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Remote monitoring system for real time detection and classification of transmission line faults in a power grid using PMU measurements

机译:使用PMU测量的电网实时检测和传输线故障分类的远程监控系统

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摘要

Abstract Remote monitoring of transmission lines of a power system is significant for improved reliability and stability during fault conditions and protection system breakdowns. This paper proposes a smart backup monitoring system for detecting and classifying the type of transmission line fault occurred in a power grid. In contradiction to conventional methods, transmission line fault occurred at any locality within power grid can be identified and classified using measurements from phasor measurement unit (PMU) at one of the generator buses. This minimal requirement makes the proposed methodology ideal for providing backup protection. Spectral analysis of equivalent power factor angle (EPFA) variation has been adopted for detecting the occurrence of fault that occurred anywhere in the grid. Classification of the type of fault occurred is achieved from the spectral coefficients with the aid of artificial intelligence. The proposed system can considerably assist system protection center (SPC) in fault localization and to restore the line at the earliest. Effectiveness of proposed system has been validated using case studies conducted on standard power system networks.
机译:摘要电力系统传输线的远程监控对于改善故障条件和保护系统故障期间的可靠性和稳定性很大。本文提出了一种智能备份监控系统,用于检测和分类电网发生的传输线故障类型。为了传统方法,可以使用来自发电机总线之一的游戏测量单元(PMU)的测量来识别和分类在电网内的任何局部性的传输线故障。这种最小要求使得提出的方法理想是提供备份保护。已经采用了等效功率因数角度(EPFA)变化的光谱分析来检测网格中的任何地方发生的故障发生。借助人工智能,从光谱系数实现了发生故障类型的分类。所提出的系统可以在故障本地化中辅助系统保护中心(SPC),并最早恢复该线路。使用标准电力系统网络进行的案例研究验证了所提出的系统的有效性。

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