Gain-scheduling control of floating offshore wind turbines on barge platforms

This thesis studies the application of gain-scheduling (GS) control techniques to floating offshore wind turbines on barge platforms. Modelling, control objectives, controller design and performance evaluations are presented for both low wind speed and high wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed.
The dynamics variation is represented by a linear parameter-varying (LPV) model. The LPV model for wind turbines is derived by linearizing the nonlinear dynamics at various operating wind speeds and by interpolating the linearized models.
In low wind speed, to achieve control objectives of maximizing power capture and minimizing platform movements, for the LPV model, the LPV GS design
technique is explored. In this region, the advantage of making use of blade pitch angle as a control input is also investigated. In high wind speed, to achieve control objectives of regulating power capture and minimizing platform movements, both LQR and LPV GS design techniques are explored.
To evaluate the designed controllers, simulation studies are conducted with a realistic 5 MW wind turbine model developed at National Renewable Energy Laboratory, and realistic wind and wave profiles. The average and root mean square values of power capture and platform pitch movement are adopted as performance measures, and compared among designed GS controllers and conventional controllers. The comparisons demonstrate the performance improvement achieved by GS control
techniques.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVAU.2429/44879
Date11 1900
CreatorsBagherieh, Omid
PublisherUniversity of British Columbia
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation

Page generated in 0.0017 seconds