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<p>Artificial intelligence (AI) is increasingly transforming the renewable energy (RE) sector by enabling intelligent data-driven solutions to address complex operational and integration challenges. This study presents a comprehensive bibliometric analysis of global research on AI applications in renewable energy from 2010 to 2025, based on 1409 publications retrieved from the Scopus Core Collection. Using VOSviewer software, the study maps publication trends, collaboration networks, and thematic clusters to characterize the intellectual landscape and research evolution of this rapidly growing domain. The findings indicate that China leads in research output and international collaboration, followed by the United States and key European countries. Major research themes include AI-based techniques for transient stability assessment, frequency regulation, and solar and wind energy forecasting—areas essential for improving grid reliability and renewable integration. The analysis also highlights regional differences in AI investment and policy focus: Europe emphasizes ethical governance, China shows investment variability, and the United States leads in innovation scale. Kazakhstan contribution to AI Applications in Renewable Energy is also presented. Overall, this study provides an evidence-based overview of global research trajectories and emerging trends, offering valuable insights to guide future investigations and policy directions in AI-driven renewable energy systems.</p>

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Scientific mapping of artificial intelligence research in renewable energy through bibliometric analysis using VOSviewer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月3日

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  • Satyanand Singh,
  • Bhanu Pratap Soni,
  • Shynara Sarkambayeva,
  • Bakytzhan Amralinova,
  • Poorva Soni

摘要

Artificial intelligence (AI) is increasingly transforming the renewable energy (RE) sector by enabling intelligent data-driven solutions to address complex operational and integration challenges. This study presents a comprehensive bibliometric analysis of global research on AI applications in renewable energy from 2010 to 2025, based on 1409 publications retrieved from the Scopus Core Collection. Using VOSviewer software, the study maps publication trends, collaboration networks, and thematic clusters to characterize the intellectual landscape and research evolution of this rapidly growing domain. The findings indicate that China leads in research output and international collaboration, followed by the United States and key European countries. Major research themes include AI-based techniques for transient stability assessment, frequency regulation, and solar and wind energy forecasting—areas essential for improving grid reliability and renewable integration. The analysis also highlights regional differences in AI investment and policy focus: Europe emphasizes ethical governance, China shows investment variability, and the United States leads in innovation scale. Kazakhstan contribution to AI Applications in Renewable Energy is also presented. Overall, this study provides an evidence-based overview of global research trajectories and emerging trends, offering valuable insights to guide future investigations and policy directions in AI-driven renewable energy systems.