Design and optimization of airfoils and a 20 kW wind turbine using multi-objective genetic algorithm and HARP_Opt code
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DOI: 10.1016/j.renene.2018.08.040
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- Wenbin Su & Hongbo Wei & Penghua Guo & Qiao Hu & Mengyuan Guo & Yuanjie Zhou & Dayu Zhang & Zhufeng Lei & Chaohui Wang, 2021. "Research on Hydraulic Conversion Technology of Small Ocean Current Turbines for Low-Flow Current Energy Generation," Energies, MDPI, vol. 14(20), pages 1-19, October.
- Du, Qiuwan & Li, Yunzhu & Yang, Like & Liu, Tianyuan & Zhang, Di & Xie, Yonghui, 2022. "Performance prediction and design optimization of turbine blade profile with deep learning method," Energy, Elsevier, vol. 254(PA).
- Mauro, S. & Lanzafame, R. & Messina, M. & Brusca, S., 2023. "On the importance of the root-to-hub adapter effects on HAWT performance: A CFD-BEM numerical investigation," Energy, Elsevier, vol. 275(C).
- Al-Sanad, Shaikha & Wang, Lin & Parol, Jafarali & Kolios, Athanasios, 2021. "Reliability-based design optimisation framework for wind turbine towers," Renewable Energy, Elsevier, vol. 167(C), pages 942-953.
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Keywords
Low Reynolds number airfoils; Genetic algorithm; Wind turbine; Blade design;All these keywords.
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