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Extraction of Dynamic Patterns from Wide-Area Measurements using Empirical Orthogonal Functions

Doktorarbeit / Dissertation 2010 146 Seiten

Elektrotechnik

Zusammenfassung

Multi-variate statistical data analysis techniques offer a powerful tool for analyzing power system response from measured data. In this thesis, a statistically-based, data-driven framework that integrates the use of complex wavelet empirical orthogonal function (EOF) analysis and the method of snapshots is proposed to identify and extract dynamically independent spatio-temporal patterns from time synchronized data. The procedure allows identification of the dominant spatial and temporal patterns in a complex data set and is particularly well suited for the study of standing and propagating features that can be associated with electromechanical oscillations in power systems. It is shown that, in addition to providing spatial and temporal information, the method improves the ability of conventional correlation analysis to capture temporal events and gives a quantitative result for both the amplitude and phase of motions, which are essential in the interpretation and characterization of transient processes in power systems. The efficiency and accuracy of the developed procedures for capturing the temporal evolution of the modal content of data from time synchronized phasor measurements of a real event in México is assessed. Results show that the proposed method can provide accurate estimation of nonstationary effects, modal frequency, time-varying mode shapes, and time instants of intermittent or irregular transient behavior associated with abrupt changes in system topology or operating conditions.

Details

Seiten
146
Jahr
2010
ISBN (Buch)
9783656737605
Dateigröße
2.5 MB
Sprache
Englisch
Katalognummer
v280564
Institution / Hochschule
Universidad de Guadalajara – CINVESTAV - Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional Unidad Guadalajara
Note
Identificación de patrones
Schlagworte
extraction dynamic patterns wide-area measurements empirical orthogonal functions

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Titel: Extraction of Dynamic Patterns from Wide-Area Measurements using Empirical Orthogonal Functions