Bibliometric and Visualized Analysis of China's Smart Grid Research 2008-2018

Abstract

Smart grid (SG) offers great advantages in renewable energy integration and has become a popular trend of modern power development recently; meanwhile China is the second most prolific country using SG. Hence the purpose of this study is to get access to the research status, development, and trends of SG in China based on the 3,558 published papers obtained from the WOS core library and application of the bibliometric method and visualization analysis software VOSviewer and alluvial diagrams. The results consequently demonstrate some valuable insights. Firstly, the volume of publications in China's SG is on the rise, and the cooperation between countries and institutions is getting closer. Besides, the research hotspots have obvious interdisciplinary characteristics. Taking into consideration the impact of the information and communication field on SG, the major current research hotspots include wireless sensor network (WSN), internet of things (IoT), smart meter, big data, and security. Taking into consideration the impact of SG on traditional power systems, the main hotspots cover demand response, micro-grid, distributed generation, and electric vehicle (EV). Furthermore, China's SG research shows a trend from a single theme to diversified development. The research themes during 2010-2018 have deepened with most studies focusing on the traditional power system. The findings of this paper provide some enlightenment on China's SG research, which can present scholars with an overview of the macro perspective, help them understand the latest development of the SG field in China and offer useful guidance for future research in this subject as well.

Keywords: China; VOSviewer; alluvial diagram; bibliometrics; co-authorship; co-occurrence; smart grid (SG).

Figure 1

Outline of research design.

Figure 2

Annual publications by Chinese scholars and worldwide scholars in the field of SG.

Figure 3

Annual literature distribution of international and non-international cooperation.

Figure 4

Country co-authorship network in the field of the SG field. The larger the node is, the more papers published in cooperation between the country and China, and the thicker the connection between the nodes, the closer the cooperation between the two countries is. VOSviewer parameters: counting method: full counting, minimum occurrences 5, a total of 28 countries, normalization using LinLog/modularity method, layout parameters: attraction = 6, repulsion = 0.

Figure 5

Annual literature distribution of inter-agency and single institution.

Figure 6

Institution co-authorship network in China in the field of SG. VOSviewer parameters: counting method: full counting, minimum occurrences 10, a total of 61 institutions, normalization using LinLog/modularity method, layout parameters: attraction = 8, repulsion = 0.

Figure 7

Main research topics in the top five most productive institutions. Author-keywords are selected, counting method: full counting, search keywords such as smartgrid, smart grid, and smart grids are not included. The brighter the color, the more frequently the keyword appears. VOSviewer parameters: normalization method: LinLog/modularity, attraction = 8, repulsion = 1, clustering: resolution = 1, min. The cluster size: 1, density kernel width: item density = 1.18. (A) The research topic of the State Grid Corporation of China. A total of 1,802 keywords, minimum occurrence is 3, 131 keywords were obtained. (B) The research topic of North China Elect Power University. A total of 1,045 keywords, minimum occurrence is 3, 49 keywords were obtained. (C) The research topic of Tsinghua University. A total of 581 keywords, minimum occurrence is 3, 40 keywords were obtained. (D) The research topic of the Chinese Academy of Sciences. A total of 490 keywords, minimum occurrence is 3, 31 keywords were obtained. (E) The research topic of Shanghai Jiaotong University. A total of 613 keywords, minimum occurrence is 3, 26 keywords were obtained.

Figure 8

Author-keyword co-occurrence network of SG publications in China, 2008–2009. A total of 42 keywords, VOSviewer parameters: minimum occurrence is 1, normalization method: LinLog/modularity, attraction = 3, repulsion = 0, clustering: resolution = 1 min. The cluster size: 1. Search keywords such as smartgrid, smart grid, and smart grids are not included.

Figure 9

Author-keywords co-occurrence network of SG publications in China, 2010–2014. A total of 3,185 keywords, VOSviewer parameters: minimum occurrence is 5, normalization method: LinLog/modularity, attraction = 1, repulsion = 0, clustering: resolution = 1, min. The cluster size: 5. Search keywords such as smartgrid, smart grid, and smart grids are not included.

Figure 10

Author-keyword co-occurrence network of SG publications in China, 2015–2018. A total of 5,457 keywords, VOSviewer parameters: minimum occurrence is 10, normalization method: LinLog/modularity, attraction = 1, repulsion = 0, clustering: resolution = 1 min. The cluster size: 1. Search keywords such as smartgrid, smart grid, and smart grids are not included.

Figure 11

The alluvial diagram of author-keywords in three stages. Significance clustering in 2008–2009, 2010–2014, and 2015–2018 takes up a column in the figure. Each block in a column represents a cluster, and the height of the block reflects the keywords flow for that cluster. Darker color was used to indicate the significant subset of each cluster. All keywords that are clustered in the subset of others in 2015–2018 are colored to highlight the fusion and formation of clusters. (A) Flow of keywords in SG clustering. (B) Flow of keywords in battery clustering. (C) Flow of keywords in other clustering.