Improved structural design of wind turbine blade based on topology and size optimization

Assessment of optimum tip speed ratio in wind turbines using artificial neural networks

Jie Zhu, Xin Cai, Dongfang Ma, Jialiang Zhang and Xiaohui Ni

International Journal of Low-Carbon Technologies, 2022, vol. 17, 2153-61

Abstract: In order to compete with traditional power technologies and other energy sources, it is essential to use optimization techniques as part of the design process for wind turbine blades. This paper presents an optimization approach for the improved structural design of blades, aiming at further decreasing the blade mass and bringing down the cost. The optimization approach mainly consists of two steps. In the first step, topology optimization of a full 1.5 MW wind turbine blade is carried out with the expectation of finding an improved internal structural configuration by taking minimum compliance as an objective. In the second step, the topology optimization results are interpreted to create a shell finite element model of the blade to analyse the influence of distinguishing characteristic parameters on the blade performances; then, size optimizations of the blades with improved structural configuration and conventional structure are performed by considering the minimum mass as objective, key structural parameters as variables, strain, deflection, vibration and buckling limits as constraints. The final optimization results show that the blade with improved structural configuration can reach a further mass saving of 3% compared with the optimized conventional structure design, indicating that the proposed approach is effective and reliable.

Keywords: blade mass; improved structural configuration; size optimization; topology optimization; wind turbine blade (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1093/ijlct/ctab087 (application/pdf)
Access to full text is restricted to subscribers.

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:oup:ijlctc:v:17:y:2022:i::p:2153-61.

Access Statistics for this article

International Journal of Low-Carbon Technologies is currently edited by Saffa B. Riffat

More articles in International Journal of Low-Carbon Technologies from Oxford University Press
Bibliographic data for series maintained by Oxford University Press ().