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Published in: Cluster Computing 4/2019

20-03-2018

Intelligence algorithm for optimization design of the low wind speed airfoil for wind turbine

Authors: Xiaoping Pang, Haoyu Wang, Jin Chen

Published in: Cluster Computing | Special Issue 4/2019

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Abstract

In order to develop wind resources in low wind speed (LWS) area, a new intelligence algorithm based on the airfoil profile expressed by B-spline for LWS airfoil is proposed. Considering the design requirements for LWS wind turbine airfoil design and taking the DU airfoil as original design coefficients, the new LWS airfoil families with the thickness of 18, 21, 25, 30, 35, 40% were obtained by the particle swarm optimization based on the improved inertia factor and mode. The results show that, compared with the original DU airfoils, all the LWS airfoil families have better aerodynamic performance under free and fixed transition. Performance of the 18% thickness airfoil is improved most significantly: Under fixed transition condition, the maximum lift coefficient increases by 13.53%, and the maximum lift to drag ratio increases by 10.77%; under the free transition condition, the maximum lift coefficient increases by 18.84%, and the maximum lift to drag ratio increases by 11.92%. The aerodynamic performance of a new airfoil named CQUL-180, taken as an example, was analyzed and validated by the computational fluid dynamics compared with DU96-W-180 airfoil, which verifies the reliability of the intelligence algorithm.

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Metadata
Title
Intelligence algorithm for optimization design of the low wind speed airfoil for wind turbine
Authors
Xiaoping Pang
Haoyu Wang
Jin Chen
Publication date
20-03-2018
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 4/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1635-4

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