Abstract
This work presents the detection results involving two common electrical disturbances: sags and swells. Variance, skewness and kurtosis have been used to improve statistical characterization. The measurement procedure is funded in the tuning of the signal under test via a sliding window over which computation is developed. Locking is possible because these power quality disturbances keep the frequency of the power line. Statistical features reveal the inherent properties of the signals: amplitude, frequency and symmetry. The paper primarily examines a number of synthetics in order to extract the theoretical statistical features. Then the algorithm is corroborated using real-life signals, obtaining an accuracy of 83%. This stage is part of the design of an instrument for the measurement of the power quality.
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References
Bollen, M.H.J., Gu, I.Y.H., Axelberg, P.G.V., Styvaktakis, E.: Classification of underlying causes of power quality disturbances: Deterministic versus statisticalmethods. EURASIP Journal on Advances in Signal Processing 2007, 1–17 (2007)
de la Rosa, J.J.G., Moreno Muñoz, A., Gallego, A., Piotrkowski, R., Castro, E.: Higher-order characterization of power quality transients and their classification using competitive layers. Measurement 42, 478–484 (2009)
Ribeiro, M.V., Marques, C.A.G., Duque, C.A., Cerqueira, A.S., Pereira, J.L.R.: Detection of disturbances in voltage signals for power quality analysis using hos. EURASIP Journal on Advances in Signal Processing 2007, 1–13 (2007)
de la Rosa, J.J.G., Moreno, A., Puntonet, C.G.: A practical review on higher-order statistics interpretation. application to electrical transients characterization. Dynamics of continous discrete and Impulsive Systems-Series B: Applications and Algorithms 14, 1577–1582 (2007)
de la Rosa, J.J.G., Lloret, I., Puntonet, C.G., Piotrkowski, R., Moreno, A.: Higher-order spectra measurement techniques of termite emissions. a characterization framework. Measurement 41, 105–118 (2008) (online, October 13, 2006)
de la Rosa, J.J.G., Piotrkowski, R., Ruzzante, J.: Third-order spectral characterization of acoustic emission signals in ring-type samples from steel pipes for the oil industry. Mechanical Systems and Signal Processing 21, 1917–1926 (2007) (online, October 10, 2006)
Bollen, M.H.J., Styvaktakis, E., Gu, I.Y.-H.: Categorization and analysis of power system transients. IEEE Transactions on Power Delivery 20(3), 105–118 (2005)
Moreno, A., et al.: Mitigation Technologies in a Distributed Environment, 1st edn. Power Systems. Springer (2007)
IEEE: IEEE Recommended practice for monitoring electric power quality. Technical Report IEEE Std. 1159-1995. The Institute of Electrical and Electronics Engineers, Inc. (1995)
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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González de la Rosa, J.J. et al. (2012). Power Quality Analysis Using Higher-Order Statistical Estimators: Characterization of Electrical Sags and Swells. In: Liñán Reyes, M., Flores Arias, J.M., González de la Rosa, J.J., Langer, J., Bellido Outeiriño, F.J., Moreno-Munñoz, A. (eds) IT Revolutions. IT Revolutions 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 82. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32304-1_3
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DOI: https://doi.org/10.1007/978-3-642-32304-1_3
Publisher Name: Springer, Berlin, Heidelberg
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