Vulnerability analysis of power grid structure based on complex network theory
IntroductionThe key nodes of an intelligent distribution network significantly impact the reliability and stability of the distribution network’s operation. The failure of these key nodes can severely affect the safe operation of the distribution network. Therefore, vulnerability analysis of key nod...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2024.1498678/full |
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| author | Zhichun Yang Huaidong Min Jie Zhao Xuzhu Dong Fan Yang Chenhao Wang Nan Zhang |
| author_facet | Zhichun Yang Huaidong Min Jie Zhao Xuzhu Dong Fan Yang Chenhao Wang Nan Zhang |
| author_sort | Zhichun Yang |
| collection | DOAJ |
| description | IntroductionThe key nodes of an intelligent distribution network significantly impact the reliability and stability of the distribution network’s operation. The failure of these key nodes can severely affect the safe operation of the distribution network. Therefore, vulnerability analysis of key nodes is particularly important.MethodsThis article proposes a comprehensive weighting method for evaluating indicators,combining the analytic hierarchy process (AHP) and entropy weighting method, while considering the structure and operational status of the power system grid. Key node structural evaluation indicators, such as node degree, node shrinkage centrality, and electric mediator, are established considering “significance” and “destructiveness.” State indicators are established based on the degree of impact of current, voltage, and load changes on the grid, as well as the uniformity of their distribution, including the improved current distribution entropy, voltage terre entropy, and three-phase state indicators of lost load. Subsequently, based on the AHP and entropy weighting method, a comprehensive weighting method is proposed to assign subjective and objective weights to the comprehensive evaluation indicators, obtaining the comprehensive weights of the indicators. Finally, the gray correlation degree is introduced to improve the ideal solution of the multi-objective decision making method, obtaining the criticality of the grid nodes and then identifying the critical nodes.Results and DiscussionThe example analysis presented in this article shows that the identified critical nodes of the power grid have a high degree of overlap with the identification results of different methods, can better identify edge nodes, and validate the effectiveness of the proposed evaluation indicators and key node identification methods. |
| format | Article |
| id | doaj-art-1d8abbfc9386484abd0e15b3597bf761 |
| institution | Kabale University |
| issn | 2296-598X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj-art-1d8abbfc9386484abd0e15b3597bf7612025-01-03T04:13:36ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2025-01-011210.3389/fenrg.2024.14986781498678Vulnerability analysis of power grid structure based on complex network theoryZhichun Yang0Huaidong Min1Jie Zhao2Xuzhu Dong3Fan Yang4Chenhao Wang5Nan Zhang6State Grid Hubei Electric Power Company Electric Power Research Institute, Wuhan, Hubei, ChinaState Grid Hubei Electric Power Company Electric Power Research Institute, Wuhan, Hubei, ChinaHubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network, School of Electrical Engineering and Automation, Wuhan University, Wuhan, ChinaHubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network, School of Electrical Engineering and Automation, Wuhan University, Wuhan, ChinaState Grid Hubei Electric Power Company Electric Power Research Institute, Wuhan, Hubei, ChinaHubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network, School of Electrical Engineering and Automation, Wuhan University, Wuhan, ChinaState Grid Hubei Electric Power Co., Ltd. Wuhan Power Supply Company, Wuhan, Hubei, ChinaIntroductionThe key nodes of an intelligent distribution network significantly impact the reliability and stability of the distribution network’s operation. The failure of these key nodes can severely affect the safe operation of the distribution network. Therefore, vulnerability analysis of key nodes is particularly important.MethodsThis article proposes a comprehensive weighting method for evaluating indicators,combining the analytic hierarchy process (AHP) and entropy weighting method, while considering the structure and operational status of the power system grid. Key node structural evaluation indicators, such as node degree, node shrinkage centrality, and electric mediator, are established considering “significance” and “destructiveness.” State indicators are established based on the degree of impact of current, voltage, and load changes on the grid, as well as the uniformity of their distribution, including the improved current distribution entropy, voltage terre entropy, and three-phase state indicators of lost load. Subsequently, based on the AHP and entropy weighting method, a comprehensive weighting method is proposed to assign subjective and objective weights to the comprehensive evaluation indicators, obtaining the comprehensive weights of the indicators. Finally, the gray correlation degree is introduced to improve the ideal solution of the multi-objective decision making method, obtaining the criticality of the grid nodes and then identifying the critical nodes.Results and DiscussionThe example analysis presented in this article shows that the identified critical nodes of the power grid have a high degree of overlap with the identification results of different methods, can better identify edge nodes, and validate the effectiveness of the proposed evaluation indicators and key node identification methods.https://www.frontiersin.org/articles/10.3389/fenrg.2024.1498678/fullcomprehensive weightskey nodesimproved TOPSIS methodAHPcomprehensive evaluation indexes |
| spellingShingle | Zhichun Yang Huaidong Min Jie Zhao Xuzhu Dong Fan Yang Chenhao Wang Nan Zhang Vulnerability analysis of power grid structure based on complex network theory Frontiers in Energy Research comprehensive weights key nodes improved TOPSIS method AHP comprehensive evaluation indexes |
| title | Vulnerability analysis of power grid structure based on complex network theory |
| title_full | Vulnerability analysis of power grid structure based on complex network theory |
| title_fullStr | Vulnerability analysis of power grid structure based on complex network theory |
| title_full_unstemmed | Vulnerability analysis of power grid structure based on complex network theory |
| title_short | Vulnerability analysis of power grid structure based on complex network theory |
| title_sort | vulnerability analysis of power grid structure based on complex network theory |
| topic | comprehensive weights key nodes improved TOPSIS method AHP comprehensive evaluation indexes |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2024.1498678/full |
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