Estimation of Low Frequency Oscillation Parameters Using Singular Value Decomposition Combined Group Search Optimizer

References

• W. Yao, L. Jiang, J. Y. Wen, Q. H. Wu, and S. J. Cheng, “Wide-area damping controller for power system interarea oscillations: A networked predictive control approach,” IEEE Trans. Control Syst. Technol., vol. 23, no. 1, pp. 27–36, 2015.
   Web of Science ®Google Scholar
• M. Klein, G. J. Rogers, and P. Kundur, “A fundamental study of inter-area oscillations in power systems,” IEEE Trans. Power Syst., vol. 6, no. 3, pp. 914–921, 1991. DOI:10.1109/59.119229.
   Web of Science ®Google Scholar
• H. L. Gao, X. S. Zhan, X. W. Jiang, J. Wu, and Q. S. Yang, “Research on mechanism of power system low frequency oscillation based on damping coefficient.” In International Conference on Electrical and Electronics Engineering, pp. 99–103, 2017.
   Google Scholar
• W. S. Kao, “The effect of load models on unstable low-frequency oscillation damping in a longitudinal power system,” Electric Power Compon. Syst., vol. 29, no. 8, pp. 723–737, 2001. DOI:10.1080/153250001753182719.
   Web of Science ®Google Scholar
• Y. Shen, W. Yao, J. Y. Wen, H. B. He, and W. B. Chen, “Adaptive supplementary damping control of vsc-hvdc for interarea oscillation using grhdp,” IEEE Trans. Power Syst., vol. 33, no. 2, pp. 1777–1788, 2018.
   Web of Science ®Google Scholar
• Y. Shen, W. Yao, J. Y. Wen, H. B. He, and L. Jiang, “Resilient wide-area damping control using grhdp to tolerate communication failures,” IEEE Trans. Smart Grid, 2018, DOI:10.1109/TSG.2018.2803822.
   Google Scholar
• Messina, A. Roman, Inter-area Oscillations in Power Systems: a Nonlinear and Nonstationary Perspective. New York: Springer, 2009.
   Google Scholar
• K. Prasertwong, N. Mithulananthan, and D. Thakur, “Understanding low-frequency oscillation in power systems,” Int. J. Electric. Eng. Educ., vol. 47, no. 3, pp. 248–262, 2010. DOI:10.7227/IJEEE.47.3.2.
   Web of Science ®Google Scholar
• M. J. Rana, M. S. Alam, and M. S. Islam, “Continuous wavelet transform based analysis of low frequency oscillation in power system.” In International Conference on Advances in Electrical Engineering, pp. 320–323, 2015.
   Google Scholar
• J. F. Hauer, D. J. Trudnowski, and J. G. DeSteese, “A perspective on wams analysis tools for tracking of oscillatory dynamics.” In Power Engineering Society General Meeting, 2007. IEEE, pp. 1–10. IEEE, 2007.
   Google Scholar
• T. Jin, S. Liu, R. C. C. Flesch, and W. Su, “A method for the identification of low frequency oscillation modes in power systems subjected to noise,” Appl. Energy, vol. 206, pp. 1379–1392, 2017. DOI:10.1016/j.apenergy.2017.09.123.
   Web of Science ®Google Scholar
• Y. P. Yu, Y. L. Shen, X. Zhang, J. Y. Zhu, and J. J. Du, “The load oscillation energy and its effect on low-frequency oscillation in power system.” In International conference on Electric Utility Deregulation and Restructuring and Power Technologies, pp. 1336–1341, 2015.
   Google Scholar
• T. Hashiguchi, M. Yoshimoto, Y. Mitani, O. Saeki, and K. Tsuji, “Analysis of power system dynamics based on multiple synchronized phasor measurements.” In Power Engineering Society General Meeting, 2003, IEEE, volume 2. IEEE, 2003.
   Google Scholar
• D. J. Trudnowski, J. M. Johnson, and J. F. Hauer, “Making prony analysis more accurate using multiple signals,” IEEE Trans. Power Syst., vol. 14, no. 1, pp. 226–231, 1999. DOI:10.1109/59.744537.
   Web of Science ®Google Scholar
• J. Xiao, X. Xie, Y. Han, and J. Wu, “Dynamic tracking of low-frequency oscillations with improved prony method in wide-area measurement system.” In Power Engineering Society General Meeting, 2004. IEEE, pp. 1104–1109. IEEE, 2004.
   Google Scholar
• J. L. Rueda, C. A. Jurez, and I. Erlich, “Wavelet-based analysis of power system low-frequency electromechanical oscillations,” IEEE Trans. Power Syst., vol. 26, no. 3, pp. 1733–1743, 2011. DOI:10.1109/TPWRS.2010.2104164.
   Web of Science ®Google Scholar
• C. R. Liu, X. Li, P. F. Tian, and M. Wang, “An improved ira algorithm and its application in critical eigenvalues searching for low frequency oscillation analysis,” IEEE Trans. Power Syst., vol. 13, no. 4, pp. 2974–2983, 2017. DOI:10.1109/TPWRS.2016.2623661.
   Google Scholar
• J. Ma, P. Zhang, H. J. Fu, B. Bo, and Z. Y. Dong, “Application of phasor measurement unit on locating disturbance source for low-frequency oscillation,” IEEE Trans. Smart Grid, vol. 1, no. 3, pp. 340–346, 2010. DOI:10.1109/TSG.2010.2071889.
   Web of Science ®Google Scholar
• Y. S. Zhao, Y. Gao, Z. J. Hu, Y. J. Yang, J. Zhan, and Y. Zhang, “A new method of identifying the low frequency oscillations of power systems.” In 2009. ICEET’09. International Conference on Energy and Environment Technology, vol. 2, pp. 19–22. IEEE, 2009.
   Google Scholar
• Y. z Li, X. w Zheng, and X. c Xiao, “A study on cooperative multi-objective group search optimizer.” In The 27th Chinese Control and Decision Conference (2015 CCDC), pp. 3776–3781, May 2015.
   Google Scholar
• F. Y. Cong, W. Zhong, S. G. Tong, N. Tang, and J. Chen, “Research of singular value decomposition based on slip matrix for rolling bearing fault diagnosis,” J. Sound Vib., vol. 344, pp. 447–463, 2015. DOI:10.1016/j.jsv.2015.01.014.
   Web of Science ®Google Scholar
• J. J. Sanchez-Gasca, and J. H. Chow, “Computation of power system low-order models from time domain simulations using a Hankel matrix,” IEEE Trans. Power Syst., vol. 12, no. 4, pp. 1461–1467, 1997. DOI:10.1109/59.627842.
   Web of Science ®Google Scholar
• T. Wang, Z. P. Wang, and Y. Yang, “Modal estimation of low-frequency oscillation using perturbation sensitivity matrix with multiple parameters,” Electric Power Compon. Syst., vol. 42, no. 12, pp. 1301–1312, 2014. DOI:10.1080/15325008.2014.927027.
   Web of Science ®Google Scholar
• E. Aptoula, and S. Lefvre, “A comparative study on multivariate mathematical morphology,” Pattern Recognit., vol. 40, no. 11, pp. 2914–2929, 2007. DOI:10.1016/j.patcog.2007.02.004.
   Web of Science ®Google Scholar
• Q. H. Wu, Z. Lu, and T. Y. Ji, Protective Relaying of Power Systems Using Mathematical Morphology. London: Springer, 2009.
   Google Scholar
• D. Lauria, and C. Pisani, “On Hilbert transform methods for low frequency oscillations detection,” IET Gener. Transm. Distrib., vol. 8, no. 6, pp. 1061–1074, 2014. DOI:10.1049/iet-gtd.2013.0545.
   Web of Science ®Google Scholar
• Y. Shi, and R. C. Eberhart, “A modified particle swarm optimizer,” Proc. IEEE World Congr. Comput. Intell., pp. 69–73, 1998.
   Google Scholar
• L. Hai-Yan, and J. Hua, “Vicinal risk minimization based probability density function estimation algorithm using svm.” In 2010 Third International Conference on Information and Computing, volume 4, pp. 161–164. IEEE, 2010.
   Google Scholar
• I. Hiskens, IEEE pes task force on benchmark systems for stability controls. Technical Report, 2013.
   Google Scholar
• P. W. Sauer, M. A. Pai, and J. H. Chow, Power System Dynamics and Stability: With Synchrophasor Measurement and Power System Toolbox. Hoboken, NJ: Wiley - IEEE, 2017.
   Google Scholar
• R. Wilson, R. Shah, and N. Mithulananthan, “Expanding power system analysis toolbox (psat) functionalities for better result interpretation.” In Australasian Universities Power Engineering Conference, pp. 1–6. IEEE, 2014.
   Google Scholar