Abstract

This manuscript presents a complex power quality (PQ) disturbances recognition algorithm using hybrid features of signals extracted using Stockwell transform and Hilbert transform. A power quality index is proposed with the help of various complex PQ disturbances are detected effectively. Peak magnitudes of this power quality index are taken as input for decision tree supported by rules to classify the complex PQ disturbances. This algorithm is robust to be incorporated in online PQ monitoring equipments. Effectiveness of proposed algorithm has been established for detecting and classifying the different nature of complex nature PQ disturbances. Study is carried out using MATLAB software.

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