• DocumentCode
    2260307
  • Title

    Long and Medium Term Power Load Forecasting with Multi-Level Recursive Regression Analysis

  • Author

    Duan, Lidong ; Niu, Dongxiao ; Gu, Zhihong

  • Author_Institution
    Sch. of Bus. Adm., North China Electr. Power Univ., Beijing
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    514
  • Lastpage
    518
  • Abstract
    A lot of exogenous factors and the sequential variance held by the power system itself should be considered in the medium and long term load forecasting of power system. In view of these characters, the study on long and medium term load forecasting is worked by the means of multi-level recursive regression in this paper, and the model is established based on it. Forecasting is divided into two parts: the forecasting of time-varying parameters and the forecasting of power load based on the former one. The forecasting precision is improved by precise prediction of time-varying parameters and sufficient consideration of the important function of the related factors. In this paper, the yearly demand energy of a region in China from 1996 to 2003 is taken as data for the modeling. Simulation result shows that the average error of the forecasted power load of 2004 to 2006 is 1.5%. So the applicability and advantage of the method is verified.
  • Keywords
    load forecasting; power systems; regression analysis; demand energy; long term power load forecasting; medium term power load forecasting; multilevel recursive regression analysis; power system; time-varying parameters; Demand forecasting; Economic forecasting; Load forecasting; Power system analysis computing; Power system dynamics; Power system modeling; Power system planning; Predictive models; Regression analysis; Weather forecasting; Multi-level Recursive Regression Analysis; power load forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3497-8
  • Type

    conf

  • DOI
    10.1109/IITA.2008.397
  • Filename
    4739626