Modal Extraction for Wind Turbines using Moving Window Subspace Identification

W. Liang, Timothy Littler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper proposes a method for wind turbine mode identification using the multivariable output error statespace (MOESP) identification algorithm. The paper incorporates a fast moving window QR decomposition and propagator method from array signal processing, yielding a moving window subspace identification algorithm. The algorithm assumes that the system order is known as a priori and remains constant during identification. For the purpose of extracting modal information for turbines modelled as a linear parameter varying (LPV) system, the algorithm is applicable since a nonlinear system can be approximated as a piecewise time invariant system in consecutive data windows. The algorithm is exemplified using numerical simulations which show that the moving window algorithm can track the modal information. The paper also demonstrates that the low computational burden of the algorithm, compared to conventional batch subspace identification, has significant implications for online implementation.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Sustainable Power Generation (SUPERGEN '09)
Pages1-9
Number of pages9
DOIs
Publication statusPublished - Apr 2009
EventInternational Conference on Sustainable Power Generation and Supply, 2009 (SUPERGEN '09) - Nanjing, China
Duration: 01 Apr 200901 Apr 2009

Conference

ConferenceInternational Conference on Sustainable Power Generation and Supply, 2009 (SUPERGEN '09)
Abbreviated titleSUPERGEN '09
CountryChina
CityNanjing
Period01/04/200901/04/2009

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  • Cite this

    Liang, W., & Littler, T. (2009). Modal Extraction for Wind Turbines using Moving Window Subspace Identification. In Proceedings of the International Conference on Sustainable Power Generation (SUPERGEN '09) (pp. 1-9) https://doi.org/10.1109/SUPERGEN.2009.5348112