Coiflet wavelet transform applied to inspect power system disturbance-generated signals

An application of Coiflet wavelet transform for the study of power system disturbance-generated signals is proposed. Because the wavelet transform possesses the time-frequency localization characteristics, the time and frequency information of a waveform can be integrally presented. Therefore, this approach can be more efficient in monitoring time-varying disturbances when compared with those Fourier transform-based methods. Moreover, when compared with the Morlet wavelet transform, the merits of easier implementation presented by Coiflet transform method as a discrete form further solidify the practicality for electric power quality applications. This approach has been validated through various test scenarios, including oscillatory transients, voltage sag, voltage swell, momentary interruption, and flat-top. Test results demonstrated the feasibility of the method for the applications considered.

[1]  A.P.S. Meliopoulos,et al.  Directions of research on electric power quality , 1993 .

[2]  M. D. Cox,et al.  Discrete wavelet analysis of power system transients , 1996 .

[3]  D. Vandorpe,et al.  Range image processing based on multiresolution analysis , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[4]  Ward Jewell,et al.  Effects of harmonics on equipment , 1993 .

[5]  I. Daubechies Orthonormal bases of compactly supported wavelets II: variations on a theme , 1993 .

[6]  Dong Wei,et al.  Representations of stochastic processes using coiflet-type wavelets , 2000, Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496).

[7]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[8]  Chul-Hwan Kim,et al.  A noise suppression method for improvement of power quality using wavelet transforms , 1999, 1999 IEEE Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.99CH36364).

[9]  R. Coifman,et al.  Fast wavelet transforms and numerical algorithms I , 1991 .

[10]  P. Pillay,et al.  Application of wavelets to model short-term power system disturbances , 1996 .

[11]  Jan E. Odegard,et al.  Nearly symmetric orthogonal wavelets with non-integer DC group delay , 1996, 1996 IEEE Digital Signal Processing Workshop Proceedings.

[12]  I. Daubechies Orthonormal bases of compactly supported wavelets , 1988 .

[13]  A. Grossmann,et al.  DECOMPOSITION OF HARDY FUNCTIONS INTO SQUARE INTEGRABLE WAVELETS OF CONSTANT SHAPE , 1984 .

[14]  S. J. Huang,et al.  Application of Gabor transform technique to supervise power system transient harmonics , 1996 .

[15]  Jan E. Odegard,et al.  Coiflet systems and zero moments , 1998, IEEE Trans. Signal Process..

[16]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  D. D. Sabin,et al.  Quality enhances reliability [power supplies] , 1996 .

[18]  O. Rioul,et al.  Wavelets and signal processing , 1991, IEEE Signal Processing Magazine.

[19]  M. Grgic,et al.  Filter comparison in wavelet transform of still images , 1999, ISIE '99. Proceedings of the IEEE International Symposium on Industrial Electronics (Cat. No.99TH8465).

[20]  J. Morlet,et al.  Wave propagation and sampling theory—Part II: Sampling theory and complex waves , 1982 .

[21]  Truong Q. Nguyen,et al.  Wavelets and filter banks , 1996 .

[22]  J. Morlet,et al.  Wave propagation and sampling theory—Part I: Complex signal and scattering in multilayered media , 1982 .

[23]  Shyh-Jier Huang,et al.  Application of Morlet wavelets to supervise power system disturbances , 1999 .

[24]  Shyh-Jier Huang,et al.  High-impedance fault detection utilizing a Morlet wavelet transform approach , 1999 .