• DocumentCode
    556684
  • Title

    Short-term load forecasting system using data mining

  • Author

    Jin, Liu ; Jilai, Yu

  • Author_Institution
    Dept. of Electr. Eng., Harbin Inst. of Technol., Harbin, China
  • fYear
    2011
  • fDate
    10-10 Sept. 2011
  • Firstpage
    183
  • Lastpage
    188
  • Abstract
    In this paper, by means of data mining techniques, a platform of data warehouse is designed after preprocessing the huge amounts original data of power system, and a system for short term load forecasting (STLF) is developed, in which there is the synthetic technology of both fuzzy clustering and robust regression model in the platform. The useful data excavated from large amounts of data can offer the effective and accurate load forecasting information for reliable and economic operation of power systems. The validity of the designed system for STLF is shown by the simulation results of an actual power system in China.
  • Keywords
    data mining; data warehouses; fuzzy set theory; load forecasting; pattern clustering; power systems; STLF; data mining techniques; data warehouse; fuzzy clustering; power system; robust regression model; short-term load forecasting system; Data mining; Data warehouses; Load forecasting; Load modeling; Meteorology; Robustness; data mining; data warehouse; fuzzy clustering; load forecasting; robust regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Computing (ICAC), 2011 17th International Conference on
  • Conference_Location
    Huddersfield
  • Print_ISBN
    978-1-4673-0000-1
  • Type

    conf

  • Filename
    6084924