Knowledge Graph-based Bibliometric Analysis of Artificial Intelligence in Power Systems

Artificial intelligence (AI), with its powerful perception and decision-making capabilities, has demonstrated significant potential for application within power systems. The development of smart grids has accelerated the research into next-generation AI in power systems. However, a systematic review and analysis of domestic and international research outcomes remain lacking. Additionally, there is a need for accurate summaries and forecasts regarding current and future development trends in this field. In response, this study initially retrieves 3,365 research documents from the China National Knowledge Infrastructure (CNKI) database and 42,542 documents from the Web of Science Core Collection database, spanning the period from 2003 to 2023. By employing bibliometric and knowledge mapping techniques, along with the application of VOSviewer and Origin software, a quantitative analysis of annual publication trends, disciplinary distribution, geographic and institutional contributions, and research hotspots in the field of AI in power systems is conducted. This comprehensive and multidimensional analysis provides insights into the research history and current development status in this field. Finally, the study offers a summary of the distinctive characteristics of existing research and an outlook on emerging trends.