气候变化领域集成服务门户(CCPortal): Analysis and forecast of China's energy consumption structure

CCPortal

DOI	10.1016/j.enpol.2021.112630
	Analysis and forecast of China's energy consumption structure
	Zeng S.; Su B.; Zhang M.; Gao Y.; Liu J.; Luo S.; Tao Q.
发表日期	2021
ISSN	0301-4215
卷号	159
英文摘要	In the context of the practice of high-quality social development gradually deepening, the optimization of energy structure is an important link to promote high-quality economic development. We used China's historical data from 1980 to 2019, and identified 17 influencing factors of its energy consumption structure. From four dimensions (economy, structure, technology, population and policy), Copula function was employed to establish a multi-factor dynamic support vector machine model to predict the advanced index of energy consumption structure in 2020–2030. The results show that (a) China's energy consumption structure is being optimized. An up-trend is found in the advanced index of China's energy consumption structure, and the proportion of its coal consumption shows a downward trend, but the decline is gradually decreasing. (b) Energy price adjustment, increased rural income, industry structure improvement, higher R&D expenses contribute to energy consumption structure optimization in China. (c) China is able to meet the carbon emission target set for 2030 on schedule. China is expected to reach carbon emission peak in 2030, and non-fossil energy will account for about 21% in 2026. The carbon emission target per unit of GDP is expected to be completed ahead of schedule. © 2021 Elsevier Ltd
英文关键词	Advanced index; China; Copula function model; Energy consumpxtion structure; Multi-factor dynamic support vector machine model
语种	英语
scopus关键词	Carbon; Economic and social effects; Economics; Energy policy; Energy utilization; Support vector machines; Advanced index; China; Copula function model; Copula functions; Dynamic supports; Energy; Energy consumpxtion structure; Function modelling; Multi-factor; Multi-factor dynamic support vector machine model; Support vector machine models; Structural optimization; carbon emission; consumption behavior; economic analysis; economic development; energy use; forecasting method; Gross Domestic Product; research and development; resource economy; support vector machine; targeting; China
来源期刊	Energy Policy
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/256491
作者单位	Research Center for Economy of Upper Reaches of the Yangtse River, Chongqing Technology and Business University, Chongqing, China; Energy Studies Institute, National University of Singapore, Singapore; School of Economics, Shenzhen University, Shenzhen, China; School of Finance, Chongqing Technology and Business University, Chongqing, China
推荐引用方式 GB/T 7714	Zeng S.,Su B.,Zhang M.,et al. Analysis and forecast of China's energy consumption structure[J],2021,159.
APA	Zeng S..,Su B..,Zhang M..,Gao Y..,Liu J..,...&Tao Q..(2021).Analysis and forecast of China's energy consumption structure.Energy Policy,159.
MLA	Zeng S.,et al."Analysis and forecast of China's energy consumption structure".Energy Policy 159(2021).