-cyclic component; time series models; weekly peak-load forecasts; Biological system modeling; Forecasting; Load forecasting; Load modeling; Market research; Mathematical model; Predictive models;
  • fLanguage
    English
  • Journal_Title
    Electrical Engineering Journal, Canadian
  • Publisher
    ieee
  • ISSN
    0700-9216
  • Type

    jour

  • DOI
    10.1109/CEEJ.1986.6591943
  • Filename
    6591943