Artificial Intelligence in Energy Economics Research: A Bibliometric Review

Zhilun Jiao, Chenrui Zhang and Wenwen Li ()
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Zhilun Jiao: College of Economic and Social Development, Nankai University, Tianjin 300071, China
Chenrui Zhang: College of Economic and Social Development, Nankai University, Tianjin 300071, China
Wenwen Li: College of Economic and Social Development, Nankai University, Tianjin 300071, China

Energies, 2025, vol. 18, issue 2, 1-30

Abstract: 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.

Keywords: artificial intelligence; energy economics; bibliometric analysis; network analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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