{"title":"CiteSpace Based Knowledge Mapping Research of Artificial Intelligence Technology in Power System","authors":"Hongsheng Xu, Jixiang Lu, Zhihong Yang","doi":"10.1109/POWERCON.2018.8601848","DOIUrl":null,"url":null,"abstract":"Recently, the rapid development of Artificial Intelligence (AI) has attracted more and more attention. It has been over two decades since AI techniques emerged in power systems as effective tools to solve many complex problems. The new generation AI technologies will promote energy transition and support future power system with no doubt. This paper tried to grasp the research hotspots, frontiers and mainstream trends of AI research in power systems through a literature data collected from the Web of Science (WOS) database between 2010 and 2018, by using a widely used tool in knowledge mapping—CiteSpace. The collaboration networks were analyzed among different countries/regions and institutions contributing to the publications. A detailed discussion was given based on the general statistical data and the visualized knowledge maps. The pivotal and mushrooming articles were identified and reviewed by introducing the betweenness centrality and citation bursts as indicators.","PeriodicalId":260947,"journal":{"name":"2018 International Conference on Power System Technology (POWERCON)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Power System Technology (POWERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERCON.2018.8601848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Recently, the rapid development of Artificial Intelligence (AI) has attracted more and more attention. It has been over two decades since AI techniques emerged in power systems as effective tools to solve many complex problems. The new generation AI technologies will promote energy transition and support future power system with no doubt. This paper tried to grasp the research hotspots, frontiers and mainstream trends of AI research in power systems through a literature data collected from the Web of Science (WOS) database between 2010 and 2018, by using a widely used tool in knowledge mapping—CiteSpace. The collaboration networks were analyzed among different countries/regions and institutions contributing to the publications. A detailed discussion was given based on the general statistical data and the visualized knowledge maps. The pivotal and mushrooming articles were identified and reviewed by introducing the betweenness centrality and citation bursts as indicators.