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Power quality (PQ) is becoming prevalent and of critical importance for power industry recently. The fast expansion in use of power electronics devices led to a wide diffusion of nonlinear, time-variant loads in the power distribution network, which cause massive serious power quality problems. The quantitative detection of two distortions of voltage waveform, i.e., voltage sag and voltage swell,...
To improve the precision of power quality disturbance detection and recognition in distributed power system, a novel method based on complex transform wavelet transform is presented. Due to the property that instantaneous amplitudes of voltages and currents as well as instantaneous phase differences can be obtained, the combined information with time and frequency localization properties are defined...
This paper presents a novel power quality disturbance detection and classification method of distribution power system based on complex wavelet transform (WT) and radial basis function (RBF) neural network. The complex supported orthogonal wavelets is employed to extract the feature information of disturbance signal, and finally proposed to explore several novel wavelet combined information (CI) to...
Power quality (PQ) has attracted considerable attention from both utilities and users due to the use of many types of sensitive electronic equipment. This paper proposed a novel approach for the PQ disturbances classification based on the wavelet network. Wavelet transform is utilized to extract feature vectors for various PQ disturbances based on the multi-resolution analysis (MRA). These feature...
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