Power quality monitoring using an integrated Fourier linear combiner and fuzzy expert system

The paper presents a new approach for the classification of transient distu rbance waveforms in a power system by using a Fourier linear combiner and a fuzzy expert system. The measured voltage or current waveforms at a distri bution bus are passed through a Fourier linear combiner block to provide pe ak or root mean square (RMS) amplitude and phase of the fundamental compone nt at every sampling instant. The peak or RMS amplitude and computed slope of the waveforms are then passed on to a diagnostic module that computes th e truth value of the signal combination and determines the class to which t he waveform belongs. Computer simulated tests are carried out using EMTP pr ograms to obtain the disturbance waveform classification with the help of a new hybrid approach which is much simpler than the recently postulated neu ral network and wavelet based techniques. The classification is found to be robust and yields accurate results in most cases with the least amount of computational burden. (C) 1999 Elsevier Science Ltd. All rights reserved.