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Aerodynamic wind-turbine rotor design using surrogate modeling and three-dimensional viscous–inviscid interaction technique

Author

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  • Sessarego, Matias
  • Ramos-García, Néstor
  • Yang, Hua
  • Shen, Wen Zhong

Abstract

In this paper a surrogate optimization methodology using a three-dimensional viscous-inviscid interaction code for the aerodynamic design of wind-turbine rotors is presented. The framework presents a unique approach because it does not require the commonly-used blade element momentum (BEM) method. The three-dimensional viscous-inviscid interaction code used here is the accurate and fast MIRAS code developed at the Technical University of Denmark. In comparison with BEM, MIRAS is a higher-fidelity aerodynamic tool and thus more computationally expensive as well. Designing a rotor using MIRAS instead of an inexpensive BEM code represents a challenge, which is resolved by using the proposed surrogate-based approach. As a verification case, the methodology is applied to design a model wind-turbine rotor and is compared in detail with the one designed with BEM. Results demonstrate that nearly identical aerodynamic performance can be achieved using the new design method and that the methodology is effective for the aerodynamic design of wind-turbine rotors.

Suggested Citation

  • Sessarego, Matias & Ramos-García, Néstor & Yang, Hua & Shen, Wen Zhong, 2016. "Aerodynamic wind-turbine rotor design using surrogate modeling and three-dimensional viscous–inviscid interaction technique," Renewable Energy, Elsevier, vol. 93(C), pages 620-635.
    • Handle: RePEc:eee:renene:v:93:y:2016:i:c:p:620-635
    DOI: 10.1016/j.renene.2016.03.027
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    References listed on IDEAS

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    1. Ramos-García, Néstor & Sørensen, Jens Nørkær & Shen, Wen Zhong, 2014. "Validation of a three-dimensional viscous–inviscid interactive solver for wind turbine rotors," Renewable Energy, Elsevier, vol. 70(C), pages 78-92.
    2. Ashuri, T. & Zaaijer, M.B. & Martins, J.R.R.A. & van Bussel, G.J.W. & van Kuik, G.A.M., 2014. "Multidisciplinary design optimization of offshore wind turbines for minimum levelized cost of energy," Renewable Energy, Elsevier, vol. 68(C), pages 893-905.
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    Cited by:

    1. Dai, Juchuan & Tan, Yayi & Shen, Xiangbin, 2019. "Investigation of energy output in mountain wind farm using multiple-units SCADA data," Applied Energy, Elsevier, vol. 239(C), pages 225-238.
    2. Hyeonjeong Ahn & Hyunkyoung Shin, 2020. "Experimental and Numerical Analysis of a 10 MW Floating Offshore Wind Turbine in Regular Waves," Energies, MDPI, vol. 13(10), pages 1-17, May.
    3. Yanfang Lv & Liping Sun & Michael M. Bernitsas & Mengjie Jiang & Hai Sun, 2021. "Modelling of a Flow-Induced Oscillation, Two-Cylinder, Hydrokinetic Energy Converter Based on Experimental Data," Energies, MDPI, vol. 14(4), pages 1-24, February.
    4. Sessarego, Matias & Feng, Ju & Ramos-García, Néstor & Horcas, Sergio González, 2020. "Design optimization of a curved wind turbine blade using neural networks and an aero-elastic vortex method under turbulent inflow," Renewable Energy, Elsevier, vol. 146(C), pages 1524-1535.
    5. Zhiqiang Yang & Minghui Yin & Yan Xu & Yun Zou & Zhao Yang Dong & Qian Zhou, 2016. "Inverse Aerodynamic Optimization Considering Impacts of Design Tip Speed Ratio for Variable-Speed Wind Turbines," Energies, MDPI, vol. 9(12), pages 1-15, December.
    6. Santhanam, Chandramouli & Riva, Riccardo & Knudsen, Torben, 2023. "A study of Stall-Induced Vibrations using Surrogate-Based Optimization," Renewable Energy, Elsevier, vol. 214(C), pages 201-215.
    7. Zhenye Sun & Matias Sessarego & Jin Chen & Wen Zhong Shen, 2017. "Design of the OffWindChina 5 MW Wind Turbine Rotor," Energies, MDPI, vol. 10(6), pages 1-20, June.

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