Adaptive identification of critical nodes for fault‐on voltage support in islanded microgrids
Abstract The shedding of critical distributed energy resources during faults in an islanded microgrid may induce widespread voltage drops, potentially triggering a cascade of reactions leading to the collapse of the entire system. Accurately identifying critical nodes is the key technology to improv...
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| Format: | Article |
| Language: | English |
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Wiley
2024-12-01
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| Series: | IET Renewable Power Generation |
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| Online Access: | https://doi.org/10.1049/rpg2.13033 |
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| _version_ | 1832579842457993216 |
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| author | Shiran Cao Lipeng Zhu Jiayong Li Wen Huang Lili He Wei Zhang Huimin Zhao Zhikang Shuai |
| author_facet | Shiran Cao Lipeng Zhu Jiayong Li Wen Huang Lili He Wei Zhang Huimin Zhao Zhikang Shuai |
| author_sort | Shiran Cao |
| collection | DOAJ |
| description | Abstract The shedding of critical distributed energy resources during faults in an islanded microgrid may induce widespread voltage drops, potentially triggering a cascade of reactions leading to the collapse of the entire system. Accurately identifying critical nodes is the key technology to improve the resilience of microgrids. However, multi‐source coupling and the uncertainty in fault‐induced voltage sag can diminish the accuracy of node importance identification. To address this, this paper proposes an adaptive node identification method designed for quick and accurate identification of nodes that cope with various fault scenarios. This method introduces an index for evaluating voltage support capability based on the equivalent voltage drop range. This index adapts to fault uncertainty while integrating electrical parameters with spatial position. Furthermore, a higher‐order transition matrix reconstruction strategy with power propagation characteristics is proposed to reduce the higher‐order complexities arising from remote end faults' current flowing path length. Ultimately, the transition matrix is optimized by integrating it with the PageRank algorithm and highlighting the importance of source nodes. The proposed method is validated by numerical computation and time‐domain simulation results in a benchmark test microgrid, demonstrating its remarkable identification accuracy in a variety of fault scenarios. |
| format | Article |
| id | doaj-art-1cfa41267b2f4c9986dbc343b4f1f6b9 |
| institution | Kabale University |
| issn | 1752-1416 1752-1424 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Renewable Power Generation |
| spelling | doaj-art-1cfa41267b2f4c9986dbc343b4f1f6b92025-01-30T12:15:53ZengWileyIET Renewable Power Generation1752-14161752-14242024-12-0118163798380910.1049/rpg2.13033Adaptive identification of critical nodes for fault‐on voltage support in islanded microgridsShiran Cao0Lipeng Zhu1Jiayong Li2Wen Huang3Lili He4Wei Zhang5Huimin Zhao6Zhikang Shuai7College of Electrical and Information Engineering Hunan University Changsha ChinaCollege of Electrical and Information Engineering Hunan University Changsha ChinaCollege of Electrical and Information Engineering Hunan University Changsha ChinaCollege of Electrical and Information Engineering Hunan University Changsha ChinaCollege of Electrical and Information Engineering Hunan University Changsha ChinaCollege of Electrical and Information Engineering Hunan University Changsha ChinaCRRC Zhuzhou Electric Locomotive Research Institute Co., Ltd Zhuzhou ChinaCollege of Electrical and Information Engineering Hunan University Changsha ChinaAbstract The shedding of critical distributed energy resources during faults in an islanded microgrid may induce widespread voltage drops, potentially triggering a cascade of reactions leading to the collapse of the entire system. Accurately identifying critical nodes is the key technology to improve the resilience of microgrids. However, multi‐source coupling and the uncertainty in fault‐induced voltage sag can diminish the accuracy of node importance identification. To address this, this paper proposes an adaptive node identification method designed for quick and accurate identification of nodes that cope with various fault scenarios. This method introduces an index for evaluating voltage support capability based on the equivalent voltage drop range. This index adapts to fault uncertainty while integrating electrical parameters with spatial position. Furthermore, a higher‐order transition matrix reconstruction strategy with power propagation characteristics is proposed to reduce the higher‐order complexities arising from remote end faults' current flowing path length. Ultimately, the transition matrix is optimized by integrating it with the PageRank algorithm and highlighting the importance of source nodes. The proposed method is validated by numerical computation and time‐domain simulation results in a benchmark test microgrid, demonstrating its remarkable identification accuracy in a variety of fault scenarios.https://doi.org/10.1049/rpg2.13033microgridspower system identification |
| spellingShingle | Shiran Cao Lipeng Zhu Jiayong Li Wen Huang Lili He Wei Zhang Huimin Zhao Zhikang Shuai Adaptive identification of critical nodes for fault‐on voltage support in islanded microgrids IET Renewable Power Generation microgrids power system identification |
| title | Adaptive identification of critical nodes for fault‐on voltage support in islanded microgrids |
| title_full | Adaptive identification of critical nodes for fault‐on voltage support in islanded microgrids |
| title_fullStr | Adaptive identification of critical nodes for fault‐on voltage support in islanded microgrids |
| title_full_unstemmed | Adaptive identification of critical nodes for fault‐on voltage support in islanded microgrids |
| title_short | Adaptive identification of critical nodes for fault‐on voltage support in islanded microgrids |
| title_sort | adaptive identification of critical nodes for fault on voltage support in islanded microgrids |
| topic | microgrids power system identification |
| url | https://doi.org/10.1049/rpg2.13033 |
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