• DocumentCode
    1608986
  • Title

    The Application and Research of the PAR Approach in the Short Term Load Forecasting

  • Author

    Fan, Yu ; Min, Dong

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Xi´´an Technol. Univ., Xi´´an, China
  • fYear
    2012
  • Firstpage
    307
  • Lastpage
    309
  • Abstract
    For load sequences changes run in cycle by days, weeks, and years, and the power load data are non-stationary, the periodic autoregressive (PAR) model is used to describe the periodic variations accurately of the power load and establish a short-term forecast of the prediction model. Compared with traditional time series, it is show that this way is more effective.
  • Keywords
    autoregressive processes; load forecasting; PAR approach; load sequences; periodic autoregressive model; periodic variations; power load; prediction model; short term load forecasting; time series; Industrial control; PAR model; Power load; Short-term forecast;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4673-1450-3
  • Type

    conf

  • DOI
    10.1109/ICICEE.2012.88
  • Filename
    6322377
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1608986