PDF Печать E-mail

DOI: https://doi.org/10.15407/techned2017.05.067


Journal Tekhnichna elektrodynamika
Publisher Institute of Electrodynamics National Academy of Sciences of Ukraine
ISSN 1607-7970 (print), 2218-1903 (online)
Issue No 5, 2017 (September/October)
Pages 67 – 75


O.F. Butkevych1,2, V.V. Chyzhevskyi2
1 – Institute of Electrodynamics National Academy of Sciences of Ukraine,
pr. Peremohy, 56, Kyiv, 03057, Ukraine,
e-mail: Этот e-mail адрес защищен от спам-ботов, для его просмотра у Вас должен быть включен Javascript
2 – National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”,
pr. Peremohy, 37, Kyiv, 03056, Ukraine



The article presents comparative identification results of low-frequency components of the signals in the cases of using their both effective and instantaneous values. It is shown that using of instantaneous values of power system operational condition parameters measured by phasor measurement units will increase a detection reliability of low-frequency modes of electromechanical oscillations, however, such use in real time will require a high processor speed. Therefore, for reliable detection of low-frequency modes it is more expedient to increase the observation window’s width and to use the effective values of the power system operational condition parameters. References 10, figures 6, tables 3.


Key words: power system, low-frequency modes, electromechanical oscillations, data sampling, instantaneous values.


Received:     28.04.2017
Accepted:     30.06.2017
Published:   17.08.2017



1. Butkevych О.F., Chyzhevskyi V.V. Evaluation and decrease in real time of risk of oscillatory loss of Interconnected Power System stability. Tekhnichna Elektrodynamika. 2015. No 6. Pp. 46–52. (Ukr)
2. Butkevych О.F., Chyzhevskyi V.V. An influence of digital filtering of signals at analysis results of low-frequency electromechanical oscillations in interconnected power systems. Tekhnichna Elektrodynamika. 2016. No 6. Pp. 54–59. (Ukr)
3. Agüero J.L., Molina R.D., Barbero J.C, Issouribehere F. Poorly damped electromechanical oscillation in the 345 kV interconnection between Argentina and Chile. Identification based on sliding Prony analysis. 2016 CIGRE Session Proceedings. – Paris, CIGRE Session from 21 till 26 August 2016.  Paper C2-205.  9 p.
4. Gong Y., Guzmán А. Synchrophasor-Based Online Modal Analysis to Mitigate Power System Interarea Oscillation. Journal of Reliable Power. 2011. Vol. 2. No 2. Pр. 42–47.
5. Identification of Electromechanical Modes in Power Systems. IEEE Task Force Report. Special Publication TP462. June 2012 / IEEE Power & Energy Society. IEEE 2012. The Institute of Electrical and Electronic Engineers, Inc. 2012. 282 p.
6. Jakpattanajit C., Hoonchareon N., Yokoyama A. On-line Estimation of Power System Low Frequency Oscillatory Modes in Large Power Systems. Journal of International Council on Electrical Engineering. 2011. Vol. 1. No 3. Pp. 352–358.
7. Lauria D., Pisani C. On Hilbert transform methods for low frequency oscillations detection. IET Generation, Transmission & Distribution. 2014. Vol. 8. Iss. 6. Pр. 1061–1074.
8. Lin T.-H., Soo V.-W. Pruning Fuzzy ARTMAP Using the Minimum Description Length Principle in Learning from Clinical Databases. Ninth IEEE International Conference on Tools with Artificial Intelligence. Proceedings. 1997, November 3-8, Newport Beach, California. Pp. 396–403.
9. Lu C., Shi B., Wu X., and Sun H. Advancing China’s Smart Grid. IEEE power & energy magazine.  2015. Vol. 13. No 5. Pр. 60–71.
10. Patil V. S., Jambhulkar P.P., Kamble V.P. Real-time Identification of Electromechanical Modes using Controlled Window-size Multi-Prony Analysis. International Journal of Engineering Research & Technology. 2014. Vol. 3. Iss. 4. Pр. 1627–1634.