Forecast of Fossil Fuel Demand Based On Low Carbon Emissions from the Perspective of Energy Security

被引:4
|
作者
Huang, Yanrong [1 ,2 ]
Lin, Jie [1 ]
Wang, Yingying [3 ]
Min, Jian [4 ]
Wang, Rui [5 ,6 ]
Jin, Di [1 ]
Wei, Bo [7 ]
机构
[1] Zhejiang Univ Water Resource & Elect Power, Coll Econ & Management, Hangzhou, Peoples R China
[2] Zhejiang Univ Water Resource & Elect Power, Res Ctr Digital Econ & Sustainable Dev Water Resou, Hangzhou, Peoples R China
[3] Guizhou Univ, Sch Philosophy, Guiyang, Peoples R China
[4] Wuhan Univ Technol, Sch Management, Wuhan, Peoples R China
[5] Jiangxi Univ Sci & Technol, Sch Econ & Management, Ganzhou, Peoples R China
[6] Fujian Agr & Forestry Univ, Sch Econ, Fuzhou, Peoples R China
[7] Zhejiang Sci Tech Univ, Sch Comp Sci & Technol, Hangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
fossil fuel; demand forecast; low carbon emissions; energy security; OIL CONSUMPTION;
D O I
10.1007/s10553-023-01490-z
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
Fossil fuel is a key factor related to national energy security. Studying and judging the development trend of China's future demand for fossil fuel and obtaining fossil fuel stably and adequately is of great significance to ensuring China's political stability, normal operation of the national economy and national military security. Under the background of low carbon emissions in China, starting from the perspective of energy security, based on China's carbon emissions and GDP data from 1997 to 2019, four methods, namely Ridge Regression, ARIMA Time Series Model, BP Neural Network and Linear Regression, are used to forecast and analyze the demand for six fossil fuels: raw coal, coke, crude oil, kerosene, diesel and natural gas, providing a reference for national energy policy formulation and fossil fuel security early warning.
引用
收藏
页码:1075 / 1082
页数:8
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