Detection of Disturbances in Voltage Signals for Power Quality Analysis Using HOS
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Research Article Detection of Disturbances in Voltage Signals for Power Quality Analysis Using HOS ´ V. Ribeiro,1 Cristiano Augusto G. Marques,1 Carlos A. Duque,1 Moises Augusto S. Cerqueira,1 and Jose´ Luiz R. Pereira2 1 Department 2 Department
of Electrical Circuit, Federal University of Juiz de Fora, 36 036 330 Juiz de Fora, MG, Brazil of Electrical Energy, Federal University of Juiz de Fora, 36 036 330 Juiz de Fora, MG, Brazil
Received 1 May 2006; Accepted 4 February 2007 Recommended by M. Reza Iravani This paper outlines a higher-order statistics (HOS)-based technique for detecting abnormal conditions in voltage signals. The main advantage introduced by the proposed technique refers to its capability to detect voltage disturbances and their start and end points in a frame whose length corresponds to, at least, N = 16 samples or 1/16 of the fundamental component if a sampling rate equal to fs = 256 × 60 Hz is considered. This feature allows the detection of disturbances in submultiples or multiples of one-cycle fundamental component if an appropriate sampling rate is considered. From the computational results, one can note that almost all abnormal and normal conditions are correctly detected if N = s256, 128, 64, 32, and 16 and the SNR is higher than 25 dB. In addition, the proposed technique is compared to a root mean square (rms)-based technique, which was recently developed to detect the presence of some voltage events as well as their sources in a frame whose length ranges from 1/8 up to one-cycle fundamental component. The numerical results reveal that the proposed technique shows an improved performance when applied not only to synthetic data, but also to real one. Copyright © 2007 Mois´es V. Ribeiro et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
The increasing pollution of power line signals and its impact on the quality of power delivery by electrical utilities to end users are pushing forward the development of signal processing tools to provide several functionalities, among them it is worth mentioning the following ones [1]: (i) disturbances detection, (ii) disturbances classification, (iii) disturbance sources identification, (iv) disturbance sources localization, (v) transients analysis, (vi) fundamental, harmonic, and interharmonic parameters estimations, (vii) disturbances compression, (viii) signal segmentation, and so forth. Regarding the power quality (PQ) monitoring needs, one can note that the detection of disturbances as well as their start and end points in electric signals is a very important issue to upcoming generation of PQ monitoring equipment. In fact, the detection technique has to present good performance under different sampling rates, frame lengths ranging from submultiples up to multiples of power frequency cycle and varying signal-to-noise ratio (SNR) conditions. Therefore, for those in
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