Effects of forced oscillations in power system damping estimation

This article analyzes the impact of forced power system oscillations on mode damping estimation. Parametric (Yule-Walker) and non-parametric (Welch) methods for mode estimation are tested in the presence of forced power system oscillations. For mode damping estimation based on non-parametric methods, an application of Half Power Point method is proposed. Performances of the mode estimators are evaluated using both simulated and real synchrophasor data from the Nordic Grid. The presence of forced oscillations poses difficulties to mode damping estimators, these difficulties are identified, illustrated and explained herein.

[1]  Li Xiaoxiao,et al.  Analysis on oscillation in electro-hydraulic regulating system of steam turbine and fault diagnosis based on PSOBP , 2010 .

[2]  J. F. Hauer,et al.  Making Prony analysis more accurate using multiple signals , 1999 .

[3]  Daniel J. Trudnowski,et al.  Initial results in electromechanical mode identification from ambient data , 1997 .

[4]  Arturo Roman Messina,et al.  Inter-area Oscillations in Power Systems , 2009 .

[5]  N. Rostamkolai,et al.  Evaluation of the impact of a large cyclic load on the LILCO power system using time simulation and frequency domain techniques , 1994 .

[6]  J. E. Van Ness,et al.  Response of Large Power Systems to Cyclic Load Variations , 1966 .

[7]  J. F. Hauer,et al.  Initial results in Prony analysis of power system response signals , 1990 .

[8]  Xiaoxiao Li,et al.  Analysis on oscillation in electro-hydraulic regulating system of steam turbine and fault diagnosis based on PSOBP , 2010, Expert Syst. Appl..

[9]  B. C. Papadias,et al.  Analysis of forced oscillations in a multimachine power system , 1991 .

[10]  Arturo Roman Messina,et al.  Inter-area Oscillations in Power Systems: A Nonlinear and Nonstationary Perspective , 2009 .

[11]  J.W. Pierre,et al.  Bootstrap-based confidence interval estimates for electromechanical modes from multiple output analysis of measured ambient data , 2005, IEEE Transactions on Power Systems.

[12]  Joe H. Chow,et al.  Application of ambient analysis techniques for the estimation of electromechanical oscillations from measured PMU data in four different power systems , 2011 .

[13]  Monson H. Hayes,et al.  Statistical Digital Signal Processing and Modeling , 1996 .

[14]  J. O. Gjerde,et al.  Applications of spectral analysis techniques for estimating the nordic grid's low frequency electromechanical oscillations , 2012 .

[15]  Matthew K. Donnelly,et al.  Overview of System Identification for Power Systems from Measured Responses1 , 2012 .

[16]  George D. Hatzigeorgiou,et al.  On the use of the half-power bandwidth method to estimate damping in building structures , 2011 .