Applications of a new nonparametric estimator of ambient power system spectra for measurements containing forced oscillations

Synchrophasor measurements from power systems can include several components, including ambient noise, forced oscillations (FOs), and transients. A new nonparametric spectral estimator is proposed that is able to accurately estimate the ambient noise spectrum, even in the presence of FOs. The statistical performance of the method is derived and compared with the commonly used Welch periodogram. The importance of the estimator's characteristics in a FO detection algorithm's design is highlighted with simulation examples. It is expected that other applications will also benefit from the new estimator's defining characteristics.

[1]  M. A. Magdy,et al.  Frequency domain analysis of power system forced oscillations , 1990 .

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

[3]  Francis Tuffner,et al.  A multi-channel method for detecting periodic forced oscillations in power systems , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[4]  C. W. Taylor,et al.  Model validation for the August 10, 1996 WSCC system outage , 1999 .

[5]  Dmitry Kosterev,et al.  PDCI damping control analysis for the western North American power system , 2013, 2013 IEEE Power & Energy Society General Meeting.

[6]  P. Kundur,et al.  Power system stability and control , 1994 .

[7]  I. Hiskens,et al.  Limit-induced stable limit cycles in power systems , 2005, 2005 IEEE Russia Power Tech.

[8]  Ning Zhou,et al.  Initial results in using a self-coherence method for detecting sustained oscillations , 2015, 2015 IEEE Power & Energy Society General Meeting.

[9]  Petre Stoica,et al.  Spectral Analysis of Signals , 2009 .

[10]  Haikady N. Nagaraja.  Order Statistics from Independent Exponential Random Variables and the Sum of the Top Order Statistics , 2006 .

[11]  John Pierre,et al.  Detection of Periodic Forced Oscillations in Power Systems , 2016, IEEE Transactions on Power Systems.

[12]  Ning Zhou,et al.  A coherence method for detecting and analyzing oscillations , 2013, 2013 IEEE Power & Energy Society General Meeting.

[13]  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 .

[14]  D. Brillinger.  Time series - data analysis and theory , 1981, Classics in applied mathematics.

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

[16]  J.W. Pierre,et al.  Electromechanical Modal Behavior During a 48 Hour Interval Using Nonparametric Methods , 2006, 2006 38th North American Power Symposium.

[17]  John Pierre,et al.  RMS-energy filter design for real-time oscillation detection , 2015, 2015 IEEE Power & Energy Society General Meeting.