• DocumentCode
    2987146
  • Title

    The variable weight combination load forecasting based on grey model and semi-parametric Regression Model

  • Author

    Shushu Ma ; Xingying Chen ; Yingchen Liao ; Gang Wang ; Xiaohua Ding ; Kai Chen

  • Author_Institution
    Hohai Univ., Nanjing, China
  • fYear
    2013
  • fDate
    22-25 Oct. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Grey model using dimensional information update technology always contains the latest information from sample data, it guarantees the accuracy of mid-long term load forecasting. Semi-parametric regression model which combines the advantages of parametric model and nonparametric model, it can fully reflect the complexity and uncertainties of the load change. This paper put forward an improved method which combines grey model with semi-parametric regression model by time-varying weight for load forecasting, the proposed method would make full use of data information and consider its inherent regularity completely, which makes prediction more realistic. At last, a comparison of the error has been made between the single model and the combination model. The test example results show that this method has higher precision.
  • Keywords
    grey systems; load forecasting; regression analysis; dimensional information update technology; grey model; load change; mid-long term load forecasting; nonparametric model; parametric model; semiparametric regression model; time-varying weight; variable weight combination load forecasting; Adaptation models; Analytical models; Data models; Load forecasting; Load modeling; Mathematical model; Predictive models; Grey model; Semi-parametric regression model; Variable weight combination;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2013 - 2013 IEEE Region 10 Conference (31194)
  • Conference_Location
    Xi´an
  • ISSN
    2159-3442
  • Print_ISBN
    978-1-4799-2825-5
  • Type

    conf

  • DOI
    10.1109/TENCON.2013.6719040
  • Filename
    6719040