EconPapers    
Economics at your fingertips  
 

Bionic inspired flutter suppression method for offshore ultra-long wind turbine blades

Xu Zhang, Lijun Zhang, Kaifei Wang, Xudong Cui, Zhengjun Jing, Ziyi Liu, Shibo Liu, Jiahui Lu, Yifan Zhang and Jiaxuan Li

Renewable Energy, 2025, vol. 239, issue C

Abstract: As the length of offshore horizontal axis wind turbine (HAWT) blades increases, the flutter problem becomes increasingly severe. A bionic inspired flutter suppression method for ultra-long wind turbine blades is proposed in this study. Considering the impact of aerodynamic loads from CFD on the structural vibration characteristics of the CSD, the flutter stability of the blades is analyzed using the eigenvalue method. The bionic liquid circulation system (BLCS) is constructed by orthogonal test and Voronoi diagram algorithm. The flutter suppression effect under three typical working conditions is also analyzed. The results show that the BLCS effectively reduces blade tip displacement under flutter conditions. In contrast to scenarios that employ solely reservoir or pipe network, the synergistic application of both yields the highest flutter suppression efficiency, enhancing the vibration reduction ratio by 0.9 % and 5.3 %, respectively.

Keywords: Ultra-long blades; Flutter suppression; Eigenvalue method; Voronoi diagram; Bionic (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148124021591
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:239:y:2025:i:c:s0960148124021591

DOI: 10.1016/j.renene.2024.122091

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:renene:v:239:y:2025:i:c:s0960148124021591