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Optimization of Blade Geometry of Savonius Hydrokinetic Turbine Based on Genetic Algorithm

by Jiahao Lu1, Fangfang Zhang1, Weilong Guang1, Yanzhao Wu1, Ran Tao1,2,*, Xiaoqin Li1,2, Ruofu Xiao1,2

1 College of Water Resources and Civil Engineering, China Agricultural University, Beijing, 100083, China
2 Beijing Engineering Research Center of Safety and Energy Saving Technology for Water Supply Network System, China Agricultural University, Beijing, 100083, China

* Corresponding Author: Ran Tao. Email: email

Energy Engineering 2023, 120(12), 2819-2837. https://doi.org/10.32604/ee.2023.042287

Abstract

Savonius hydrokinetic turbine is a kind of turbine set which is suitable for low-velocity conditions. Unlike conventional turbines, Savonius turbines employ S-shaped blades and have simple internal structures. Therefore, there is a large space for optimizing the blade geometry. In this study, computational fluid dynamics (CFD) numerical simulation and genetic algorithm (GA) were used for the optimal design. The optimization strategies and methods were determined by comparing the results calculated by CFD with the experimental results. The weighted objective function was constructed with the maximum power coefficient Cp and the high-power coefficient range R under multiple working conditions. GA helps to find the optimal individual of the objective function. Compared the optimal scheme with the initial scheme, the overlap ratio β increased from 0.2 to 0.202, and the clearance ratio ε increased from 0 to 0.179, the blade circumferential angle γ increased from 0° to 27°, the blade shape extended more towards the spindle. The overall power of Savonius turbines was maintained at a high level over 22%, R also increased from 0.73 to 1.02. In comparison with the initial scheme, the energy loss of the optimal scheme at high blade tip speed is greatly reduced, and this reduction is closely related to the optimization of blade geometry. As R becomes larger, Savonius turbines can adapt to the overall working conditions and meet the needs of its work in low flow rate conditions. The results of this paper can be used as a reference for the hydrodynamic optimization of Savonius turbine runners.

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APA Style
Lu, J., Zhang, F., Guang, W., Wu, Y., Tao, R. et al. (2023). Optimization of blade geometry of savonius hydrokinetic turbine based on genetic algorithm. Energy Engineering, 120(12), 2819-2837. https://doi.org/10.32604/ee.2023.042287
Vancouver Style
Lu J, Zhang F, Guang W, Wu Y, Tao R, Li X, et al. Optimization of blade geometry of savonius hydrokinetic turbine based on genetic algorithm. Energ Eng. 2023;120(12):2819-2837 https://doi.org/10.32604/ee.2023.042287
IEEE Style
J. Lu et al., “Optimization of Blade Geometry of Savonius Hydrokinetic Turbine Based on Genetic Algorithm,” Energ. Eng., vol. 120, no. 12, pp. 2819-2837, 2023. https://doi.org/10.32604/ee.2023.042287



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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