基于神经网络的高阻抗故障保护检测新技术

M. Eissa, G. Sowilam, A. Sharaf
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引用次数: 29

摘要

本文介绍了神经网络技术在高阻抗故障模式识别中的应用。该继电器基于一种新颖的低频(三次和五次谐波特征诊断向量)。电流和电压作为特征提取信号用于故障识别。本文的重点是设计一种鲁棒的基于人工神经网络的继电保护装置,该装置可以对配电径向电力系统的高阻抗小电流故障进行检测。模拟了各种故障和系统条件,以评估所提出技术的可靠性和灵敏度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Protection Detection Technique for High Impedance Fault Using Neural Network
The paper presents the application of Neural Network technique as a pattern recognition to high impedance faults (HIFs). The relay is based on a novel low-frequency (3rd and 5th harmonic feature diagnostic vector). The currents and voltages are used as a featured extracted signals for fault discrimination. The focus of this paper is to design a robust ANN-based relay, which can determine the high impedance low current faults on distribution radial electrical systems. A variety of faults and system conditions have been simulated to evaluate the reliability and sensitivity of the proposed technique.
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