Aerodynamic Optimization of the Archimedes Spiral Wind Turbine Blade Based on the Kriging Surrogate Model and Differential Evolution.
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| Title: | Aerodynamic Optimization of the Archimedes Spiral Wind Turbine Blade Based on the Kriging Surrogate Model and Differential Evolution. |
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| Authors: | Li, Mengyao1,2 (AUTHOR), Li, Zhi1,2 (AUTHOR), Xu, Shuhui1,2 (AUTHOR) xushuhui@qlu.edu.cn |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 10, p2298. 23p. |
| Subject Terms: | *Differential evolution, *Turbine blades, *Wind power, *Gaussian processes, *Computational fluid dynamics, *Wind turbine efficiency, *Computational aerodynamics |
| Abstract: | The Archimedes Spiral Wind Turbine (ASWT) is a novel horizontal axis wind turbine for urban low-wind-speed applications. To improve the wind energy capture efficiency of the ASWT, this study adopted a multivariable global optimization strategy. A differential evolution–Kriging surrogate model method was employed for blade structural optimization. The blade geometry was parametrically modeled, and three design variables were selected: spiral pitch, opening angle, and spiral rotation number (SRN). Latin hypercube sampling was used to generate sample points in the design space. The power coefficients (Cp) of all design samples were calculated by Computational Fluid Dynamics (CFD) simulations. A Kriging surrogate model was constructed to map the nonlinear relationship between the design variables and Cp. The optimal blade geometry was obtained by solving the surrogate model with differential evolution (DE) and validated by CFD. The results showed that at the design condition of a wind speed of 8 m/s and a tip speed ratio (TSR) of 1.875, the relative error between Kriging model predictions and CFD simulations was only 0.27%. The optimized blade achieved a Cp of 0.3085, representing a 4.78% improvement over the best sample blade, with both achieving their peak power coefficients at TSR = 1.875. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Abstract: | The Archimedes Spiral Wind Turbine (ASWT) is a novel horizontal axis wind turbine for urban low-wind-speed applications. To improve the wind energy capture efficiency of the ASWT, this study adopted a multivariable global optimization strategy. A differential evolution–Kriging surrogate model method was employed for blade structural optimization. The blade geometry was parametrically modeled, and three design variables were selected: spiral pitch, opening angle, and spiral rotation number (SRN). Latin hypercube sampling was used to generate sample points in the design space. The power coefficients (Cp) of all design samples were calculated by Computational Fluid Dynamics (CFD) simulations. A Kriging surrogate model was constructed to map the nonlinear relationship between the design variables and Cp. The optimal blade geometry was obtained by solving the surrogate model with differential evolution (DE) and validated by CFD. The results showed that at the design condition of a wind speed of 8 m/s and a tip speed ratio (TSR) of 1.875, the relative error between Kriging model predictions and CFD simulations was only 0.27%. The optimized blade achieved a Cp of 0.3085, representing a 4.78% improvement over the best sample blade, with both achieving their peak power coefficients at TSR = 1.875. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 19961073 |
| DOI: | 10.3390/en19102298 |
