• DocumentCode
    2808029
  • Title

    Integration of Grey Model and Multiple Regression Model to Predict Energy Consumption

  • Author

    Wang, Qi ; Xiaodan Wang ; Xia, Fengyi

  • Author_Institution
    Sch. of Life & Environ. Sci., Wenzhou Univ., Wenzhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    16-18 Oct. 2009
  • Firstpage
    194
  • Lastpage
    197
  • Abstract
    Forecasting of energy consumption has always been an essential part of energy planning and policy. This paper presents grey model (GM), multiple regression model (MRM) and the integration model of grey model and multiple regression model (IGMMRM) to forecast the number and trend of energy consumption in Zhejiang. The three prediction models established are the highly accurate forecasting, but the combination model was found to be the best model which can overcome some defects of single model such as GM and MRM when mining information. Using IGMMRM, energy consumption of Zhejiang will be almost 0.19 billion tons coal equivalent in 2010 and over 0.3 billion tons coal equivalent in 2015, respectively. It is urgent that level of sustainable utilization for energy should be further improved in Zhejiang.
  • Keywords
    load forecasting; regression analysis; enegy policy; energy consumption forecasting; energy planning; grey model; multiple regression model; Air pollution; Chemical engineering; Chemistry; Economic indicators; Energy consumption; Load forecasting; Mathematical model; Predictive models; Technology planning; Volatile organic compounds; Combination model; Energy consumption forecasting; Grey model; Multiple regression model; Zhejiang;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy and Environment Technology, 2009. ICEET '09. International Conference on
  • Conference_Location
    Guilin, Guangxi
  • Print_ISBN
    978-0-7695-3819-8
  • Type

    conf

  • DOI
    10.1109/ICEET.2009.53
  • Filename
    5362832