中国电力2026，Vol.59Issue(8)：39-48,10.DOI:10.11930/j.issn.1004-9649.202602007
基于加权覆盖率与多权重协同优化的接地网腐蚀诊断端口优选方法
Optimal port selection method for grounding grid corrosion diagnosis based on weighted coverage and multi-weight collaborative optimization
摘要
Abstract
Port selection plays a critical role in the corrosion diagnosis of grounding grids.However,the lack of scientific guidance for port selection has restricted the application of network-based corrosion diagnosis methods.To address this issue,this paper proposes an iterative optimization method for port selection based on weighted coverage and multi-weight collaborative optimization.The method firstly establishes a port scoring model using the sensitivity matrix to quantify port values from three aspects:information complementarity,information richness and numerical stability.An iterative optimization strategy is then adopted,which greedily selects ports while predicting the resistance of grounding grid branches,thereby enabling recursive correction of the sensitivity matrix and gradually screening out port combinations with high-quality information.Finally,simulation experiments conducted on a simulated grounding grid with 53 branches show that,compared with the unweighted greedy selection with the same 14 selected ports,the weighted greedy selection method reduces the mean absolute percentage error from 34.83%to 5.7%.It is verified that the proposed method can effectively optimize the measuring port selection and improve the accuracy of grounding grid corrosion diagnosis.The research conclusions can provide theoretical guidance for port selection in corrosion diagnosis of large grounding grids.关键词
接地网/端口迭代优选/支路端口灵敏度/多权重协同优化Key words
grounding grid/port iterative optimization/branch-port sensitivity/multi-weight collaborative optimization引用本文复制引用
黄亚飞,左佳午,王子豪,杨鑫,谭天,姜飞..基于加权覆盖率与多权重协同优化的接地网腐蚀诊断端口优选方法[J].中国电力,2026,59(8):39-48,10.基金项目
This work is supported by National Natural Science Foundation of China(Nos.52507163 and 52507023),Natural Science Foundation of Hunan Province(No.2026JJ60193),Natural Science Foundation of Changsha(No.kq2502124).国家自然科学基金资助项目(52507163,52507023) （Nos.52507163 and 52507023）
湖南省自然科学基金资助项目(2026JJ60193) （2026JJ60193）
长沙市自然科学基金资助项目(kq2502124). （kq2502124）
