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Identification and Validation of a Barge Floating Offshore Wind Turbine Model with Optimized Tuned Mass Damper

Tomas-Rodriguez, M. ORCID: 0000-0001-9630-9579, Villoslada, D. and Santos, M. (2019). Identification and Validation of a Barge Floating Offshore Wind Turbine Model with Optimized Tuned Mass Damper. Paper presented at the 10th EUROSIM Congress on Modelling and Simulation Logroño, 01 - 05 July 2019, La Rioja, Spain.

Abstract

Floating offshore wind turbines (FWOT) 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, we apply passive structural control in the form of a tuned mass damper, installed in the nacelle to mitigate the tower fatigue. A linear dynamics model for the barge-type offshore wind turbine is formulated based on Lagrange’s equations. The parameter identification for this model is performed using the FAST-SC simulation software to produce synthetic experimental reference data. A thorough validation study was carried out to select the optimal free-decay initial conditions and test duration to obtain the most suited model parameters. It was found that the 3 degrees initial platform pitch tests began sufficiently far from rest to allow the dynamics to be characterized, but not so far to be affected by the unmodeled non-linearities. Once the model was ready to simulate the system properly, an optimization of the TMD parameters is carried out using genetic algorithms, taking the tower fatigue as a fitness function, derived from the tower top displacement. The results show this tuned conventional passive structural control can help to absorb the vibrations of the structure, reducing the tower fatigue by 50%.

Publication Type: Conference or Workshop Item (Paper)
Publisher Keywords: Identification, simulation, barge-type floating wind turbine, passive structural control, genetic algorithms
Subjects: T Technology > TC Hydraulic engineering. Ocean engineering
T Technology > TJ Mechanical engineering and machinery
Departments: School of Mathematics, Computer Science & Engineering > Engineering > Mechanical Engineering & Aeronautics
Date Deposited: 09 Dec 2019 16:17
URI: https://openaccess.city.ac.uk/id/eprint/23192
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