A dual‐tree complex wavelet transform‐based approach for recognition of power system transients. Issue 1 (15th January 2014)

• Record Type: Journal Article
• Authors: Chakraborty, Soumi; Chatterjee, Amitava; Goswami, Swapan Kumar
• Is Part Of: Expert systems. Volume 32:Issue 1(2015)
• Page Start: 132
• Page End: 140
• Publication Date: 2014-01-15
• Subjects: Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12066
• Languages: English
• ISSNs: 0266-4720

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>The present paper proposes a dual‐tree complex wavelet transform (DTCWT) based approach for recognition of power system transients. Several researchers, all over the world, have so far attempted to solve the problems of recognition of power system transients, hybridizing transform‐based techniques with popular computational intelligence based tools, for example, using wavelet transform and S‐transform for feature extraction, followed by artificial neural networks (ANN) or fuzzy logic‐based classifiers. The proposed method of hybridizing DTCWT‐based feature extraction with ANN‐based classification could efficiently detect several commonly occurring power quality (PQ) disturbance events. The PQ disturbance events considered include four different transient conditions, namely transients due to capacitor switching, transformer inrush currents, transients due to motor switching and transients due to short circuit faults. A detailed performance comparison with several contemporary, competing methods existing in the literatures for similar problems aptly demonstrates the suitability of the proposed method.</p> </abstract>