A Comparative Study of Prony Based Method for Identification of Low-Frequency Oscillations in the Power System

A Comparative Study of Prony Based Method for Identification of Low-Frequency Oscillations in the Power System

© 2021 by IJETT Journal
Volume-69 Issue-8
Year of Publication : 2021
Authors : Abhinav Pathak, Ratnesh Gupta
DOI :  10.14445/22315381/IJETT-V69I8P221

How to Cite?

Abhinav Pathak, Ratnesh Gupta, "A Comparative Study of Prony Based Method for Identification of Low-Frequency Oscillations in the Power System," International Journal of Engineering Trends and Technology, vol. 69, no. 8, pp. 174-178, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I8P221

In a modern power system, low-frequency electromechanical oscillations get triggered due to many reasons like a sudden change in load; these oscillations may lead to power system instability if the oscillations are not damped, which may finally lead to the collapse of the system. Hence accurate and precise estimation of the parameters of low-frequency oscillation in a power system is of utmost importance. In this research paper, the performance of two Prony based methods is compared for identifying dominant low-frequency oscillations. The performance is compared in terms of attenuation factor and frequency of oscillation with different noise levels and sampling rates of the Phasor Measurement Unit (PMU) with the synthetic signal generated in MATLAB and realtime data obtained from Western Electricity Coordinating Council (WECC).

Attenuation factor, Low-frequency oscillations, Phasor Measurement Unit, Power System, Prony Method.

[1] M. Klein, G. J. Rogers, and P. Kundur., A fundamental study of inter-area oscillations in power systems, IEEE Trans. Power Syst., 6(3) (1991) 914–921. doi: 10.1109/59.119229.
[2] M. E. Aboul-Ela, A. A. Sallam, J. D. McCalley, and A. A. Fouad, Damping controller design for power system oscillations using global signals, IEEE Trans. Power Syst., 11(2) (1996) 767–773. doi: 10.1109/59.496152.
[3] A. Pathak and R. Gupta., Small Signal Stability of a Power System, Int. J. Recent Technol. Eng., 8(3) (2019) 2277–3878. doi: 10.35940/ijrte.C3970.098319.
[4] P. Kundur, Power System Stability, and Control. Tata Mc-Graw Hill, (1994).
[5] T. JIANG, L. BAI, G. LI, H. JIA, Q. HU, and H. YUAN, Estimating inter-area dominant oscillation mode in bulk power grid using multi-channel continuous wavelet transform, J. Mod. Power Syst. Clean Energy, 4(3) (2016) 394–405. doi: 10.1007/s40565-016-0203-x.
[6] P. Ray, Power system low-frequency oscillation mode estimation using wide-area measurement systems, Eng. Sci. Technol. an Int. J., 20(2) (2017) 598–615. doi: https://doi.org/10.1016/j.jestch.2016.11.019.
[7] J. G. Philip and T. Jain, Analysis of low-frequency oscillations in power system using EMO ESPRIT, Int. J. Electr. Power Energy Syst., 95 (2018) 499–506. doi: 10.1016/j.ijepes.2017.08.037.
[8] N. Zhou, Z. Huang, F. Tuffner, J. Pierre, and S. Jin, Automatic implementation of Prony analysis for electromechanical mode identification from phasor measurements, in IEEE PES General Meeting, (2010)1–8. doi: 10.1109/PES.2010.5590169.
[9] S. Rai, P. Tripathy, and S. K. Nayak, A robust TLS-ESPIRIT method using covariance approach for identification of lowfrequency oscillatory mode in power systems, in Eighteenth National Power Systems Conference (NPSC), (2014) 1–6. doi: 10.1109/NPSC.2014.7103887.
[10] S. Rai, D. Lalani, S. K. Nayak, T. Jacob, and P. Tripathy, Estimation of low-frequency modes in power system using robust modified Prony, IET Gener. Transm. Distrib., 10(6) (2016) 1401– 1409. doi: https://doi.org/10.1049/iet-gtd.2015.0663.
[11] J. F. Hauer, C. J. Demeure, and L. L. Scharf, Initial results in Prony analysis of power system response signals, IEEE Trans. Power Syst., 5(1) (1990) 80–89. doi: 10.1109/59.49090.
[12] J. W. Pierre, D. J. Trudnowski, and M. K. Donnelly, Initial results in electromechanical mode identification from ambient data, IEEE Trans. Power Syst., 12(3) (1997) 1245–1251. doi: 10.1109/59.630467.
[13] J. F. Hauer, Application of Prony analysis to the determination of modal content and equivalent models for measured power system response, IEEE Trans. Power Syst., 6(3) (1991) 1062–1068. doi: 10.1109/59.119247.
[14] D. P. Wadduwage, U. D. Annakkage, and K. Narendra, Identification of dominant low-frequency modes in ring-down oscillations using multiple Prony models, IET Gener. Transm. Distrib., 9(15) (2015) 2206–2214,. doi: https://doi.org/10.1049/ietgtd. 2014.0947.
[15] P. Tripathy, S. C. Srivastava, and S. N. Singh., A Modified TLSESPRIT- Based Method for Low-Frequency Mode Identification in Power Systems Utilizing Synchrophasor Measurements, IEEE Trans. Power Syst., 26(2) (2011) 719–727. doi: 10.1109/TPWRS.2010.2055901.
[16] Y. Hua and T. K. Sarkar, Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise, IEEE Trans. Acoust., 38(5) (1990) 814–824. doi: 10.1109/29.56027.
[17] M. Sforna and M. Delfanti, Overview of the events and causes of the 2003 Italian blackout, in IEEE PES Power Systems Conference and Exposition, PSCE - Proceedings, (2006) 301–308.