Hybrid demodulation concept and harmonic analysis for single/multiple power quality events detection and classification

A novel real-time analysis of power quality (PQ) events has been presented using amplitude and frequency demodulation concepts. The earlier techniques were analyzing the few cycles of the power signal based upon wavelets, having the computational complexity of the order O(n2). In the proposed method, PQ events can be considered as similar to various modulating signal forms. In this paper, the concept of demodulation has been used to separate various single/multiple event patterns and MUSIC harmonics algorithm has been used to detect the presence of the various harmonics. These techniques have been well tested on transient, sag, swell harmonics and their combinations in real-time. Fuzzy classifiers have been used for the classification of PQ events from the knowledge base, obtained from amplitude demodulation, frequency demodulation and MUSIC harmonic algorithm. It is concluded from the confusion tables that the efficiency of single/multiple PQ events recognition of fuzzy product aggregation reasoning rule (FPARR) classifier is higher.

► A novel real-time analysis of power quality (PQ) events has been presented.
► Single PQ event have been separated using cross-correlation function.
► Amplitude and frequency demodulation analysis have been used for PQ events.
► MUSIC algorithm has been used for determining the dominant frequencies/Harmonics and the events have been classified using FPARR classifier.