Classification of power quality disturbances using Stockwell Transform and Back Propagation algorithm

摘要

Nowadays detecting power quality issues are major concern in power system. This paper aims to develop a real time solution for detecting the Power Quality events. By providing a voltage Data Acquisition Card, NI DAQ-9225, fourteen Power Quality events are acquired by the Virtual Instrument software package. The acquired data in time domain is transformed into frequency domain by Stockwell Transform. The features extracted from the transformation are then fed into the Back Propagation Neural Network for training which aids in automatic classification of Power Quality Events. A combination of Stockwell Transform technique and Neural Networks are employed to detect and characterize the Power Quality Disturbances. The result obtained shows the effectiveness of the Stockwell Transform based Back Propagation algorithm in classifying the Power Quality Disturbances and is validated through Power Quality Analyzer.