Symmetrical pattern and PCA based framework for fault detection and classification in power systems

Q. Alsafasfeh, I. Abdel-Qader, A. Harb
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引用次数: 28

Abstract

An important attribute of an electrical power system is the continuity of service with a high level of reliability. This motivated many researchers to investigate power systems in an effort to improve reliability by focusing on fault detection and classification. In this work, a new electrical protective relaying framework to detect and classify any fault type in an electrical power system is presented. This work will use readings of the phase current only during the first (1/4)th of a cycle in an integrated method that combines symmetrical components technique with the principal component analysis (PCA) to declare, identify, and classify a fault. Furthermore, our approach also distinguishes a real fault from a transient one and can be used in either a transmission or a distribution system. Implementation results using PSCAD are also presented.
基于对称模式和主成分分析的电力系统故障检测与分类框架
电力系统的一个重要属性是服务的连续性和高水平的可靠性。这促使许多研究人员通过关注故障检测和分类来研究电力系统,努力提高可靠性。本文提出了一种新的继电保护框架,用于对电力系统中各种类型的故障进行检测和分类。这项工作将只在一个周期的第一个(1/4)个周期内使用相电流的读数,采用一种将对称分量技术与主成分分析(PCA)相结合的综合方法来声明、识别和分类故障。此外,我们的方法还可以区分真实故障和暂态故障,并可用于输电或配电系统。并给出了基于PSCAD的实现结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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