Comparative study on power quality disturbance magnitude characterization

• Main Authors: Wang, Z.Q., Zhu, S.Z.
• Format: Conference Proceeding
• Language: English
• Subjects: Digital signal processing; Discrete wavelet transforms; Feature extraction; Monitoring; Power quality; Power system transients; Root mean square; Signal processing algorithms; Voltage fluctuations; Wavelet packets
• DOI: 10.1109/ICPST.2002.1053513

Power quality disturbances (PQD) are normally monitored by dedicated PQ devices. The devices capture disturbances' waveform in real-time. Magnitude is accepted as a significant index for detection, general classification and later assessment analysis. To choose a suitable way of magnitude characterization is a fundamental work of PQD measuring and monitoring. This study presents three different ways, RMS voltage, peak voltage and fundamental voltage component, to determine magnitude. The algorithms of the three approaches implemented in Matlab are introduced. The algorithms are FFT-based and wavelet transformation (WT) based. A voltage sag benchmark in a radial test system is used to verify and validate the study. The depth-duration characterization of voltage sags is illustrated. The most appropriate approach is suggested at the end of the paper according to the practical monitoring or measuring requirements. The research result is applied to a new PQ monitor with DSP infrastructure being developed by us. The proper window length selection and technique to avoid oscillation is also discussed in the rest of the paper. The information obtained from the magnitude characterization can be furthered to extract features for PQD detection and classification.