Visual Analysis of the Green Power Trading Research Based on the CiteSpace and VOSviewer

• Published in: 2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2) pp. 2481 - 2486
• Main Authors: Sun, Xiaorong, Liao, Yuwen, Jin, Chenhao, Han, Chunyu, Pan, Xueping, Zhang, Danxu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 11.11.2022
• Subjects: CiteSpace; Green power trading; Green products; Knowledge graphs; Mapping knowledge domain; Renewable energy sources; Soft sensors; System integration; Termination of employment; Visualization; VOSviewer
• DOI: 10.1109/EI256261.2022.10116077

The green power trading system is expected to boost renewable energy development and accelerate its transition to a low-carbon regime world widely. With the trend of research popularity in the green energy trading field, this paper utilizes bibliometric methods, and employs the CiteSpace and VOSviewer to map the knowledge of 348 research articles in the Web of Science core database from 1997 to 2022 retrieved by specific ways on the topic of green power trading. The research literature is summarized and analyzed in terms of annual publications, keyword hotspots, authors, research institutions and countries, with the aim of providing references for the research development of green power trading in China. Based the lessons learned from the existing articles, China will be able to develop the green power trading markets, policies and systems with unique Chinese characteristics, so as to increase the depth and breadth of China's research on green power trading.