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Time-Frequency Analysis based Approach to Islanding Detection in Micro-grid System

机译:基于时频分析的微电网孤岛检测方法

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摘要

This paper presents a novel technique based on time-frequency analysis to detect the islanding conditions in distribution network with the presence of multiple distributed generations (DGs). Various islanding and non-islanding fault conditions such as capacitor switching, load rejection and line to line fault etc., are analyzed through negative sequence decomposition technique. Feature extraction has been carried out by two time-frequency analysis techniques based on wavelet transform (WT) and S-Transform (ST). For the detection of various disturbances the energy and standard deviation (SD) features of signals are estimated by wavelet transform coefficient and S-transform matrix. Furthermore, based on the estimated features the artificial neural network (ANN) and support vector machine (SVM) are used as a classifier to classify the islanding and non-islanding events. For showing the effectiveness of the proposed technique to delect islanding conditions under a wide range of operating environment, some simulated results are presented.
机译:本文提出了一种基于时频分析的新技术,用于在存在多个分布式发电(DG)的情况下检测配电网中的孤岛状态。通过负序分解技术分析了各种孤岛和非孤岛的故障情况,例如电容器切换,负载抑制和线对线故障等。特征提取是通过基于小波变换(WT)和S变换(ST)的两种时频分析技术进行的。为了检测各种干扰,通过小波变换系数和S变换矩阵来估计信号的能量和标准差(SD)特征。此外,基于估计的特征,人工神经网络(ANN)和支持向量机(SVM)被用作分类器,以对孤岛和非孤岛事件进行分类。为了显示所提出的技术在大范围的操作环境下改善孤岛条件的有效性,提出了一些仿真结果。

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