ARIMA forecasting of China's coal consumption, price and investment by 2030

被引:55
作者
Jiang, Shumin [1 ,2 ]
Yang, Chen [1 ]
Guo, Jingtao [1 ]
Ding, Zhanwen [1 ,2 ]
机构
[1] Jiangsu Univ, Fac Sci, Zhenjiang, Peoples R China
[2] Jiangsu Univ, Ctr Energy Dev & Environm Protect Strategy Res, Zhenjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
ARIMA; coal consumption; coal investment; coal price; energy forecasting; ENERGY-CONSUMPTION; EMISSION;
D O I
10.1080/15567249.2017.1423413
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Forecasting of energy consumption, price, and investment in coal industry is one of the most important proactive approaches and policy instruments used by decision-makers in China. Due to the richer information on time-related changes than the other methods, autoregressive integrated moving average (ARIMA) is applied to estimate the further coal price, consumption, and investment of China from 2016 to 2030. The best-fitted models for coal price, consumption, and investment at each predicted step are selected. The empirical results show that the annual average rate of coal consumption and investment will decrease between 2016 and 2030 except for coal price, which exhibits fluctuant behavior in the forecast period. The annual droop rate of coal consumption from 2016 to 2030 will be rather big, nearly the same with the annual growth rate from 2000 to 2015. The coal investment has the similar result with coal consumption.
引用
收藏
页码:190 / 195
页数:6
相关论文
共 14 条
[1]   Forecasting monthly electric energy consumption in eastern Saudi Arabia using univariate time-series analysis [J].
AbdelAal, RE ;
AlGarni, AZ .
ENERGY, 1997, 22 (11) :1059-1069
[2]  
BP, 2017, BP STAT REV WORLD EN
[3]   ARIMA forecasting of primary energy demand by fuel in Turkey [J].
Ediger, Volkan S. ;
Akar, Sertac .
ENERGY POLICY, 2007, 35 (03) :1701-1708
[4]   China's farewell to coal: A forecast of coal consumption through 2020 [J].
Hao, Yu ;
Zhang, Zong-Yong ;
Liao, Hua ;
Wei, Yi-Ming .
ENERGY POLICY, 2015, 86 :444-455
[5]  
IEA, 2014, CARB DIOX FUEL COMB
[6]  
Macgregor J., 2017, ENERG POLICY, P107
[7]   Forecasting electricity consumption in New Zealand using economic and demographic variables [J].
Mohamed, Z ;
Bodger, P .
ENERGY, 2005, 30 (10) :1833-1843
[8]  
NBSC, 2016, NAT BUR STAT PEOPL R
[9]   Application of ARIMA for forecasting energy consumption and GHG emission: A case study of an Indian pig iron manufacturing organization [J].
Sen, Parag ;
Roy, Mousumi ;
Pal, Parimal .
ENERGY, 2016, 116 :1031-1038
[10]  
Siew LimYing., 2008, The Malaysian Journal of Analytics Sciences, V12, P257