Post-Optimum Sensitivity Analysis with Automatically Tuned Numerical Gradients Applied to Swept Wind Turbine Blades

Post-Optimum Sensitivity Analysis (POSA) extends numerical design optimization to provide additional information on how the design and performance would change if various parameters and constraints were varied. POSA is challenging since it typically requires accurate gradients and gradient-based opt...

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Bibliographic Details
Published in:Energies (Basel) 2022-05, Vol.15 (9), p.2998
Main Authors: McWilliam, Michael K., Dicholkar, Antariksh C., Zahle, Frederik, Kim, Taeseong
Format: Article
Language:English
Subjects:
Algorithms
Bending moments
Blade tips
Civil engineering
Design
Design optimization
Driving ability
Energy
Materials failure
optimization
Sensitivity analysis
Statistical methods
Turbine blades
Turbines
Wind power
Wind speed
wind turbines
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Summary:Post-Optimum Sensitivity Analysis (POSA) extends numerical design optimization to provide additional information on how the design and performance would change if various parameters and constraints were varied. POSA is challenging since it typically requires accurate gradients and gradient-based optimization problems that provide Lagrange multipliers. To overcome this problem, this paper introduces a technique to automatically tune gradients with statistical methods and algorithms to calculate the Lagrange multipliers after an optimization. This allows these methods to be applied to problems with noisy gradients or problems solved with gradient-free optimization algorithms. These methods have been applied to swept wind turbine blades. Swept blades can reduce wind turbine loads by twisting out of the wind when the wind speed increases. The methods have shown that introducing design freedom in the sweep, blade root flap-wise bending moments and blade tip deflection has a weaker influence on the design. Instead, blade root torsion moment and material failure become the driving constraints.
ISSN:1996-1073
1996-1073
DOI:10.3390/en15092998