Statistical linearisation of a nonlinear floating offshore wind turbine under random waves and winds

被引:15
|
作者
Da Silva, L. S. P. [1 ,2 ]
De Oliveira, M. [3 ]
Cazzolato, B. [1 ]
Sergiienko, N. [1 ]
Amaral, G. A. [4 ]
Ding, B. [1 ]
机构
[1] Univ Adelaide, Sch Mech Engn, Adelaide, Australia
[2] Delmar Syst, Perth, Australia
[3] Univ Sao Paulo, Dept Mech Engn, Escola Politecn, Sao Paulo, Brazil
[4] Univ Sao Paulo, Offshore Mech Lab, Escola Politecn, Sao Paulo, Brazil
基金
巴西圣保罗研究基金会;
关键词
Floating offshore wind turbine; Statistical linearisation; Frequency-domain; Aerodynamic admittance; Nonlinear dynamics; FREQUENCY-DOMAIN MODEL; ADMITTANCE FUNCTION; DYNAMIC-RESPONSE; COUPLED ANALYSIS; IMPACT; LOADS;
D O I
10.1016/j.oceaneng.2022.112033
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
This paper investigates the stochastic nonlinear dynamics of a floating offshore wind turbine (FOWT) in the frequency-domain under irregular waves and turbulent winds. The main sources of nonlinearities are estimated using statistical linearisation, which are calculated based on probability density functions (PDFs) between the degrees-of-freedom and the environment. The nonlinear mooring model captures the coupling between degrees -of-freedom when the platform has a mean displacement caused by the wind thrust, changing the natural frequency especially in surge. In addition, the nonlinear viscous drag loads offer an hydrodynamic damping that lead to better estimates of the responses. The nonlinear aerodynamic loads uses the relative motion experienced by the wind turbine under turbulent wind, and the concept of aerodynamic admittance function, which has not been applied yet to FOWTs, is included to capture the spatial effects of the wind turbulence. The results are benchmarked against nonlinear time-domain simulations using OpenFAST, and good agreement is obtained in terms of power spectral densities, PDFs and standard deviations. Several environmental conditions are used to explore some of the platform characteristics and salient features from the model. The main advantage of the following approach is the low computational cost, while providing reliable estimates of the response.
引用
收藏
页数:15
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