A Bibliometric Analysis of Artificial Intelligence and Electrical Energy Reliability

The escalating dependence on artificial intelligence (AI) in energy and electrical power dependability systems has garnered significant interest in both academic and industrial circles. This study provides a bibliometric examination of artificial intelligence (AI) applications in the field of electrical dependability, covering the time frame from 2002 to 2023. The main aim of this study is to examine the patterns of publication, notable authors, institutions, and funding organizations that contribute to research in artificial intelligence for electrical dependability. A further objective of the endeavor is to chart the co-authorship networks, keyword frequencies, and citation trends in the field. Extraction of data from the Scopus database was carried out using an extensive search approach, and subsequently, network visualization was performed using VOSviewer. The findings indicated a substantial rise in research productivity throughout the last ten years, accompanied with a distinguishable expansion in joint research endeavors. China has established itself as the foremost nation in research on electrical reliability powered by artificial intelligence, with the United States and India following closely after. In addition, the National Natural Science Foundation of China was recognized as the most productive and influential funding institution. The thematic analysis revealed many prominent subjects in the sector, such as predictive maintenance, problem detection, and energy consumption optimization via artificial intelligence. The paper offers invaluable insights into the present research landscape and emphasizes developing trends, providing a clear plan for future research objectives in the fields of artificial intelligence and electrical dependability.