Detection and Classification of Power Quality Disturbancewaveform Using MRA Based Modified Wavelet Transfrom and Neural Networks

Author:

Chandrasekar Perumal,Kamaraj Vijayarajan

Abstract

Detection and Classification of Power Quality Disturbancewaveform Using MRA Based Modified Wavelet Transfrom and Neural Networks In this paper, the modified wavelet based artificial neural network (ANN) is implemented and tested for power signal disturbances. The power signal is decomposed by using modified wavelet transform and the classification is carried by using ANN. Discrete modified wavelet transforms based signal decomposition technique is integrated with the back propagation artificial neural network model is proposed. Varieties of power quality events including voltage sag, swell, momentary interruption, harmonics, transient oscillation and voltage fluctuation are used to test the performance of the proposed approach. The simulation is carried out by using MATLAB software. The simulation results show that the proposed scheme offers superior detection and classification compared to the conventional approaches.

Publisher

Walter de Gruyter GmbH

Subject

Electrical and Electronic Engineering

Reference13 articles.

1. Power Quality Detection and Classification UsingWavelet-Multiresolution Signal Decomposition;A. GAOUDA;IEEE Transactions on PowerDelivery,1999

2. Application of Multiresolution Signal Decomposition For Monitoring Short-Duration Variations in Distribution Systems;A. GAOUDA;IEEE Transactions on Power Delivery,2000

3. Application of Wavelets to Classify Power System Disturbances;S. HUANG;Electric Power System Research,1998

4. Application of Morlet Wavelets to Supervise Power System Disturbance;S. HUANG;IEEE Transactions on Power Delivery,1999

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