{"title":"基于多度量融合的电网关键部件识别","authors":"X. Mao, W. Niu, Hua Huang, Huarong Zeng, Hao Li","doi":"10.1109/ICPICS55264.2022.9873750","DOIUrl":null,"url":null,"abstract":"The safe and stable operation of the power system is a critical support to maintain the security of the national science and technology industry and the steady operation of the social economy. Complex network theory abstracts power grid components and transmission lines into nodes and links in the network, respectively, providing a new perspective to explore the structure and operation characteristics of the power grid. Therefore, it is of great significance to apply complex network theory to the prevention and control of large-scale blackouts. In this paper, we propose an approach, IDEC, to Identifying key Components in a power grid based on multi-metric fusion. IDEC considers the network's topological characteristics and the electrical operating characteristics of the power system and introduces multiple metrics, such as degree centrality, one-order structural entropy, electrical betweenness centrality, and node contribution degree, to characterize the importance of components in the power grid, which are further combined together by AHP (Analytic Hierarchy Process) to characterize the importance of components overly. In the experiments, the IEEE-39 bus system is taken as a case study, and the results are compared with those in the literature. The results show that IDEC is superior to the approaches in the literature.","PeriodicalId":257180,"journal":{"name":"2022 IEEE 4th International Conference on Power, Intelligent Computing and Systems (ICPICS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying Key Components in Power Grid based on Multi-metric Fusion\",\"authors\":\"X. Mao, W. Niu, Hua Huang, Huarong Zeng, Hao Li\",\"doi\":\"10.1109/ICPICS55264.2022.9873750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The safe and stable operation of the power system is a critical support to maintain the security of the national science and technology industry and the steady operation of the social economy. Complex network theory abstracts power grid components and transmission lines into nodes and links in the network, respectively, providing a new perspective to explore the structure and operation characteristics of the power grid. Therefore, it is of great significance to apply complex network theory to the prevention and control of large-scale blackouts. In this paper, we propose an approach, IDEC, to Identifying key Components in a power grid based on multi-metric fusion. IDEC considers the network's topological characteristics and the electrical operating characteristics of the power system and introduces multiple metrics, such as degree centrality, one-order structural entropy, electrical betweenness centrality, and node contribution degree, to characterize the importance of components in the power grid, which are further combined together by AHP (Analytic Hierarchy Process) to characterize the importance of components overly. In the experiments, the IEEE-39 bus system is taken as a case study, and the results are compared with those in the literature. The results show that IDEC is superior to the approaches in the literature.\",\"PeriodicalId\":257180,\"journal\":{\"name\":\"2022 IEEE 4th International Conference on Power, Intelligent Computing and Systems (ICPICS)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 4th International Conference on Power, Intelligent Computing and Systems (ICPICS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPICS55264.2022.9873750\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 4th International Conference on Power, Intelligent Computing and Systems (ICPICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPICS55264.2022.9873750","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying Key Components in Power Grid based on Multi-metric Fusion
The safe and stable operation of the power system is a critical support to maintain the security of the national science and technology industry and the steady operation of the social economy. Complex network theory abstracts power grid components and transmission lines into nodes and links in the network, respectively, providing a new perspective to explore the structure and operation characteristics of the power grid. Therefore, it is of great significance to apply complex network theory to the prevention and control of large-scale blackouts. In this paper, we propose an approach, IDEC, to Identifying key Components in a power grid based on multi-metric fusion. IDEC considers the network's topological characteristics and the electrical operating characteristics of the power system and introduces multiple metrics, such as degree centrality, one-order structural entropy, electrical betweenness centrality, and node contribution degree, to characterize the importance of components in the power grid, which are further combined together by AHP (Analytic Hierarchy Process) to characterize the importance of components overly. In the experiments, the IEEE-39 bus system is taken as a case study, and the results are compared with those in the literature. The results show that IDEC is superior to the approaches in the literature.