An interval quantification-based optimization approach for wind turbine airfoil under uncertainties. (1st April 2022)
- Record Type:
- Journal Article
- Title:
- An interval quantification-based optimization approach for wind turbine airfoil under uncertainties. (1st April 2022)
- Main Title:
- An interval quantification-based optimization approach for wind turbine airfoil under uncertainties
- Authors:
- Tang, Xinzi
Yuan, Keren
Gu, Nengwei
Li, Pengcheng
Peng, Ruitao - Abstract:
- 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. Highlights: A novel methodology for uncertain optimization of wind turbine airfoil. StudyAbstract: 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. Highlights: A novel methodology for uncertain optimization of wind turbine airfoil. Study of influences of uncertain turbulence and geometric error. Interval-based uncertainty quantification coupled in optimization. Validation of airfoil robustness optimization. Flow field analysis by non-deterministic CFD approach. … (more)
- Is Part Of:
- Energy. Volume 244(2022)Part A
- Journal:
- Energy
- Issue:
- Volume 244(2022)Part A
- Issue Display:
- Volume 244, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 244
- Issue:
- 1
- Issue Sort Value:
- 2022-0244-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-04-01
- Subjects:
- Wind turbine -- Optimization -- Turbulence intensity -- Geometric error -- Interval -- Surrogate model
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2021.122623 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20852.xml