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Discrimination between transient voltage stability and voltage sag

机译:瞬态电压稳定性和电压凹陷之间的歧视

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The discrete wavelet transform 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 presents a technique for accurate discrimination between transient voltage stability and voltage sag by combining wavelet transforms with neural networks. The wavelet transform is firstly applied to decompose the signals into a series of detailed wavelet components. The wavelet components are calculated and then employed to train a neural network. 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:离散小波变换是在电力系统中的瞬态现象分析时的强大工具,因为它能够在时间和频域中提取信息。本文提出了一种技术,通过将小波变换与神经网络相结合,提供了一种用于瞬态电压稳定性和电压凹陷之间的精确判断。首先应用小波变换以将信号分解为一系列详细的小波分量。计算小波部件,然后采用用于训练神经网络。提出的模拟结果清楚地表明,所提出的技术可以精确地区分电力系统保护中的瞬态电压稳定性和电压凹陷。

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