Optimization of Wind Turbine Thick Airfoils Using Improved Multi-objective Particle Swarm Algorithm

doi:10.12068/j.issn.1005-3026.2016.02.018

Journal of Northeastern University Natural Science ›› 2016, Vol. 37 ›› Issue (2): 232-236.DOI: 10.12068/j.issn.1005-3026.2016.02.018

• Mechanical Engineering • Previous Articles Next Articles

Optimization of Wind Turbine Thick Airfoils Using Improved Multi-objective Particle Swarm Algorithm

CHEN Jin， GUO Xiao-feng， SUN Zhen-ye， LI Song-lin

State Key Laboratory of Mechanic Transmission，Chongqing University，Chongqing 400044， China.

Received:2014-06-30 Revised:2014-06-30 Online:2016-02-15 Published:2016-02-18
Contact: GUO Xiao-feng
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Abstract

Abstract: Considering the low structural performance of wind turbine airfoils designed just with aerodynamic performance as an optimization objective， a new multi-objective optimization method is proposed based on improved multi-objective particle swarm optimization， which balances aerodynamic and structural performance of airfoils. The airfoils with thickness of 40% are parametrically described using the wind turbine airfoil integrated theory. The optimization objectives are the maximum lift-drag ratio when designing attack angles and the maximum inertia moment about the chord axis， with such requirements as stalling characteristics， sensitivity to leading edge roughness and design lift at off-design condition considered together. The Pareto-optimal set of airfoils is obtained. The representative airfoils in the set outperform the airfoil (DU00-W2-401) in terms of aerodynamic and structural performance.

Key words: wind turbine airfoil, structural performance, aerodynamic performance, multi-objective particle swarm optimization, optimization design

CLC Number:

TK83
TH12

CHEN Jin， GUO Xiao-feng， SUN Zhen-ye， LI Song-lin. Optimization of Wind Turbine Thick Airfoils Using Improved Multi-objective Particle Swarm Algorithm[J]. Journal of Northeastern University Natural Science, 2016, 37(2): 232-236.

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Optimization of Wind Turbine Thick Airfoils Using Improved Multi-objective Particle Swarm Algorithm

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