Using incomplete complex modes for model updating of monopiled offshore wind turbines. (January 2022)

• Record Type: Journal Article
• Authors: Cong, Shuai; James Hu, Sau-Lon; Li, Hua-Jun
• Is Part Of: Renewable energy. Volume 181(2022)
• Page Start: 522
• Page End: 534
• Publication Date: 2022-01
• Subjects: Offshore wind turbines -- Model updating -- Spatial incompleteness -- Complex modes; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2021.09.022
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: The soil-structure interface stiffness/damping, structure damping, aerodynamic damping, and hydrodynamic added mass are the four major sources of error while modeling a monopiled offshore wind turbine by using finite element methods. This study develops a comprehensive strategy, involving optimal sensor placement, complex mode expansion, and cross-model cross-mode-based model updating technique, for simultaneously correcting the model parameters associated with the mentioned four major sources of error, when only a few sensors are installed to extract modal data, including modal frequencies and damping ratios, and spatially incomplete mode shapes. To demonstrate the effectiveness of the proposed method, computer simulations with the National Renewable Energy Laboratory 5-MW reference turbine are carried out. The numerical studies reveal that (1) when clean modal data are utilized, all model parameters can be updated properly by the proposed method; it is recommended the first few low-order modes, together with as many sensors as possible, be used; (2) when contaminated spatially incomplete complex eigenvectors are given, even some model parameters can not be updated accurately, the updated model is still adequate for dynamic analysis and design as long as the dominant model parameters are updated properly. Highlights: Develops a comprehensive updating strategy using measurements from a few sensors. Simultaneously updates OWT's mass, damping and stiffness parameters. Requires only a few low-order eigenvalues and incomplete eigenvectors. Demonstrates the effectiveness of the proposed method by computer sim-ulations.