Novel approaches for multi-channel ringdown analysis using digital filters

This paper proposes novel techniques for monitoring the oscillatory modes in wide-area using synchrophasors measurements. The oscillatory modes are identified through the Taylor-Kalman-Fourier, Alternating Kalman, and Taylor-Fourier digital filters, accomplishing a ringdown analysis. They are stated multidimensionally in order to process multiple channels from PMU data. The proposals are tested under noisy conditions with simulated data, exhibiting the capability of identifying multiple electromechanical modes, and providing global information about modal properties of the power system.

[1]  Bin Sun,et al.  Dynamic characteristic analysis of power system interarea oscillations using HHT , 2010 .

[2]  Juan M. Ramirez,et al.  Phasor estimation under transient conditions , 2015, 2015 IEEE Eindhoven PowerTech.

[3]  Mario A. Rios,et al.  Electromechanical Modes Identification Based on Sliding-window Data from a Wide-area Monitoring System , 2013 .

[4]  A. Chakrabortty,et al.  PMU placement for dynamic equivalencing of power systems under flow observability constraints , 2014 .

[5]  V. Vittal,et al.  Right-Sized Power System Dynamic Equivalents for Power System Operation , 2011, IEEE Transactions on Power Systems.

[6]  Vaithianathan Venkatasubramanian,et al.  Two-Level Ambient Oscillation Modal Estimation From Synchrophasor Measurements , 2015, IEEE Transactions on Power Systems.

[7]  José Antonio de la O. Serna,et al.  Dynamic Phasor Estimates for Power System Oscillations , 2007, IEEE Transactions on Instrumentation and Measurement.

[8]  Juan M. Ramirez,et al.  Digital filter for phasor estimation applied to distance relays , 2015 .

[9]  A.R. Messina,et al.  A Refined Hilbert–Huang Transform With Applications to Interarea Oscillation Monitoring , 2009, IEEE Transactions on Power Systems.

[10]  Michael Feldman,et al.  Hilbert Transform Applications in Mechanical Vibration: Feldman/Hilbert Transform Applications in Mechanical Vibration , 2011 .

[11]  Arturo Roman Messina Wide Area Monitoring of Interconnected Power Systems , 2015 .

[12]  Junqi Liu,et al.  A Fast and Accurate PMU Algorithm for P+M Class Measurement of Synchrophasor and Frequency , 2014, IEEE Transactions on Instrumentation and Measurement.

[13]  Jukka Turunen,et al.  Modal analysis of power systems through natural excitation technique , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[14]  Ali Mehrizi-Sani,et al.  Estimation of Electromechanical Oscillation Parameters Using an Extended Kalman Filter , 2015, IEEE Transactions on Power Systems.

[15]  Wendy Van Moer,et al.  Using Alternating Kalman Filtering to Analyze Oscillometric Blood Pressure Waveforms , 2013, IEEE Transactions on Instrumentation and Measurement.

[16]  Tapan K. Sarkar,et al.  Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise , 1990, IEEE Trans. Acoust. Speech Signal Process..

[17]  José Antonio de la O. Serna,et al.  Smart grids Part 2: Synchrophasor measurement challenges , 2015, IEEE Instrumentation & Measurement Magazine.

[18]  P. Korba,et al.  Nonlinear damping computation and envelope detection using Hilbert transform and its application to power systems wide area monitoring , 2009, 2009 IEEE Power & Energy Society General Meeting.

[19]  Joost Rommes,et al.  Computing Rightmost Eigenvalues for Small-Signal Stability Assessment of Large-Scale Power Systems , 2010, IEEE Transactions on Power Systems.

[20]  Arindam Ghosh,et al.  Dynamic equivalent state estimation for multi-area power systems withsynchronized phasor measurement units , 2013 .

[21]  José Antonio de la O. Serna,et al.  Taylor–Kalman–Fourier Filters for Instantaneous Oscillating Phasor and Harmonic Estimates , 2012, IEEE Transactions on Instrumentation and Measurement.

[22]  Juan M. Ramirez,et al.  Identification of Electromechanical Modes Based on the Digital Taylor-Fourier Transform , 2016, IEEE Transactions on Power Systems.

[23]  J. A. de la O Serna,et al.  Instantaneous Oscillating Phasor Estimates With Taylor$^K$-Kalman Filters , 2011, IEEE Transactions on Power Systems.

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

[25]  R. Kumaresan,et al.  Estimating the parameters of exponentially damped sinusoids and pole-zero modeling in noise , 1982 .

[26]  Rob J Hyndman,et al.  Forecasting with Exponential Smoothing: The State Space Approach , 2008 .

[27]  Jer-Nan Juang,et al.  An eigensystem realization algorithm for modal parameter identification and model reduction. [control systems design for large space structures] , 1985 .

[28]  Nilanjan Senroy,et al.  Critical clearing time estimation using synchrophasor data-based equivalent dynamic model , 2015 .

[29]  Vaithianathan Venkatasubramanian,et al.  Multi-Dimensional Fourier Ringdown Analysis for Power Systems Using Synchrophasors , 2014, IEEE Transactions on Power Systems.