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A robust optimization method for wind turbine blade integration based on modal parameterization
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PRE
AI
DOI：10.1080/15567036.2025.2547080.png)
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Abstract
En 中文
The aerodynamic performance of wind turbine blades is critical to wind energy conversion efficiency. However, geometric and operational uncertainties often cause deviations between actual and designed performance, affecting overall turbine efficiency. Traditional optimization methods typically neglect uncertainty as a design variable, treating objectives and constraints as deterministic values. Additionally, the high dimensionality of design parameters complicates robustness optimization. A common approach involves sequentially optimizing airfoil profiles prior to blade-level design, which limits the integration of feedback between local airfoil performance and overall blade aerodynamics. To address these challenges, this study proposes an integrated robustness optimization method based on modal parameterization, enabling direct blade shape optimization while incorporating uncertainty. Modal parameterization is employed to represent blade cross-sections, extract key design parameters, and quantify aerodynamic uncertainty using kernel density estimation. Compared to the baseline blade, the optimized design achieves a 4.01% increase in the mean annual energy production (AEP) and a 65.1% reduction in its standard deviation, indicating a significant improvement in performance and robustness to the assumed geometric perturbations. This approach enhances the robustness of wind turbine blade design and provides insights for robust optimization in other engineering applications.
Keywords:
Aerodynamics
annual energy production
robust optimization
uncertainty quantification
wind turbine blades
Journal
E
IF:
2.2
Papers:
512
Citations:
1.1W