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The Swing-Blocking Methods for Digital Distance Protection Based on Wavelet Packet Transform and Support Vector Machine

机译:基于小波包变换和支持向量机的数字距离保护的摆动阻断方法

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This paper presents a method for power swing and fault diagnosis of power system based on Wavelet Packet Transform(WPT) and Support Vector Machine (SVM) classifier. The method adopts Least Square Support Vector Machine (LS-SVM) classifier to identify the power swing and fault types. The power swing blocking elements are based on monitoring the rate of change of wavelet packet energy and wavelet packet entropy of voltage and current signal, the positive current and zero sequence component. The process of training the LS-SVM using a K-folded cross validation process for determining the values of parameter and parameter in RBF kernel parameters can minimize the classification error. The proposed method can successfully detect power swing and provide power swing blocking signal for accurate distance protection.
机译:提出了一种基于小波包变换(WPT)和支持向量机(SVM)分类器的电力系统电力波动和故障诊断方法。该方法采用最小二乘支持向量机(LS-SVM)分类器来识别功率摆幅和故障类型。功率摆幅阻塞元件基于监视小波包能量的变化率以及电压和电流信号,正电流和零序分量的小波包熵。使用K折叠交叉验证过程训练LS-SVM以确定RBF内核参数中的参数值和参数值的过程可以最大程度地减少分类错误。所提出的方法可以成功地检测出功率摆幅并提供功率摆幅阻塞信号,以实现精确的距离保护。

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