International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9, No.8 (2016), pp.355-380 http://dx.doi.org/10.14257/ijsip.2016.9.8.31 ISSN: 2005-4254 IJSIP Copyright ⓒ 2016 SERSC Extraction of Fundamental Component in Power Quality Application using Tunable-Q Wavelet Transform G.Ravi Shankar Reddy 1 and Rameshwar Rao 2 1 Dept.of ECE, CVR College of Engineering, Hyderabad, India 2 Ex-Vice Chancellor, JNT University, Hyderabad, India 1 ravigosula_ece39@yahoo.co.in, 2 rameshwar_rao@hotmail.com Abstract Application of a Tunable-Q Wavelet Transform based technique is proposed in this paper for the extraction of Fundamental frequency component in Power Quality Disturbances. The TQWT filters are designed to extract the fundamental frequency component from the complete voltage (or) current signal. This is achieved by tuning the Q-factor and redundancy of the wavelet by primarily investigating the presence of interharmonics near the fundamental frequency. To test the effectiveness of the proposed scheme, the system is verified with various Power Quality Disturbances as per IEEE standards encountered in power system are considered here. Keywords: Tunable-Q Wavelet Transform, Power Quality Disturbances, Fundamental frequency component, TQWT filters, Q-factor, redundancy 1. Introduction With society’s growing dependence on electrical devices, the danger of equipment malfunction due to Power-quality disturbances (PQDs) have become an issue of essential importance [1]. So, the PQ (Power Quality) is like an umbrella which covers the various disturbances of the voltage and the current such as the voltage sag, swell, harmonics and oscillatory transients etc., [2]. Today the PQ has become a very interesting cross-disciplinary topic, coupling power engineering and power electronics with digital signal processing, software engineering, networking and VLSI. Power quality is defined as any power problem manifested in voltage, current, or frequency deviations that result in failure or misoperation of customer equipment and system itself. In electrical energy systems, voltages and especially currents become very irregular due to the increasing popularity of power electronics and other non-linear loads [3-4]. In recent past, the researchers have applied different signal processing techniques in order to detect and identify the disturbances. The Fourier Transform (FT) is suitable to analyze stationary signals but not suitable for non-stationary signals such as the transient signals. The Short Time Fourier transform (STFT) overcomes time localization problem of FT.According to Panigrahi et.al., [4], Wavelet transform (WT) is more suitable than STFT as STFT possesses fixed window property. Transient signals are easily analyzed by WT due its multiresolution property. The time plays an important role in the power system operation. One of the important issues of PQ problem is the fast mitigation of the disturbances. Fast detection and localization of the disturbances promote the fast mitigation [5-6]. In other words; the fast detection of PQ disturbance is becoming an important factor [7] in deregulated market. In this paper TQWT based decomposition techniques are applied to extract the fundamental frequency component from the different types of power quality disturbances. The tunable Q-factor wavelet transform (TQWT) is a recently developed wavelet transform designed so that the Q-factor is easily and continuously adjustable. The Online Version Only. Book made by this file is ILLEGAL.