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This research presents systematic bibliometric analysis of artificial intelligence applications in renewable energy systems. The study examines 2177 publications from the Web of Science database spanning the period 1995–2026. Through rigorous quantitative methods and network visualization techniques, the research identifies key contributors, institutional collaborations, and thematic structures within this domain. The analysis reveals the temporal evolution of research activities, geographic distribution of scientific output, and conceptual frameworks that characterize the integration of artificial intelligence into renewable energy technologies.

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Bibliometric Analysis About AI in Sustainable Energy Technologies

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  • 发表日期：

    2026年

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  • Afsin Gungor,
  • Sena Zeliha Taskan,
  • Mehmet Bucakli,
  • Ahmet Cosgun

摘要

This research presents systematic bibliometric analysis of artificial intelligence applications in renewable energy systems. The study examines 2177 publications from the Web of Science database spanning the period 1995–2026. Through rigorous quantitative methods and network visualization techniques, the research identifies key contributors, institutional collaborations, and thematic structures within this domain. The analysis reveals the temporal evolution of research activities, geographic distribution of scientific output, and conceptual frameworks that characterize the integration of artificial intelligence into renewable energy technologies.