Artificial Intelligence in Energy Economics Research: A Bibliometric Review

被引:0
|
作者
Jiao, Zhilun [1 ,2 ]
Zhang, Chenrui [1 ]
Li, Wenwen [1 ]
机构
[1] Nankai Univ, Coll Econ & Social Dev, Tianjin 300071, Peoples R China
[2] Nankai Univ, Lab Behav Econ & Policy Simulat, Tianjin 300071, Peoples R China
基金
中国国家社会科学基金;
关键词
artificial intelligence; energy economics; bibliometric analysis; network analysis; RENEWABLE ENERGY; EMERGING TRENDS; REGENERATIVE MEDICINE; FINANCE; GREEN; SET;
D O I
10.3390/en18020434
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
Artificial intelligence (AI) is gaining attention in energy economics due to its ability to process large-scale data as well as to make non-linear predictions and is providing new development opportunities and research subjects for energy economics research. The aim of this paper is to explore the trends in the application of AI in energy economics over the decade spanning 2014-2024 through a systematic literature review, bibliometrics, and network analysis. The analysis of the literature shows that the prominent research themes are energy price forecasting, AI innovations in energy systems, socio-economic impacts, energy transition, and climate change. Potential future research directions include energy supply-chain resilience and security, social acceptance and public participation, economic inequality and the technology gap, automated methods for energy policy assessment, the circular economy, and the digital economy. This innovative study contributes to a systematic understanding of AI and energy economics research from the perspective of bibliometrics and inspires researchers to think comprehensively about the research challenges and hotspots.
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页数:30
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