Dynamic analysis and optimization of a wind turbine tower subject to wind and earthquake loads

Summary A dynamic model of a wind turbine tower is established to investigate its dynamic responses under wind and earthquake loads. Then a generalized global spatial discretization method is used to solve the problem. Modal analysis of the wind turbine tower is conducted using the dynamic model and...

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Bibliographic Details
Published inThe structural design of tall and special buildings Vol. 31; no. 15
Main Authors Zhu, Hao, Li, Deyu, Xu, Jun
Format Journal Article
LanguageEnglish
Published Oxford Wiley Subscription Services, Inc 25.10.2022
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Summary:Summary A dynamic model of a wind turbine tower is established to investigate its dynamic responses under wind and earthquake loads. Then a generalized global spatial discretization method is used to solve the problem. Modal analysis of the wind turbine tower is conducted using the dynamic model and the results are verified by shell models and beam models established in the commercial FE software ANSYS and LS‐DYNA. Transient vibration displacements, as well as normal and shear stress distributions of the wind turbine tower subject to different levels of pulsing wind loads, are calculated based on the dynamic model. Quasi‐static motion and transient motion assumptions are applied to evaluate the strengths of the tower, respectively. Influences of different earthquake ground motions on vibration amplitudes of the tower top are examined. Then, a hybrid mutation particle swarm optimization algorithm is used to perform design optimization on the tower body thickness for vibration reduction with its weights and strength being constrained. The penalty function strategy is used to deal with the constraints on body weight and stress level. Results demonstrate that the comprehensive performances of the wind turbine tower especially the tower top vibration have been greatly reduced after optimization.
Bibliography:Funding information
Miaozi Project in Science and Technology Innovation Program of Sichuan Province, Grant/Award Number: 2020‐33; Natural Science Foundation of Sichuan Province in China, Grant/Award Numbers: 2022NSFSC1929, 2022NSFSC1159; Natural Science Foundation of China, Grant/Award Number: 51805339
ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1541-7794
1541-7808
DOI:10.1002/tal.1971