An interval quantification-based optimization approach for wind turbine airfoil under uncertainties

Xinzi Tang, Keren Yuan, Nengwei Gu, Pengcheng Li and Ruitao Peng

Energy, 2022, vol. 244, issue PA

Abstract: Wind turbine airfoil operates in the atmosphere with uncertain turbulence and relatively low Reynolds number all year round. Meanwhile, due to the complexity of blade airfoil fabrication, there are inevitable geometric deviations to the theoretical airfoil shape. These uncertainties from manufacturing and operating environment couple together and lead to performance degradation. In the traditional wind turbine airfoil design process, the uncertainties are not the design variables, objectives, and constraints are deterministic. This paper presents a novel approach for uncertain analysis and aerodynamic robustness optimization of wind turbine airfoil considering turbulence and geometric error uncertainties. An interval method coupled with the Kriging model is applied to quantify the uncertain influence, and is integrated in the optimization. The target of optimization is to find an optimal airfoil with low sensitivity to uncertainties, as well as maintaining lift to drag ratio. After optimization the min std best airfoil shows 17.96% reduction of fluctuation range and no decreased average of lift to drag ratio compared to the baseline airfoil. The optimization was validated through flow field analysis by non-deterministic CFD approach. The proposed methodology can be further applied to other engineering designs making product less sensitivity to uncertainties thus more reliable.

Keywords: Wind turbine; Optimization; Turbulence intensity; Geometric error; Interval; Surrogate model (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:244:y:2022:i:pa:s0360544221028723

DOI: 10.1016/j.energy.2021.122623

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