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High Impedance Fault Localization Using Discrete Wavelet Transform for Single Line to Ground Fault

机译:单线接地故障的离散小波变换高阻抗故障定位

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This paper presents a new approach to determine the high impedance fault location in a distribution network using discrete wavelet transform (DWT). The technique comprises three stages which are fault impedance identification, faulty section localization and fault distance estimation. First, the transient voltage and current waveforms are analyzed using DWT to obtain the energy values of its coefficients. Then artificial neural network is utilized to predict the fault impedance value. Next, the database and trigonometry techniques are used to localize the faulty section and fault distance successively. The proposed method is used to detect single line to ground faults on a 38-node distribution simulated network created using the PSCAD/EMTDC software. The output waveforms are analyzed using MATLAB. The fault impedance and fault distance can be estimated with errors of less than 0.42 and 2.37%, respectively, while the faulty section can be determined within the 6th rank. The encouraging results show that the approach is capable of determining the fault impedance value, localizing the faulty section and estimating the fault distance under various fault inception angles, fault impedances and fault distances.
机译:本文提出了一种使用离散小波变换(DWT)确定配电网中高阻抗故障位置的新方法。该技术包括三个阶段:故障阻抗识别,故障区域定位和故障距离估计。首先,使用DWT分析瞬态电压和电流波形,以获得其系数的能量值。然后利用人工神经网络预测故障阻抗值。接下来,使用数据库和三角技术依次定位故障区域和故障距离。所提出的方法用于在使用PSCAD / EMTDC软件创建的38个节点的分布式仿真网络上检测单线接地故障。使用MATLAB分析输出波形。故障阻抗和故障距离的估计误差分别小于0.42和2.37%,而故障区间可以确定在6级以内。令人鼓舞的结果表明,该方法能够确定故障阻抗值,定位故障区域并估计各种故障起始角度,故障阻抗和故障距离下的故障距离。

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