• DocumentCode
    3204576
  • Title

    Short term load forecast using Burg autoregressive technique

  • Author

    Kamel, Nidal ; Baharudin, Zuhairi

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Univ. Teknol. Petronas, Tronoh
  • fYear
    2007
  • fDate
    25-28 Nov. 2007
  • Firstpage
    912
  • Lastpage
    916
  • Abstract
    Short-term load forecasting plays an important role in planning and operation of power system. The accuracy of this forecasted value is necessary for economically efficient operation and also for effective control. This paper describes a method of autoregressive Burg in solving one week ahead of short term load forecasting. The proposed method is tested based from historical load data of Malaysia Grid system. The accuracy of proposed method, i.e., the forecast error, which is the difference between the forecast value and actual value of the load, is obtained and reported.
  • Keywords
    autoregressive moving average processes; load forecasting; power system economics; power system planning; Burg autoregressive technique; autoregressive moving average; power system economic; power system operation; power system planning; short term load forecasting; Artificial neural networks; Demand forecasting; Economic forecasting; Fuzzy logic; Intelligent systems; Load forecasting; Power generation economics; Power system economics; Power system planning; Predictive models; Autoregressive moving average (ARMA); Burg; MAPE; Short term load forecasting (STLF); autoregressive (AR);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-1355-3
  • Electronic_ISBN
    978-1-4244-1356-0
  • Type

    conf

  • DOI
    10.1109/ICIAS.2007.4658519
  • Filename
    4658519