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
Link To Document