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
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;
Conference_Titel :
Energy and Environment Technology, 2009. ICEET '09. International Conference on
Conference_Location :
Guilin, Guangxi
Print_ISBN :
978-0-7695-3819-8
DOI :
10.1109/ICEET.2009.53