Overview

Power system quality and its reliability continue to grow in importance as consumers become more sensitive and the cost of power quality problems increases. Identification and classification of voltage and current disturbances in power systems is an important task in power system monitoring and protection. Detection and classification of power system disturbances based on visual inspection of waveforms by a human operator are laborious and erroneous. Existing automatic recognition methods need much improvement in terms of their versatility, reliability, and accuracy. Sophisticated systems for automatic classification of power quality disturbances are highly desired for both power suppliers and consumers. The objective of this research is to develop state of the art signal classification algorithms for classifying different types of power quality disturbances, based on the recent advances in signal processing and pattern classification techniques. This research presents a power quality monitoring system for classifying voltage and current waveform events that are related to a variety of power quality problems.

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