A Novel Parametric Modeling Method and Optimal Design for Savonius Wind Turbines

Baoshou Zhang, Baowei Song, Zhaoyong Mao, Wenlong Tian, Boyang Li and Bo Li
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Baoshou Zhang: School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China
Baowei Song: School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China
Zhaoyong Mao: School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China
Wenlong Tian: School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China
Boyang Li: College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, Shandong, China
Bo Li: School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China

Energies, 2017, vol. 10, issue 3, 1-20

Abstract: Under the inspiration of polar coordinates, a novel parametric modeling and optimization method for Savonius wind turbines was proposed to obtain the highest power output, in which a quadratic polynomial curve was bent to describe a blade. Only two design parameters are needed for the shape-complicated blade. Therefore, this novel method reduces sampling scale. A series of transient simulations was run to get the optimal performance coefficient (power coefficient C p) for different modified turbines based on computational fluid dynamics (CFD) method. Then, a global response surface model and a more precise local response surface model were created according to Kriging Method. These models defined the relationship between optimization objective Cp and design parameters. Particle swarm optimization (PSO) algorithm was applied to find the optimal design based on these response surface models. Finally, the optimal Savonius blade shaped like a “hook” was obtained. Cm (torque coefficient), Cp and flow structure were compared for the optimal design and the classical design. The results demonstrate that the optimal Savonius turbine has excellent comprehensive performance. The power coefficient Cp is significantly increased from 0.247 to 0.262 (6% higher). The weight of the optimal blade is reduced by 17.9%.

Keywords: Savonius wind turbine; parametric model; polar coordinates; computational fluid dynamics (CFD); Kriging method; particle swarm optimization (PSO) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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