Abstract
This study demonstrates detection and classification of power quality (PQ) events utilising Volterra series for feature extraction and interval type-2 fuzzy logic system (IT2FLS) for classification of PQ events. The Volterra series represented in the form of infinite power series with memory which provides a convenient and strong platform for representation of input–output relationship for non-linear systems. IT2FLS uses the concept of membership functions to perform classification of multiple PQ events. When supply power is distorted by additive noise where signal-to-noise ratio is low and uncertain, IT2FLS has shown improved performance over support vector machine, neural networks (NNs), probabilistic NN and type-1 fuzzy logic system classifiers, which makes an IT2FLS favourable for real-time applications.
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