Discrimination between transient voltage stability and voltage sag

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.

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