Knowledge Mapping in Electricity Demand Forecasting: A Scientometric Insight
Yang, Dongchuan1; Guo, Ju-e1; Li, Jie2,3; Wang, Shouyang4,5,6; Sun, Shaolong1
AbstractElectricity 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.

Keywordelectricity demand forecasting scientometric visualization citespace knowledge mapping
Indexed BySCI
Funding ProjectNational Natural Science Foundation of China[72101197] ; National Natural Science Foundation of China[71988101] ; Fundamental Research Funds for the Central Universities[SK2021007]
WOS Research AreaEnergy & Fuels
WOS SubjectEnergy & Fuels
WOS IDWOS:000713647200001
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Document Type期刊论文
Corresponding AuthorSun, Shaolong
Affiliation1.Xi An Jiao Tong Univ, Sch Management, Xian, Peoples R China
2.Chinese Acad Sci, Natl Sci Lib, Beijing, Peoples R China
3.Liaoning Tech Univ, Coll Safety Sci & Engn, Fuxing, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
5.Univ Chinese Acad Sci, Sch Econ & Management, Beijing, Peoples R China
6.Chinese Acad Sci, Ctr Forecasting Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Yang, Dongchuan,Guo, Ju-e,Li, Jie,et al. Knowledge Mapping in Electricity Demand Forecasting: A Scientometric Insight[J]. FRONTIERS IN ENERGY RESEARCH,2021,9:14.
APA Yang, Dongchuan,Guo, Ju-e,Li, Jie,Wang, Shouyang,&Sun, Shaolong.(2021).Knowledge Mapping in Electricity Demand Forecasting: A Scientometric Insight.FRONTIERS IN ENERGY RESEARCH,9,14.
MLA Yang, Dongchuan,et al."Knowledge Mapping in Electricity Demand Forecasting: A Scientometric Insight".FRONTIERS IN ENERGY RESEARCH 9(2021):14.
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