This paper presents a fuzzy-expert system for automated detection and classification of power quality disturbances. The types of concerned disturbances include voltage sags, swells, interruptions, switching transients, impulses, flickers, harmonics, and notches. It is assumed that the analyzed waveforms are available in sampled form. Fourier transform and wavelet analysis are utilized to obtain unique features for the waveforms. A fuzzy-expert system is designed for making a decision regarding the type of the disturbance. Simulation studies are presented to verify the accuracy of the proposed approach. Comparison studies between an Artificial Neural Network based classification technique and the proposed approach are also reported to show the advantages of the proposed approach.
|Number of pages||7|
|Journal||International Journal of Electrical Power and Energy System|
|State||Published - Mar 2004|
Copyright 2008 Elsevier B.V., All rights reserved.
- Artificial neural network
- Fuzzy-expert system
- Power quality disturbance classification
- Wavelet analysis
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering