Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation
In the state estimation of distribution systems, it is difficult to fully monitor numerous network devices, resulting in insufficient measurement data. Besides, frequent topology switching urgently requires efficient algorithms. Therefore, this paper proposed an effective weighted minimum absolute v...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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State Grid Energy Research Institute
2024-01-01
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| Series: | Zhongguo dianli |
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| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202307049 |
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| _version_ | 1850070365241344000 |
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| author | Guang MA Wen ZHU Huijie GU Huashi ZHAO Xiqi HE Shijie CHEN |
| author_facet | Guang MA Wen ZHU Huijie GU Huashi ZHAO Xiqi HE Shijie CHEN |
| author_sort | Guang MA |
| collection | DOAJ |
| description | In the state estimation of distribution systems, it is difficult to fully monitor numerous network devices, resulting in insufficient measurement data. Besides, frequent topology switching urgently requires efficient algorithms. Therefore, this paper proposed an effective weighted minimum absolute value state estimation method for distribution network topology identification. Firstly, the traditional weighted minimum absolute value state estimation method based on linear programming was improved to improve the calculation efficiency. Secondly, a weighted minimum absolute value state estimation method based on mixed integer linear programming was formed by adding supplementary variables and constraints to the reformulated weighted minimum absolute value state estimation method to adapt to the topology identification problem. The simulation results on four example systems validate the excellent performance of the proposed topology identification method in different amounts of real-time measurements, high pseudo measurement errors, measurements corrupted by bad data, and unknown branch state scenarios. |
| format | Article |
| id | doaj-art-d3602422e33a4b0186a393d6eb48a136 |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2024-01-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-d3602422e33a4b0186a393d6eb48a1362025-08-20T02:47:34ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492024-01-0157116717410.11930/j.issn.1004-9649.202307049zgdl-57-01-maguangTopology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State EstimationGuang MA0Wen ZHU1Huijie GU2Huashi ZHAO3Xiqi HE4Shijie CHEN5China Southern Power Grid Company Limited, Guangzhou 510770, ChinaChina Southern Power Grid Company Limited, Guangzhou 510770, ChinaChina Southern Power Grid Company Limited, Guangzhou 510770, ChinaChina Southern Power Grid Company Limited, Guangzhou 510770, ChinaChina Southern Power Grid Company Limited, Guangzhou 510770, ChinaDongfang Electronics Co., Ltd., Yantai 264000, ChinaIn the state estimation of distribution systems, it is difficult to fully monitor numerous network devices, resulting in insufficient measurement data. Besides, frequent topology switching urgently requires efficient algorithms. Therefore, this paper proposed an effective weighted minimum absolute value state estimation method for distribution network topology identification. Firstly, the traditional weighted minimum absolute value state estimation method based on linear programming was improved to improve the calculation efficiency. Secondly, a weighted minimum absolute value state estimation method based on mixed integer linear programming was formed by adding supplementary variables and constraints to the reformulated weighted minimum absolute value state estimation method to adapt to the topology identification problem. The simulation results on four example systems validate the excellent performance of the proposed topology identification method in different amounts of real-time measurements, high pseudo measurement errors, measurements corrupted by bad data, and unknown branch state scenarios.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202307049distribution systemstate estimationtopology identificationweighted minimum absolute valuemixed integer linear programming |
| spellingShingle | Guang MA Wen ZHU Huijie GU Huashi ZHAO Xiqi HE Shijie CHEN Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation Zhongguo dianli distribution system state estimation topology identification weighted minimum absolute value mixed integer linear programming |
| title | Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation |
| title_full | Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation |
| title_fullStr | Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation |
| title_full_unstemmed | Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation |
| title_short | Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation |
| title_sort | topology identification method for active distribution network based on weighted minimum absolute value state estimation |
| topic | distribution system state estimation topology identification weighted minimum absolute value mixed integer linear programming |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202307049 |
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