Using spectral analysis and modal estimation for identifying electromechanical oscillations: A case study of the power system in northern Norway and northern Finland

This paper analyses electromechanical oscillations in the northern area of the Nordic power system. Both spectral analysis and modal identification methods are used to analyze signals received from the phasor measurement units (PMU) installed in the system. Spectrograms are used to analyze the characteristics of electromechanical oscillations and to support the interpretation of the modal identification methods. The results indicate that these methods are effective in presenting the oscillatory characteristics of the system. In addition, the results show that the spectrograms help in interpretation of the modal estimates.

[1]  K. Uhlen,et al.  Wide Area Monitoring Experiences in Norway , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[2]  W. Mittelstadt,et al.  Electromechanical Mode Online Estimation Using Regularized Robust RLS Methods , 2008, IEEE Transactions on Power Systems.

[3]  J.W. Pierre,et al.  Combining least mean squares adaptive filter and auto-regressive block processing techniques for estimating the low-frequency electromechanical modes in power systems , 2006, 2006 IEEE Power Engineering Society General Meeting.

[4]  Tuomas Rauhala,et al.  Selecting wavelets for damping estimation of ambient-excited electromechanical oscillations , 2010, IEEE PES General Meeting.

[5]  J Thambirajah,et al.  A Multivariate Approach Towards Interarea Oscillation Damping Estimation Under Ambient Conditions Via Independent Component Analysis and Random Decrement , 2011, IEEE Transactions on Power Systems.

[6]  Jukka Turunen,et al.  A wavelet-based method for estimating damping in power systems , 2011 .

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

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

[9]  Jukka Turunen,et al.  Modal analysis of power systems with eigendecomposition of multivariate autoregressive models , 2013, 2013 IEEE Grenoble Conference.

[10]  Nand Kishor,et al.  Modal Analysis of Power Systems Through Natural Excitation Technique , 2014, IEEE Transactions on Power Systems.

[11]  A. M. Carter,et al.  Comparison of Three Electromechanical Oscillation Damping Estimation Methods , 2011, IEEE Transactions on Power Systems.

[12]  Luigi Vanfretti,et al.  Spectral estimation of low-frequency oscillations in the Nordic grid using ambient synchrophasor data under the presence of forced oscillations , 2013, 2013 IEEE Grenoble Conference.

[13]  Jukka Turunen,et al.  Performance of wavelet-based damping estimation method under ambient conditions of the power system , 2010, 2010 IREP Symposium Bulk Power System Dynamics and Control - VIII (IREP).

[14]  Christian Rehtanz,et al.  Detection of oscillations in power systems using Kalman filtering techniques , 2003, Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003..

[15]  Jukka Turunen,et al.  Analysis of electromechanical modes using multichannel Yule-Walker estimation of a multivariate autoregressive model , 2013, IEEE PES ISGT Europe 2013.

[16]  Mats Larsson,et al.  Monitoring of inter-area oscillations under ambient conditions using subspace identification , 2009, 2009 IEEE Power & Energy Society General Meeting.

[17]  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.

[18]  J. W. Pierre,et al.  Use of ARMA Block Processing for Estimating Stationary Low-Frequency Electromechanical Modes of Power Systems , 2002, IEEE Power Engineering Review.