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A Proper-Orthogonal-Decomposition (POD) Study of the Wake Characteristics behind a Wind Turbine Model

Author

Listed:
  • Pavithra Premaratne

    (Department of Physics and Engineering, Central College, Pella, IA 50219, USA)

  • Wei Tian

    (School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Hui Hu

    (Department of Aerospace Engineering, Iowa State University, Ames, IA 50012, USA)

Abstract

A comprehensive study was performed to analyze turbine wake characteristics by using a Proper-Orthogonal-Decomposition (POD) method to identify the dominant flow features from a comprehensive experimental database. The wake flow characteristics behind a typical three-bladed horizontal-axis wind turbine (HAWT) were measured in a large-scale wind tunnel with a scaled turbine model placed in a typical offshore Atmospheric Boundary Layer (ABL) wind under a neutral stability condition. A high-resolution Particle Image Velocimetry (PIV) system was used to achieve detailed flow field measurements to characterize the turbulent flows and wake vortex structures behind the turbine model. Statistically averaged measurements revealed the presence of the characteristic helical-tip vortex filament along with a unique secondary vortex filament emanating from 60% of the blade span measured from the hub. Both filaments breakup in the near-wake region (~0.6 rotor diameter downstream) to form shear layers, contrary to previous computational and experimental observations in which vortex filaments break up in the far wake. A Proper-Orthogonal-Decomposition (POD) analysis, based on both velocity and vorticity-based formulations, was used to extract the coherent flow structures, predominantly comprised of tip and midspan vortex elements. The reconstructions showed coherence in the flow field prior to the vortex breakup which subsequently degraded in the turbulent shear layer. The accuracy of the POD reconstructions was validated qualitatively by comparing the prediction results between the velocity and vorticity-based formulations as well as the phase-averaged PIV measurement results. This early vortex breakup was attributed to the reduced pitch between consecutive helical turns, the proximity between midspan filaments and blade tips as well as the turbulence intensity of the incoming boundary layer wind.

Suggested Citation

  • Pavithra Premaratne & Wei Tian & Hui Hu, 2022. "A Proper-Orthogonal-Decomposition (POD) Study of the Wake Characteristics behind a Wind Turbine Model," Energies, MDPI, vol. 15(10), pages 1-22, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3596-:d:815507
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    References listed on IDEAS

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    1. Lignarolo, L.E.M. & Ragni, D. & Krishnaswami, C. & Chen, Q. & Simão Ferreira, C.J. & van Bussel, G.J.W., 2014. "Experimental analysis of the wake of a horizontal-axis wind-turbine model," Renewable Energy, Elsevier, vol. 70(C), pages 31-46.
    2. Liu, Weiqi & Liu, Weixing & Zhang, Liang & Sheng, Qihu & Zhou, Binzhen, 2018. "A numerical model for wind turbine wakes based on the vortex filament method," Energy, Elsevier, vol. 157(C), pages 561-570.
    3. Adaramola, M.S. & Krogstad, P.-Å., 2011. "Experimental investigation of wake effects on wind turbine performance," Renewable Energy, Elsevier, vol. 36(8), pages 2078-2086.
    4. Wang, Zhenyu & Ozbay, Ahmet & Tian, Wei & Hu, Hui, 2018. "An experimental study on the aerodynamic performances and wake characteristics of an innovative dual-rotor wind turbine," Energy, Elsevier, vol. 147(C), pages 94-109.
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    1. Navid Belvasi & Frances Judge & Jimmy Murphy & Cian Desmond, 2022. "Analysis of Floating Offshore Wind Platform Hydrodynamics Using Underwater SPIV: A Review," Energies, MDPI, vol. 15(13), pages 1-26, June.

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