• DocumentCode
    1679607
  • Title

    Electric power systems load forecasting: a survey

  • Author

    Lotufo, A.D.P. ; Minussi, C.R.

  • Author_Institution
    DEE/FEIS/UNESP, Sao Paulo, Brazil
  • fYear
    1999
  • Firstpage
    36
  • Abstract
    This work reviews the latest works on load forecasting, classifying them according to presented methods and models, as statistical, intelligent systems, neural networks and fuzzy logic. As there are many different models and methods, we have studied the principal ones considering classical statistical and modern methods like neural networks and fuzzy logic. We emphasize the importance of load forecasting in modern operation centers, and conclude that nowadays the most used forecasting methods are the neural networks and fuzzy logic, but the statistical ones continue being used although to a lesser extent.
  • Keywords
    artificial intelligence; fuzzy logic; load forecasting; neural nets; power system analysis computing; fuzzy logic; intelligent systems; modern operation centers; neural networks; power systems load forecasting; prediction methods; statistical methods; Fuzzy logic; Intelligent networks; Intelligent systems; Load forecasting; Load modeling; Mathematical model; Neural networks; Power system modeling; Power system reliability; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Power Engineering, 1999. PowerTech Budapest 99. International Conference on
  • Conference_Location
    Budapest, Hungary
  • Print_ISBN
    0-7803-5836-8
  • Type

    conf

  • DOI
    10.1109/PTC.1999.826467
  • Filename
    826467