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Autor(en): Lemmer, Frank
Yu, Wei
Steinacker, Heiner
Skandali, Danai
Raach, Steffen
Titel: Advances on reduced-order modeling of floating offshore wind turbines
Erscheinungsdatum: 2021
Dokumentart: Konferenzbeitrag
Konferenz: ASME International Conference on Ocean, Offshore and Arctic Engineering (40th, 2021, Online)
Seiten: 9
Erschienen in: Proceedings of ASME 2021 40th International Conference on Ocean, Offshore and Arctic Engineering : OMAE 2021, June 21-30, 2021, Virtual, online. Vol. 9 : Ocean renewable energy. ASME, 2021. - ISBN 978-0-7918-8519-2, no. OMAE2021-63701, S. V009T09A034
URI: http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-117383
http://elib.uni-stuttgart.de/handle/11682/11738
http://dx.doi.org/10.18419/opus-11721
Bemerkungen: Originally published by ASME, 2021.
Zusammenfassung: Aero-hydro-servo-elastic modeling of Floating Offshore Wind Turbines (FOWTs) is a key component in the design process of various components of the system. Different approaches to order reduction have been investigated with the aim of improving structural design, manufacturing, transport and installation, but also the dynamic behavior, which is largely affected by the blade pitch controller. The present work builds on previous works on the SLOW (Simplified Low-Order Wind Turbine) code, which has already been used for the above purposes, including controller design. While the previous rigid rotor model gives good controllers in most cases, we investigate in the present work the question if aero-elastic effects in the design model can improve advanced controllers. The SLOW model is extended for the flapwise bending and coupled to NREL's AeroDyn, linearized and verified with the OlavOlsen OO-Star Wind Floater Semi 10MW public FOWT model. The results show that the nonlinear and linear reduced-order SLOW models agree well against OpenFAST. The state-feedback Linear Quadratic Regulator (LQR) applied with the same weight functions to both models, the old actuator disk, and the new aero-elastic model shows that the LQR becomes more sensitive to nonlinear excitation and that the state feedback matrix is significantly different, which has an effect on the performance and potentially also on the robustness. Thus modeling uncertainties might even be more critical for the LQR of the higher-fidelity model.
Enthalten in den Sammlungen:06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

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