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A hybrid SVM-TT transform-based method for fault location in hybrid transmission lines with underground cables

机译:基于混合SVM-TT变换的地下电缆混合输电线路故障定位方法

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摘要

This paper proposes a hybrid fault location technique in an overhead line that contains an underground cable. Time-time (TT)- and S-transforms are used to extract information from the transient voltage signals measured at a single end. This information is used to train a support vector machine (SVM) which determines whether the fault occurs in the first or second half of the underground cable or overhead line. To enhance the classification accuracy, the SVM parameters are optimized using the particle swarm optimization (PSO). After the identification, the fault is located using Bewley's lattice diagram and the transformed voltage signal. The performance of the proposed method is assessed under various parameters such as fault type, resistance, inception angle, and location. Simulation results validate the high accuracy of the proposed method in identifying the faulty section and locating the fault. Also, it is shown that the proposed technique outperforms other methods in the literature.
机译:本文提出了一种包含地下电缆的架空线混合故障定位技术。时间-时间(TT)和S变换用于从单端测量的瞬态电压信号中提取信息。该信息用于训练支持向量机(SVM),该向量机确定故障是在地下电缆还是架空线的前半部分或后半部分发生。为了提高分类精度,使用粒子群优化(PSO)对SVM参数进行了优化。识别后,使用Bewley的晶格图和变换后的电压信号来定位故障。在各种参数(例如故障类型,电阻,起始角度和位置)下评估所提出方法的性能。仿真结果验证了该方法在故障区域识别和故障定位中的准确性。而且,表明所提出的技术优于文献中的其他方法。

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