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Knowledge Mapping in Electricity Demand Forecasting: A Scientometric Insight

  • Xi'an Jiaotong University
  • CAS - National Science Library
  • Liaoning Technical University
  • CAS - Academy of Mathematics and System Sciences
  • University of Chinese Academy of Sciences
  • Chinese Academy of Sciences

科研成果: 期刊稿件文章同行评审

7 引用 (Scopus)

摘要

Electricity demand forecasting plays a fundamental role in the operation and planning procedures of power systems, and the publications related to electricity demand forecasting have attracted more and more attention in the past few years. To have a better understanding of the knowledge structure in the field of electricity demand forecasting, we applied scientometric methods to analyze the current state and the emerging trends based on the 831 publications from the Web of Science Core Collection during the past 20 years (1999–2018). Employing statistical description analysis, cooperative network analysis, keyword co-occurrence analysis, co-citation analysis, cluster analysis, and emerging trend analysis techniques, this study gives a comprehensive overview of the most critical countries, institutions, journals, authors, and publications in this field, cooperative networks relationships, research hotspots, and emerging trends. The results can provide meaningful guidance and helpful insights for researchers to enhance the understanding of crucial research, emerging trends, and new developments in electricity demand forecasting.

源语言英语
文章编号771433
期刊Frontiers in Energy Research
9
DOI
出版状态已出版 - 14 10月 2021

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