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Stochastic performance evaluation of horizontal axis wind turbine blades using non-deterministic CFD simulations

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  • Liu, ZhiYi
  • Wang, XiaoDong
  • Kang, Shun

Abstract

In this paper, non-deterministic CFD (computational fluid dynamics) simulations have been performed to investigate the uncertain effects of stochastic boundary conditions on the aerodynamic performance of wind turbines. A NIPRC (non-intrusive probabilistic collocation) method is employed, which is coupled with a commercial flow solver. A 2D (two-dimensional) airfoil case is used to validate the non-deterministic simulation, where the angle of attack is considered as an uncertain parameter in a Gaussian distribution. The simulation results are compared with Monte Carlo simulation results. Based on the validation, non-deterministic CFD simulations were performed on a 3D (three-dimensional) wind turbine blades case, where the wind speed is considered as an uncertain parameter. The discussions mainly focus on the total performance variations and the uncertainty propagation in the fluid field. The simulation results show that the input uncertainty of the inlet velocity results in a high variation zone in the pressure distribution near the blade root, and which decreases from the root to the tip. With the wind speed increases, flow separation is observed. The separation vortex regions correspond to the maximum variation area, and the maximum variation extends to the trailing edge even to the whole suction side.

Suggested Citation

  • Liu, ZhiYi & Wang, XiaoDong & Kang, Shun, 2014. "Stochastic performance evaluation of horizontal axis wind turbine blades using non-deterministic CFD simulations," Energy, Elsevier, vol. 73(C), pages 126-136.
    • Handle: RePEc:eee:energy:v:73:y:2014:i:c:p:126-136
    DOI: 10.1016/j.energy.2014.05.107
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    Cited by:

    1. Carlo Cravero & Davide De Domenico & Davide Marsano, 2023. "Uncertainty Quantification Analysis of Exhaust Gas Plume in a Crosswind," Energies, MDPI, vol. 16(8), pages 1-22, April.
    2. Kun, Wang & Fu, Chen & Jianyang, Yu & Yanping, Song, 2020. "Nested sparse-grid Stochastic Collocation Method for uncertainty quantification of blade stagger angle," Energy, Elsevier, vol. 201(C).
    3. Wang, Haipeng & Zhang, Bo & Qiu, Qinggang & Xu, Xiang, 2017. "Flow control on the NREL S809 wind turbine airfoil using vortex generators," Energy, Elsevier, vol. 118(C), pages 1210-1221.
    4. Rocha, P. A. Costa & Rocha, H. H. Barbosa & Carneiro, F. O. Moura & da Silva, M. E. Vieira & de Andrade, C. Freitas, 2016. "A case study on the calibration of the k–ω SST (shear stress transport) turbulence model for small scale wind turbines designed with cambered and symmetrical airfoils," Energy, Elsevier, vol. 97(C), pages 144-150.
    5. Daróczy, László & Janiga, Gábor & Petrasch, Klaus & Webner, Michael & Thévenin, Dominique, 2015. "Comparative analysis of turbulence models for the aerodynamic simulation of H-Darrieus rotors," Energy, Elsevier, vol. 90(P1), pages 680-690.
    6. Xia, Zhiheng & Luo, Jiaqi & Liu, Feng, 2019. "Statistical evaluation of performance impact of flow variations for a transonic compressor rotor blade," Energy, Elsevier, vol. 189(C).
    7. Salehi, Saeed & Nilsson, Håkan, 2022. "Effects of uncertainties in positioning of PIV plane on validation of CFD results of a high-head Francis turbine model," Renewable Energy, Elsevier, vol. 193(C), pages 57-75.
    8. Arteaga-López, Ernesto & Ángeles-Camacho, Cesar & Bañuelos-Ruedas, Francisco, 2019. "Advanced methodology for feasibility studies on building-mounted wind turbines installation in urban environment: Applying CFD analysis," Energy, Elsevier, vol. 167(C), pages 181-188.
    9. Wang, Xiaojing & Zou, Zhengping, 2019. "Uncertainty analysis of impact of geometric variations on turbine blade performance," Energy, Elsevier, vol. 176(C), pages 67-80.
    10. Bai, Chi-Jeng & Wang, Wei-Cheng, 2016. "Review of computational and experimental approaches to analysis of aerodynamic performance in horizontal-axis wind turbines (HAWTs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 506-519.
    11. Daróczy, László & Janiga, Gábor & Thévenin, Dominique, 2016. "Analysis of the performance of a H-Darrieus rotor under uncertainty using Polynomial Chaos Expansion," Energy, Elsevier, vol. 113(C), pages 399-412.
    12. Li, Jinxing & Liu, Tianyuan & Zhu, Guangya & Li, Yunzhu & Xie, Yonghui, 2023. "Uncertainty quantification and aerodynamic robust optimization of turbomachinery based on graph learning methods," Energy, Elsevier, vol. 273(C).

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