Optimization of Savonius wind turbine blades based on perturbed stochastic fractal search algorithm and Kriging surrogate model

ABSTRACT

The shape of its blades would significantly affect the energy capture ability of the Savonius wind turbine. This work proposed an efficient and intelligent optimization design method for the shape of the blade. Firstly, the blade’s shape is described parametrically using the cubic Bezier curve and then a certain number of design schemes in the design space are obtained using the Latin hypercube sampling technique, and the torque coefficients of these design schemes are evaluated using CFD simulation. Secondly, a Kriging model based on these design schemes and their corresponding torque coefficients is established. Thirdly, the optimal design scheme is obtained by taking the established Kriging model as an evaluation tool and taking the perturbed stochastic fractal search algorithm as an optimization tool and then verified using CFD. Through the above optimization method, a new type of blade is obtained. Compared with the traditional turbine with semi-circular blades, the turbine with the optimized blades can achieve about 9.03% improvement in energy capture efficiency at TSR = 1.

KEYWORDS:

• Savonius turbine
• Cubic Bezier curve
• Kriging
• Perturbed stochastic fractal search
• CFD

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant No. 51905284). Meanwhile, the authors sincerely thank the anonymous reviewers for their valuable comments.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

The work was supported by the National Natural Science Foundation of China [51905284]

Notes on contributors

Song Zhang

Song Zhang is a graduate student at the School of Mechanical Engineering, Qilu University of Technology, China. His research interest includes mechanical structure optimization and the utilization of renewable energy.

Shuhui Xu

Shuhui Xu got his PhD degree from the School of Mechanical Engineering, Shandong University, China, in 2017. He is working as an associate professor in School of Mechanical Engineering, Qilu University of Technology, China. His research field is focused on intelligent optimization, renewable energy, and computer aided design.