ICA-based method for power quality disturbance detection

This paper presents a method based on Independent Component Analysis (ICA) for power quality disturbance detection. The proposed method focuses on the detection of sag, swell, sinusoidal voltage fluctuation, fundamental frequency variations and harmonics in electric power signals. Suitable results were achieved from simulated signals in which the beginning and ending time of these disturbances were accurately detected. The results showed the proposed method can be used for disturbance segmentation as part of a power quality monitoring system.

[1]  Erkki Oja,et al.  Independent Component Analysis , 2001 .

[2]  Ahmet Teke,et al.  A novel wavelet transform based voltage sag/swell detection algorithm , 2015 .

[3]  J. Arrillaga,et al.  Power quality following deregulation , 2000, Proceedings of the IEEE.

[4]  Irene Yu-Hua Gu,et al.  Signal processing of power quality disturbances , 2006 .

[5]  Paulo F. Ribeiro,et al.  Extracting the transient events from power system signals by independent component analysis , 2016 .

[6]  Walid Morsi,et al.  A new perspective for the IEEE standard 1459-2000 via stationary wavelet transform in the presence of nonstationary power quality disturbance , 2009, 2009 IEEE Power & Energy Society General Meeting.

[7]  Jidong Wang,et al.  Detection of power quality disturbance based on binary wavelet transform , 2007, TENCON 2007 - 2007 IEEE Region 10 Conference.

[8]  Lang Tong,et al.  Indeterminacy and identifiability of blind identification , 1991 .

[9]  José Seixas,et al.  Method based on independent component analysis for harmonic extraction from power system signals , 2015 .

[10]  Eric Moulines,et al.  A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[11]  P.A. Crossley,et al.  Bridging the gap between signal and power , 2009, IEEE Signal Processing Magazine.

[12]  J. Cardoso,et al.  Blind beamforming for non-gaussian signals , 1993 .

[13]  M.E. Davies,et al.  Source separation using single channel ICA , 2007, Signal Process..

[14]  R. Alvarez,et al.  Detection of Sags, Swells, and Interruptions Using the Digital RMS Method and Kalman Filter with Fast Response , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[15]  Ying Wang,et al.  Calculation of the Phase-Angle-Jump for Voltage Dips in Three-Phase Systems , 2015, IEEE Transactions on Power Delivery.

[16]  Wei-Jen Lee,et al.  Robust algorithms for high speed voltage sags and swells detection , 2002, IEEE Technical Conference Industrial and Commerical Power Systems.

[17]  José Seixas,et al.  A method based on independent component analysis for single and multiple power quality disturbance classification , 2015 .

[18]  Erkki Oja,et al.  The FastICA Algorithm Revisited: Convergence Analysis , 2006, IEEE Transactions on Neural Networks.

[19]  K. Uma Rao,et al.  A modified simple algorithm for detection of voltage sags and swells in practical loads , 2009, 2009 International Conference on Power Systems.

[20]  R.B. Godoy,et al.  Multiple signal processing techniques based power quality disturbance detection, classification, and diagnostic software , 2007, 2007 9th International Conference on Electrical Power Quality and Utilisation.