Abstract
Taking advantage of S-transforms (STs), this paper proposes a new method of detecting and classifying power-quality disturbances. The ST is unique in that it provides frequency-dependent resolution while maintaining a direct relationship with the Fourier spectrum. The features obtained from ST are distinct, understandable, and immune to noise. According to a rule-based decision tree, eight types of single power disturbance and two types of complex power disturbance are well recognized, and there is no need to use other complicated classifiers. The comparison between the wavelet-transform-based method and the ST-based method for power-quality disturbance recognition is also provided. The simulation results show that the proposed method is effective and immune against noise. The proposed method is feasible and promising for real applications
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