Evaluation method of distribution network operation status based on local fuzzy measure in boundary region
Abstract With the increasing complexity of the distribution network, the proportion of abnormal data in the monitoring data of the distribution network and its daily work is extremely low. Traditional clustering analysis methods are difficult to effectively solve the imbalance problem. Therefore, th...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-11-01
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| Series: | Energy Informatics |
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| Online Access: | https://doi.org/10.1186/s42162-024-00432-1 |
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| _version_ | 1850107442402164736 |
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| author | Bing Yu Peng Xie Zhonglin Ding Letian Li Changan Chen Chunfeng Jing |
| author_facet | Bing Yu Peng Xie Zhonglin Ding Letian Li Changan Chen Chunfeng Jing |
| author_sort | Bing Yu |
| collection | DOAJ |
| description | Abstract With the increasing complexity of the distribution network, the proportion of abnormal data in the monitoring data of the distribution network and its daily work is extremely low. Traditional clustering analysis methods are difficult to effectively solve the imbalance problem. Therefore, this paper introduces the influence parameters that can adaptively adjust the cluster center of local samples in the boundary area, and improves the cluster center update formula, and proposes a method of distribution network operation state evaluation based on the local blur measurement of the boundary region. The research results found that the five evaluation indicators of the proposed algorithm were 112, 0, 2, 26, and 5, respectively, all of which were superior to the comparison algorithms. The research results showed that the cluster center update optimization method based on local fuzzy measure in boundary region could effectively reduce the negative impact of the edge region occupied by most clusters on its clustering effect, so that the cluster center was always in an ideal position. At the same time, the example results showed that the research method had a risk prediction of 0.91 for power outage networks, which was close to the real situation and had high accuracy. It can provide reference for the operation and maintenance work of power grid personnel, eliminate hidden dangers in advance, and ensure the safe operation of the power grid. |
| format | Article |
| id | doaj-art-3ccc5caf13bb488489504c75304aaae5 |
| institution | OA Journals |
| issn | 2520-8942 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Energy Informatics |
| spelling | doaj-art-3ccc5caf13bb488489504c75304aaae52025-08-20T02:38:35ZengSpringerOpenEnergy Informatics2520-89422024-11-017111810.1186/s42162-024-00432-1Evaluation method of distribution network operation status based on local fuzzy measure in boundary regionBing Yu0Peng Xie1Zhonglin Ding2Letian Li3Changan Chen4Chunfeng Jing5State Grid Xin Jiang Electronic Power CompanyState Grid Xin Jiang Electronic Power CompanyNARI Group CorporationNARI Group CorporationNARI Group CorporationNARI Group CorporationAbstract With the increasing complexity of the distribution network, the proportion of abnormal data in the monitoring data of the distribution network and its daily work is extremely low. Traditional clustering analysis methods are difficult to effectively solve the imbalance problem. Therefore, this paper introduces the influence parameters that can adaptively adjust the cluster center of local samples in the boundary area, and improves the cluster center update formula, and proposes a method of distribution network operation state evaluation based on the local blur measurement of the boundary region. The research results found that the five evaluation indicators of the proposed algorithm were 112, 0, 2, 26, and 5, respectively, all of which were superior to the comparison algorithms. The research results showed that the cluster center update optimization method based on local fuzzy measure in boundary region could effectively reduce the negative impact of the edge region occupied by most clusters on its clustering effect, so that the cluster center was always in an ideal position. At the same time, the example results showed that the research method had a risk prediction of 0.91 for power outage networks, which was close to the real situation and had high accuracy. It can provide reference for the operation and maintenance work of power grid personnel, eliminate hidden dangers in advance, and ensure the safe operation of the power grid.https://doi.org/10.1186/s42162-024-00432-1Boundary areaLocal fuzzyDistribution networkOut-off-balanceFault monitoring |
| spellingShingle | Bing Yu Peng Xie Zhonglin Ding Letian Li Changan Chen Chunfeng Jing Evaluation method of distribution network operation status based on local fuzzy measure in boundary region Energy Informatics Boundary area Local fuzzy Distribution network Out-off-balance Fault monitoring |
| title | Evaluation method of distribution network operation status based on local fuzzy measure in boundary region |
| title_full | Evaluation method of distribution network operation status based on local fuzzy measure in boundary region |
| title_fullStr | Evaluation method of distribution network operation status based on local fuzzy measure in boundary region |
| title_full_unstemmed | Evaluation method of distribution network operation status based on local fuzzy measure in boundary region |
| title_short | Evaluation method of distribution network operation status based on local fuzzy measure in boundary region |
| title_sort | evaluation method of distribution network operation status based on local fuzzy measure in boundary region |
| topic | Boundary area Local fuzzy Distribution network Out-off-balance Fault monitoring |
| url | https://doi.org/10.1186/s42162-024-00432-1 |
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