DOAJ Open Access 2023

Identification of Vibration Modes in Floating Offshore Wind Turbines

Mikel Serrano-Antoñanazas Jesús-Enrique Sierra-Garcia Matilde Santos María Tomas-Rodríguez

Abstrak

Compared to onshore turbines, floating offshore wind turbines (FOWTs) take advantage of the increased availability of offshore wind while causing less environmental impact. However, the strong winds, waves, and currents to which they are subjected trigger oscillations that can cause significant damage to the entire structural system and reduce its useful life. To reduce these loads, active tower damping techniques such as filter banks can be used. These filters must be carefully tuned to block specific vibration frequencies. Therefore, it is essential to analyze the nature of the oscillations in the FOWT and to understand how the frequencies vary in time. This topic is usually approached from a point of view very focused on a specific turbine. What is proposed here is a general method, which can be applied to any type of wind turbine, to automatically study the relationship between vibration frequencies and the degrees of freedom (DOF) of the turbine, which facilitates the design of structural control. Each frequency is associated with the DOF of the FOWT that produces it. This methodology has been successfully validated in simulation experiments with the NREL 5 MW ITI Barge FOWT. Under the wind conditions of the experiments, the main frequency found is 0.605 Hz. This frequency coincides with the 3P theoretical frequency of the FOWT. This proposal may help to design structural control systems able to damp these vibration frequencies with accuracy and efficiency.

Penulis (4)

M

Mikel Serrano-Antoñanazas

J

Jesús-Enrique Sierra-Garcia

M

Matilde Santos

M

María Tomas-Rodríguez

Format Sitasi

Serrano-Antoñanazas, M., Sierra-Garcia, J., Santos, M., Tomas-Rodríguez, M. (2023). Identification of Vibration Modes in Floating Offshore Wind Turbines. https://doi.org/10.3390/jmse11101893

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Informasi Jurnal
Tahun Terbit
2023
Sumber Database
DOAJ
DOI
10.3390/jmse11101893
Akses
Open Access ✓