ResNest-SVM-based method for identifying single-phase ground faults in active distribution networks
Single-phase grounding fault is the most common fault type in the distribution network. An accurate and effective single-phase grounding fault identification method is a prerequisite for maintaining the safe and stable operation of the power grid. Most neutral points of the active distribution netwo...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2024.1501737/full |
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| author | Qingwen Lian Xiang Luo Dong Lin Caihua Lin Bingxi Chen Ziyi Guo |
| author_facet | Qingwen Lian Xiang Luo Dong Lin Caihua Lin Bingxi Chen Ziyi Guo |
| author_sort | Qingwen Lian |
| collection | DOAJ |
| description | Single-phase grounding fault is the most common fault type in the distribution network. An accurate and effective single-phase grounding fault identification method is a prerequisite for maintaining the safe and stable operation of the power grid. Most neutral points of the active distribution network are grounded through arc suppression coils. In the active distribution network, the power supply in the network changes from one to multiple, which may change the direction of the fault current. In this paper, the superposition theorem is used to analyze the difference in the boosting effect of different types of distributed generators (DG) on line mode current in the sequence network diagram when DG is connected upstream or downstream of the fault point. Secondly, the composition of the zero-mode transient current of the fault line is analyzed. A judgment method based on the superposition diagram of transient zero-sequence voltage and current is proposed. Then, this paper improves the ResNest network and modifies the classifier of the last fully connected layer to SVM. Finally, the model in PSCAD is used to simulate single-phase grounding faults to obtain the training set and validation set. These datasets are used to train and test AlexNet, ResNet50, ResNeSt, and ResNeSt-SVM. The results show that under different fault points, transition resistances, DG access upstream and downstream of the fault point, and different fault initial phase angles, the ResNest-SVM model method can accurately identify the fault line and has better anti-noise ability than the other three network structures. |
| format | Article |
| id | doaj-art-88f5d5cfb6b84dcd898f85839570c0bc |
| institution | OA Journals |
| issn | 2296-598X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj-art-88f5d5cfb6b84dcd898f85839570c0bc2025-08-20T02:07:03ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2024-11-011210.3389/fenrg.2024.15017371501737ResNest-SVM-based method for identifying single-phase ground faults in active distribution networksQingwen Lian0Xiang Luo1Dong Lin2Caihua Lin3Bingxi Chen4Ziyi Guo5State Grid Fujian Electric Power Corporation, Gulou, Fujian, ChinaState Grid Fujian Electric Power Co., LTD., Electrical Power Research Institution, Fuzhou, ChinaState Grid Fujian Electric Power Co., LTD., Electrical Power Research Institution, Fuzhou, ChinaState Grid Fujian Electric Power Co., LTD., Electrical Power Research Institution, Fuzhou, ChinaFujian Zhongshi Institute Electric Power Adjustment Test Co., LTD., Fuzhou, ChinaState Grid Fujian Electric Power Co., LTD., Electrical Power Research Institution, Fuzhou, ChinaSingle-phase grounding fault is the most common fault type in the distribution network. An accurate and effective single-phase grounding fault identification method is a prerequisite for maintaining the safe and stable operation of the power grid. Most neutral points of the active distribution network are grounded through arc suppression coils. In the active distribution network, the power supply in the network changes from one to multiple, which may change the direction of the fault current. In this paper, the superposition theorem is used to analyze the difference in the boosting effect of different types of distributed generators (DG) on line mode current in the sequence network diagram when DG is connected upstream or downstream of the fault point. Secondly, the composition of the zero-mode transient current of the fault line is analyzed. A judgment method based on the superposition diagram of transient zero-sequence voltage and current is proposed. Then, this paper improves the ResNest network and modifies the classifier of the last fully connected layer to SVM. Finally, the model in PSCAD is used to simulate single-phase grounding faults to obtain the training set and validation set. These datasets are used to train and test AlexNet, ResNet50, ResNeSt, and ResNeSt-SVM. The results show that under different fault points, transition resistances, DG access upstream and downstream of the fault point, and different fault initial phase angles, the ResNest-SVM model method can accurately identify the fault line and has better anti-noise ability than the other three network structures.https://www.frontiersin.org/articles/10.3389/fenrg.2024.1501737/fullactive distribution networkzero-mode transientsingle-phase grounding faultdistributed line selectionneural networkResNest-SVM |
| spellingShingle | Qingwen Lian Xiang Luo Dong Lin Caihua Lin Bingxi Chen Ziyi Guo ResNest-SVM-based method for identifying single-phase ground faults in active distribution networks Frontiers in Energy Research active distribution network zero-mode transient single-phase grounding fault distributed line selection neural network ResNest-SVM |
| title | ResNest-SVM-based method for identifying single-phase ground faults in active distribution networks |
| title_full | ResNest-SVM-based method for identifying single-phase ground faults in active distribution networks |
| title_fullStr | ResNest-SVM-based method for identifying single-phase ground faults in active distribution networks |
| title_full_unstemmed | ResNest-SVM-based method for identifying single-phase ground faults in active distribution networks |
| title_short | ResNest-SVM-based method for identifying single-phase ground faults in active distribution networks |
| title_sort | resnest svm based method for identifying single phase ground faults in active distribution networks |
| topic | active distribution network zero-mode transient single-phase grounding fault distributed line selection neural network ResNest-SVM |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2024.1501737/full |
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