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Application of SVD method for signal parameters estimation in systems with DFIG
Signal parameters estimation is an important prerequisite for assessment of power quality (PQ) indices. Nowadays, large amounts of measured data need to be automatically processed for appropriate and useful data mining in PQ. Especially, modern wind generators are often seen as sources of PQ disturb...
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creator | Janik, P. Ruczewski, P. Waclawek, Z. Lobos, T. Schostan, S. Schulz, D. |
description | Signal parameters estimation is an important prerequisite for assessment of power quality (PQ) indices. Nowadays, large amounts of measured data need to be automatically processed for appropriate and useful data mining in PQ. Especially, modern wind generators are often seen as sources of PQ disturbances, which should be constantly supervised. The authors propose an application of modified singular value decomposition (SVD) method for signal parameters estimation. Results of the proposed method are compared with broadly used Fourier Transform. A mechanical model of doubly fed induction generator (DFIG) operating in various conditions was chosen as a source of disturbed signals. Research results verify the usefulness of SVD based method. Additionally, the dependence between operating mode of a DFIG and generated disturbance parameters was observed. |
doi_str_mv | 10.1109/HSI.2008.4581523 |
format | conference_proceeding |
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Nowadays, large amounts of measured data need to be automatically processed for appropriate and useful data mining in PQ. Especially, modern wind generators are often seen as sources of PQ disturbances, which should be constantly supervised. The authors propose an application of modified singular value decomposition (SVD) method for signal parameters estimation. Results of the proposed method are compared with broadly used Fourier Transform. A mechanical model of doubly fed induction generator (DFIG) operating in various conditions was chosen as a source of disturbed signals. Research results verify the usefulness of SVD based method. Additionally, the dependence between operating mode of a DFIG and generated disturbance parameters was observed.</abstract><pub>IEEE</pub><doi>10.1109/HSI.2008.4581523</doi><tpages>5</tpages></addata></record> |
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source | IEEE Xplore All Conference Series |
subjects | Artificial neural networks Current measurement Data mining DFIG Generators Harmonic analysis Mathematical model Power harmonic filters Power Quality Reactive power SVD method Wind Turbines |
title | Application of SVD method for signal parameters estimation in systems with DFIG |
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