City Research Online

Abstract

Floating offshore wind turbines (FOWT) stand as a promising concept to expand the wind energy generation into the more productive deep-water areas, where conventional bottom-fixed turbines are infeasible. Barge-type floating wind turbines experience an inverted pendulum effect which produces a coupling with the wind turbine response, resulting in large structural loads. In this paper, the authors investigate passive structural control to mitigate the tower fatigue, in the form of a tuned mass damper (TMD) installed in the nacelle. The study focuses on evaluating the benefits of adding a parallel-connected inerter device to the TMD. Based on a reduced dynamics model for the barge-type offshore wind turbine identified using the FAST-SC synthetic reference data, an optimization of the TMD and the inerter parameters is carried out. To that end, genetic algorithms were used taking the tower fatigue as a fitness function, derived from the tower top displacement. The results confirm that the inerter has limitations when installed in a traditional TMD, but show significant benefits when the TMD stroke is constrained by stops. It is found that the improved performance including the inerter is dependent on the stroke limitation with respect to the ideal TMD stroke without stops. Therefore, the use of the inerter is especially useful to enhance performances for both mass and stroke constrained applications. The load reduction for the selected baseline model improved up to 6 % over the TMD with stops and 12 % over the TMD without stops.

Publication Type:	Conference or Workshop Item (Paper)
Additional Information:	This is an open access article under the CC-BY-NC-ND license.
Publisher Keywords:	Barge Offshore Wind Turbine, Passive Structural Control, Tuned Mass Damper, Inerter, Genetic Algorithm Optimization, Fatigue
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments:	School of Science & Technology School of Science & Technology > Engineering
SWORD Depositor:	Symplectic Administrator

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