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Application of Ambient Analysis Techniques for Electromechanical Mode Estimation from Measured PMU Data in the Nordic Power System
KTH, School of Electrical Engineering (EES), Electric Power Systems.ORCID iD: 0000-0002-4125-1055
2010 (English)Report (Other academic)
Abstract [en]

For over more than two decades, the application of advanced signal processing techniques to power system measurement data for the estimation of dynamic properties has been an important research subject. Recently, many techniques have been applied to transient (or ringdown) data, ambient data, and to probing data. Some of these methodologies are now being included in off-line analysis software, and are now being incorporated into software tools used in control rooms for monitoring the near real-time behavior of power system dynamics. In this study we illustrate the practical application of some ambient analysis methods for electromechanical mode estimation in Nordic power system. The discussions and results in this study are of value to power system operators and planners as they provide information of the applicability of these techniques via readily available signal processing tools, and in addition, it is shown how to critically analyze the results obtained with these methods. Comparison with eigenanalysis results allows engineers to realize the value of ambient analysis techniques as a supportive tool for the more common eigenanalysis methods.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2010. , 11 p.
Trita-EE, ISSN 1653-5146 ; 2010:052
Keyword [en]
Power system oscillations, power system identification, power system parameter estimation, power system monitoring, application of signal processing techniques, synchronized phasor measurements, power system measurements, small-signal stability.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-63375OAI: diva2:482079
QC 20120126. Invited White paper prepared for a Special Publication of the Task Force on Modal Identification of Electromechanical Modes, IEEE PES Society, October 2010.Available from: 2012-01-26 Created: 2012-01-23 Last updated: 2012-01-26Bibliographically approved

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Vanfretti, Luigi
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