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Detecting transient voltage stability and voltage sag

机译:检测瞬态电压稳定性和电压骤降

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This paper presents method to discriminate between transient voltage stability and voltage sag. The discrete wavelet transform (WT) is a powerful tool in the analysis of the transient phenomena in power systems because of its ability to extract information in both the time and frequency domain. This paper introduces a technique for accurate discrimination by combining WTs with neural networks (NNs). The WT is first applied to decompose the signals into a series of detailed wavelet components. The wavelet components are calculated and then employed to train a NN. The simulated results presented clearly show that the proposed technique can accurately discriminate between transient voltage stability and voltage sag in power system protection.
机译:本文提出区分暂态电压稳定性和电压暂降的方法。离散小波变换(WT)是电力系统瞬态现象分析的强大工具,因为它具有在时域和频域中提取信息的能力。本文介绍了一种通过将WT与神经网络(NN)结合来进行准确判别的技术。首先应用WT将信号分解为一系列详细的小波分量。计算小波分量,然后将其用于训练NN。仿真结果清楚地表明,该技术可以准确地区分电力系统保护中的暂态电压稳定性和电压暂降。

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