Fault detection method for distribution network based on edge computing
In order to accurately and quickly detect the faults of distribution network and ensure the stable power supply, a distribution network fault detection method based on edge computing is proposed. The edge computing model is constructed through multiple fault detectors, cloud computing centers and te...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Harbin Jinhe Electrical Measurement & Instrumentation Magazine Publishing Co., Ltd.
2025-01-01
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| Series: | Diance yu yibiao |
| Subjects: | |
| Online Access: | http://www.emijournal.net/dcyyben/ch/reader/create_pdf.aspx?file_no=20220328003&flag=1&journal_id=dcyyben&year_id=2025 |
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| _version_ | 1850235706822098944 |
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| author | YANG Hao ZHAO Huan XUE Rong YU Yubin WEI Enwei HUANG Bing |
| author_facet | YANG Hao ZHAO Huan XUE Rong YU Yubin WEI Enwei HUANG Bing |
| author_sort | YANG Hao |
| collection | DOAJ |
| description | In order to accurately and quickly detect the faults of distribution network and ensure the stable power supply, a distribution network fault detection method based on edge computing is proposed. The edge computing model is constructed through multiple fault detectors, cloud computing centers and terminal equipment. Based on the edge side, combined with multi-dimensional S-transform fusion algorithm and phase modulus transformation matrix method, the relevant fault features of distribution network are extracted. According to the feature extraction results, the correlation matrix of each detection device branch and its element value conditions of the edge computing model are set after the fault information is corrected, the fault information matrix is constructed, and the fault on the line section is determined according to the value of this matrix element. Experimental results show that the distribution network fault detection method based on edge computing can effectively detect different kinds of faults, and the response time is less than 0.005 s, the detection accuracy is more than 95%, which meets the practical application requirements. |
| format | Article |
| id | doaj-art-e0b1f0e8f08f4bfbacf5eb5f759809e5 |
| institution | OA Journals |
| issn | 1001-1390 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | Harbin Jinhe Electrical Measurement & Instrumentation Magazine Publishing Co., Ltd. |
| record_format | Article |
| series | Diance yu yibiao |
| spelling | doaj-art-e0b1f0e8f08f4bfbacf5eb5f759809e52025-08-20T02:02:09ZzhoHarbin Jinhe Electrical Measurement & Instrumentation Magazine Publishing Co., Ltd.Diance yu yibiao1001-13902025-01-0162119119810.19753/j.issn1001-1390.2025.01.0231001-1390(2025)01-0191-08Fault detection method for distribution network based on edge computingYANG Hao0ZHAO Huan1XUE Rong2YU Yubin3WEI Enwei4HUANG Bing5Shenzhen Power Supply Co., Ltd., Shenzhen 510000, Guangdong, ChinaShenzhen Power Supply Co., Ltd., Shenzhen 510000, Guangdong, ChinaShenzhen Power Supply Co., Ltd., Shenzhen 510000, Guangdong, ChinaShenzhen Power Supply Co., Ltd., Shenzhen 510000, Guangdong, ChinaChina Southern Power Grid Shenzhen Digital Grid Research Institute Co., Ltd., Shenzhen 518000, Guangdong, ChinaChina Southern Power Grid Shenzhen Digital Grid Research Institute Co., Ltd., Shenzhen 518000, Guangdong, ChinaIn order to accurately and quickly detect the faults of distribution network and ensure the stable power supply, a distribution network fault detection method based on edge computing is proposed. The edge computing model is constructed through multiple fault detectors, cloud computing centers and terminal equipment. Based on the edge side, combined with multi-dimensional S-transform fusion algorithm and phase modulus transformation matrix method, the relevant fault features of distribution network are extracted. According to the feature extraction results, the correlation matrix of each detection device branch and its element value conditions of the edge computing model are set after the fault information is corrected, the fault information matrix is constructed, and the fault on the line section is determined according to the value of this matrix element. Experimental results show that the distribution network fault detection method based on edge computing can effectively detect different kinds of faults, and the response time is less than 0.005 s, the detection accuracy is more than 95%, which meets the practical application requirements.http://www.emijournal.net/dcyyben/ch/reader/create_pdf.aspx?file_no=20220328003&flag=1&journal_id=dcyyben&year_id=2025edge computingdistribution networkfault detectionedge nodeincidence matrix |
| spellingShingle | YANG Hao ZHAO Huan XUE Rong YU Yubin WEI Enwei HUANG Bing Fault detection method for distribution network based on edge computing Diance yu yibiao edge computing distribution network fault detection edge node incidence matrix |
| title | Fault detection method for distribution network based on edge computing |
| title_full | Fault detection method for distribution network based on edge computing |
| title_fullStr | Fault detection method for distribution network based on edge computing |
| title_full_unstemmed | Fault detection method for distribution network based on edge computing |
| title_short | Fault detection method for distribution network based on edge computing |
| title_sort | fault detection method for distribution network based on edge computing |
| topic | edge computing distribution network fault detection edge node incidence matrix |
| url | http://www.emijournal.net/dcyyben/ch/reader/create_pdf.aspx?file_no=20220328003&flag=1&journal_id=dcyyben&year_id=2025 |
| work_keys_str_mv | AT yanghao faultdetectionmethodfordistributionnetworkbasedonedgecomputing AT zhaohuan faultdetectionmethodfordistributionnetworkbasedonedgecomputing AT xuerong faultdetectionmethodfordistributionnetworkbasedonedgecomputing AT yuyubin faultdetectionmethodfordistributionnetworkbasedonedgecomputing AT weienwei faultdetectionmethodfordistributionnetworkbasedonedgecomputing AT huangbing faultdetectionmethodfordistributionnetworkbasedonedgecomputing |