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Print ISSN: 1582-7445
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doi: 10.4316/AECE


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  4/2013 - 21

 HIGHLY CITED PAPER 

Software Tool for Real-Time Power Quality Analysis

MIRON, A. See more information about MIRON, A. on SCOPUS See more information about MIRON, A. on IEEExplore See more information about MIRON, A. on Web of Science, CHINDRIS, M. D. See more information about  CHINDRIS, M. D. on SCOPUS See more information about  CHINDRIS, M. D. on SCOPUS See more information about CHINDRIS, M. D. on Web of Science, CZIKER, A. C. See more information about CZIKER, A. C. on SCOPUS See more information about CZIKER, A. C. on SCOPUS See more information about CZIKER, A. C. on Web of Science
 
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Download PDF pdficon (923 KB) | Citation | Downloads: 1,102 | Views: 4,408

Author keywords
application software, fault detection, harmonic analysis, signal processing algorithms, time domain analysis

References keywords
power(35), analysis(13), wavelet(9), transform(9), quality(9), systems(8), harmonic(7), frequency(7), virtual(6), measurement(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-11-30
Volume 13, Issue 4, Year 2013, On page(s): 125 - 132
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.04021
Web of Science Accession Number: 000331461300021
SCOPUS ID: 84890235763

Abstract
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A software tool dedicated for the analysis of power signals containing harmonic and interharmonic components, unbalance, voltage dips and voltage swells is presented. The software tool is a virtual instrument, which uses innovative algorithms based on time and frequency domains analysis to process power signals. In order to detect the temporary disturbances, edge detection is proposed, whereas for the harmonic analysis Gaussian filter banks are implemented. Considering that a signal recovery algorithm is applied, the harmonic analysis can be made even if voltage dips or swells appear. The virtual instrument input data can be recorded or online signals; the last ones being get through a data acquisition board. The virtual instrument was tested using both virtually created and real signals from measurements performed in distribution networks. The paper contains a numeric example made on a synthetic digital signal and an analysis made in real-time.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef]


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[CrossRef] [Web of Science Times Cited 50]


[15] S. Nath, A. Dey, A. Y. Chakrabarti, "Detection of power quality disturbances using wavelet transform", World Academy of Science, Engineering and Technology 49, 2009, pp. 869 - 873.

[16] S. Chen, H. Y. Zhu, "Wavelet transform for processing power quality disturbances", EURASIP J. Advan. Signal Proces., Vol. 2007, article ID 47695.

[17] N. C. F. Tse, "Practical application of wavelet to power quality analysis", Power Engineering Society General Meeting, 24-28 June 2007, ISBN: 1-4244-1298-6, pp. 1-6.

[18] N. Ghaffarzadeh, B. Vahidi, "A New protection scheme for high impedance fault detection using wavelet packet transform", Advances in Electrical and Computer Engineering, Vol. 10, No. 3, 2010, pp. 17 - 20.
[CrossRef] [Full Text] [Web of Science Times Cited 9] [SCOPUS Times Cited 15]


[19] Z. Wang, Y. Zhang, J. Zhang, J. Ma, "Recent research progress in fault analysis of complex electric power systems", Advances in Electrical and Computer Engineering, Vol. 10, No. 1, 2010, pp. 28 - 33.
[CrossRef] [Full Text] [Web of Science Times Cited 19] [SCOPUS Times Cited 23]


[20] T. Zheng, E.B. Makram, A. A. Girgis, "Power system transient and harmonic studies using wavelet transform", IEEE Trans. Power Deliv., Vol.14, No.4, October 1999, pp. 1461 - 1468.
[CrossRef] [Web of Science Times Cited 73] [SCOPUS Times Cited 108]


[21] S.-J. Huang, C.-T. Hsieh, C. L. Huang, "Application of Morlet wavelets to supervise power system disturbances", IEEE Trans. Power Deliv., Vol.14, No.1, January 1999, pp. 235 - 243.
[CrossRef] [Web of Science Times Cited 114] [SCOPUS Times Cited 205]


[22] A. M. Gaouda, M. M. A. Salama, M. R. Sultan, A.Y. Chikhani, "Power quality detection and classification using wavelet-multiresolution signal decomposition", IEEE Trans. Power Deliv., Vol.14, No.4, October 1999, pp. 1469 - 1473.
[CrossRef] [Web of Science Times Cited 395] [SCOPUS Times Cited 549]


[23] A. Y. Chilukuri, P. K. Dash, K. P. Basu, "Time-frequency based pattern recognition technique for detection and classification of power quality disturbances", TENCON 2004, 2004 IEEE Region 10 Conference, Vol. 3, pp. 260 - 263.
[CrossRef]


[24] E. Styvaktakis, M. H. J. Bollen, I.Y.H. Gu, "Expert system for classification and analysis of power systems events", IEEE Trans. Power Deliv., Vol. 17, No. 2, April 2002, pp. 423 - 428.
[CrossRef] [Web of Science Times Cited 175] [SCOPUS Times Cited 244]


[25] A. Miron, M. Chindris, A. Cziker, "Identification of electromagnetic disturbances in modern power systems", Journal of Sustainable Energy, Vol. 3, No. 1, March 2012, pp. 55 - 61, ISSN: 2067-5534

[26] M. Caciotta, S. Giarnetti, F. Leccese, Z. Leonowicz, "Comparison between DFT, Adaptive window DFT and EDFT for power quality frequency spectrum analysis", Intern. Conf. Modern Elect. Power Syst. 2010, Wroclaw, Polond, paper 16.1.

[27] D. N. Gheorghe, M.D. Chindris, et.al, "Signal Analysis in polluted power networks", J. Sustain. Energ., Vol.1, No.1, March, 2010, paper 1.7.

[28] H. C. Lin, C.H. Chen, L.Y Liu, "Harmonics and interharmonics measurement using group-harmonic energy distribution minimizing algorithm", Engineering Leters, 19:3, EL_19_3_17, August 2011, pp. 1 - 6.

[29] J. S. Huang, M. Negnevitsky, D.T. Nguyen, "Wavelet transform based harmonic analysis", Australasian universities power engineering conference and IEAust electric energy conference, 26-29 September 1999, Darwin, pp. 152-156.

[30] S. Tuntisak, S. Premrudeepreechacharn, "Harmonic detection in distribution systems using wavelet transform and support vector machine", Proc. Conf. IEEE Power Tech. Lausanne, pp. 1540-1545, July 2007.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 14]


[31] C.D.P. Crovato, A.A. Susin, "Frequency dependent windowing for tracking harmonics and interharmonics in power systems. Survey and the recursive corrected phase wavelet transform", Annals of the VIII Brazilian Conf. Power Qual., CBQEE 2009, Blumenau, Brazil, paper 82.

[32] H. Quan, Y. Dai, "Harmonic and interharmonic signal analysis based on generalized S-transform", Chinese J. Electron., Vol. 19, No. 4, Oct. 2010, pp. 656 - 660.

[33] A. S. Yilmaz, A. Alkan, M. H. Asyali, "Applications of parametric spectral estimation methods on detection of power systems harmonics", Electric Power Syst. Research, No. 78(2008), pp. 683 - 693.
[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 56]


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[CrossRef] [Full Text] [Web of Science Times Cited 8] [SCOPUS Times Cited 11]


[35] R. H. McEachern, "Speech information extractor", US Patent 5.214.708, 25 May, 1993.

[36] F. J. Harris, "On the use of windows for harmonic analysis with the discrete Fourier transform", Proc. IEEE, Vol. 66, No.1, 1978, pp. 51

[37] S. O.Hing-Cheung, "On Linear Least squares Approach for Phase Estimation of Real Sinusoidal Signals", IEICE Trans. Fundamentals, Vol. E88-A, No. 12, December 2005.

[38] A. Cziker, A. Miron, M. Chindris, „Power quality indices for unbalance characterization in non-sinusoidal condition", 14th Intern. Research/Expert Conf. „Trends in the Development of Machinery and Associated Technology" TMT 2010, 11-18 September 2010, pp. 481-484.



References Weight

Web of Science® Citations for all references: 1,064 TCR
SCOPUS® Citations for all references: 1,537 TCR

Web of Science® Average Citations per reference: 27 ACR
SCOPUS® Average Citations per reference: 39 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-11-18 15:21 in 132 seconds.




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