Inter-area Oscillations in Power Systems: A Nonlinear and Nonstationary Perspective
Arturo Roman Messina
Springer Science & Business Media, Apr 21, 2009 - Technology & Engineering - 275 pages
The study of complex dynamic processes governed by nonlinear and nonstationary characteristics is a problem of great importance in the analysis and control of power system oscillatory behavior. Power system dynamic processes are highly random, nonlinear to some extent, and intrinsically nonstationary even over short time intervals as in the case of severe transient oscillations in which switching events and control actions interact in a complex manner. Phenomena observed in power system oscillatory dynamics are diverse and complex. Measured ambient data are known to exhibit noisy, nonstationary fluctuations resulting primarily from small magnitude, random changes in load, driven by low-scale motions or nonlinear trends originating from slow control actions or changes in operating conditions. Forced oscillations resulting from major cascading events, on the other hand, may contain motions with a broad range of scales and can be highly nonlinear and time-varying. Prediction of temporal dynamics, with the ultimate application to real-time system monitoring, protection and control, remains a major research challenge due to the complexity of the driving dynamic and control processes operating on various temporal scales that can become dynamically involved. An understanding of system dynamics is critical for reliable inference of the underlying mechanisms in the observed oscillations and is needed for the development of effective wide-area measurement and control systems, and for improved operational reliability.
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Inter-area Oscillations in Power Systems: A Nonlinear and Nonstationary ...
Arturo Roman Messina
No preview available - 2009
algorithm ambient amplitude analytic signal analyzing application approach behavior complex computed control actions damping ratio detection distorted signal disturbance dominant modes eigenanalysis eigenvalue electromechanical modes empirical mode decomposition Empirical Orthogonal Function energy extracted false alarm frequency components Frequency Hz function heterodyne Hilbert analysis Hilbert transform Hz mode identified IEEE IEEE Trans IEEE Transactions IMF1 IMFs instantaneous frequency instantaneous phase inter-area modes Inter-area Oscillations J. F. Hauer Ledwich linear load masking signal matrix measured data modal frequency modal parameters mode estimates mode shape monitoring multi-Prony noise nonlinear nonstationary obtained operating orthogonal oscillatory phase plot PMUs power flow probing signal Prony analysis PSDC R-EMD real-time ringdown Section shown in Fig shows simulations small-signal spectral analysis spectrum stability standard EMD system dynamic system identification technique temporal threshold time-varying time–frequency Transactions on Power transient variations voltage magnitude wavelet window wNAPS xðtÞ