电气传动2025，Vol.55Issue(4)：72-81,10.DOI:10.19457/j.1001-2095.dqcd25972
基于多源信息融合的输电线路故障诊断研究
Research on Fault Diagnosis of Transmission Line Based on Multi-source Information Fusion
摘要
Abstract
With the accelerated construction of new power systems,the scale and complexity of transmission systems are constantly increasing.Therefore,it is urgent to study transmission line fault diagnosis algorithms that utilize multi-source data as driving sources and meet requirements for accuracy and low time consumption.A multi-source information fusion transmission line fault diagnosis method based on the improved NRBO-XGBoost algorithm was proposed.Firstly,by analyzing the measured electrical quantities and action switch quantities on both sides of the line protection,the correlation features of time/frequency domain differential current and differential voltage,transient polarity,and action signals under internal and external fault scenarios were decoupled.Then,the decoupled multi-source fault feature vectors were input into the XGBoost serial learning algorithm,and the NRBO algorithm was introduced to globally optimize the training parameters of XGBoost.Finally,based on the identification output of the improved NRBO-XGBoost algorithm,a complete transmission line fault diagnosis model for internal and external faults was obtained.An IEEE-30 standard node transmission system model was constructed using PSCAD/EMTDC.Through testing in four typical scenarios,the results demonstrated that the proposed multi-source information fusion algorithm achieves a line fault diagnosis accuracy of 99%,meeting the required threshold.Additionally,it exhibits certain advantages in terms of diagnosis speed compared to traditional intelligent algorithms.关键词
输电线路/故障诊断/XGBoost算法/NRBO算法/多源信息融合Key words
transmission line/fault diagnosis/XGBoost algorithm/NRBO algorithm/multi-source information fusion分类
动力与电气工程引用本文复制引用
葛亚明,周陈斌,孟屹华,沈蛟骁,曹海欧,任旭超..基于多源信息融合的输电线路故障诊断研究[J].电气传动,2025,55(4):72-81,10.基金项目
国家电网有限公司科技项目(J2023145) （J2023145）
