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A New Miniature Wind Turbine for Wind Tunnel Experiments. Part II: Wake Structure and Flow Dynamics

Author

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  • Majid Bastankhah

    (Wind Engineering and Renewable Energy Laboratory (WIRE), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-ENAC-IIE-WIRE, 1015 Lausanne, Switzerland)

  • Fernando Porté-Agel

    (Wind Engineering and Renewable Energy Laboratory (WIRE), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-ENAC-IIE-WIRE, 1015 Lausanne, Switzerland)

Abstract

An optimized three-bladed horizontal-axis miniature wind turbine, called WiRE-01, with the rotor diameter of 15 cm is designed and fully characterized in Part I of this study. In the current part of the study, we investigate the interaction of the turbine with a turbulent boundary layer. The comparison of the spectral density of the thrust force and the one of the incoming velocity revealed new insights on the use of turbine characteristics to estimate incoming flow conditions. High-resolution stereoscopic particle image-velocimetry (S-PIV) measurements were also performed in the wake of the turbine operating at optimal conditions. Detailed information on the velocity and turbulence structure of the turbine wake is presented and discussed, which can serve as a complete dataset for the validation of numerical models. The PIV data are also used to better understand the underlying mechanisms leading to unsteady loads on a downstream turbine at different streamwise and spanwise positions. To achieve this goal, a new method is developed to quantify and compare the effect of both turbulence and mean shear on the moment of the incoming momentum flux for a hypothetical turbine placed downstream. The results show that moment fluctuations caused by turbulence are bigger under full-wake conditions, whereas those caused by mean shear are clearly dominant under partial-wake conditions. Especial emphasis is also placed on how the mean wake flow distribution is affected by wake meandering. Conditional averaging based on the instantaneous position of the wake center revealed that when the wake meanders laterally to one side, a high-speed region exists on the opposite side. The results show that, due to this high-speed region, large lateral meandering motions do not lead to the expansion of the mean wake cross-section in the lateral direction.

Suggested Citation

  • Majid Bastankhah & Fernando Porté-Agel, 2017. "A New Miniature Wind Turbine for Wind Tunnel Experiments. Part II: Wake Structure and Flow Dynamics," Energies, MDPI, vol. 10(7), pages 1-19, July.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:923-:d:103521
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    References listed on IDEAS

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    1. Sina Shamsoddin & Fernando Porté-Agel, 2016. "A Large-Eddy Simulation Study of Vertical Axis Wind Turbine Wakes in the Atmospheric Boundary Layer," Energies, MDPI, vol. 9(5), pages 1-23, May.
    2. Yu-Ting Wu & Fernando Porté-Agel, 2012. "Atmospheric Turbulence Effects on Wind-Turbine Wakes: An LES Study," Energies, MDPI, vol. 5(12), pages 1-23, December.
    3. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    4. Fernando Porté-Agel & Yu-Ting Wu & Chang-Hung Chen, 2013. "A Numerical Study of the Effects of Wind Direction on Turbine Wakes and Power Losses in a Large Wind Farm," Energies, MDPI, vol. 6(10), pages 1-17, October.
    5. Leonardo P. Chamorro & Fernando Porté-Agel, 2011. "Turbulent Flow Inside and Above a Wind Farm: A Wind-Tunnel Study," Energies, MDPI, vol. 4(11), pages 1-21, November.
    6. Majid Bastankhah & Fernando Porté-Agel, 2017. "A New Miniature Wind Turbine for Wind Tunnel Experiments. Part I: Design and Performance," Energies, MDPI, vol. 10(7), pages 1-19, July.
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    Cited by:

    1. Dong, Xinghui & Li, Jia & Gao, Di & Zheng, Kai, 2021. "Wind speed modeling for cascade clusters of wind turbines Part 2: Wind speed reduction and aggregation superposition," Energy, Elsevier, vol. 215(PB).
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    3. Rosario Lanzafame & Stefano Mauro & Michele Messina & Sebastian Brusca, 2020. "Development and Validation of CFD 2D Models for the Simulation of Micro H-Darrieus Turbines Subjected to High Boundary Layer Instabilities," Energies, MDPI, vol. 13(21), pages 1-23, October.
    4. Zygmunt Szczerba & Piotr Szczerba & Kamil Szczerba & Marek Szumski & Krzysztof Pytel, 2023. "Wind Tunnel Experimental Study on the Efficiency of Vertical-Axis Wind Turbines via Analysis of Blade Pitch Angle Influence," Energies, MDPI, vol. 16(13), pages 1-21, June.
    5. Tristan Revaz & Fernando Porté-Agel, 2021. "Large-Eddy Simulation of Wind Turbine Flows: A New Evaluation of Actuator Disk Models," Energies, MDPI, vol. 14(13), pages 1-22, June.
    6. Yu-Ting Wu & Chang-Yu Lin & Che-Ming Hsu, 2020. "An Experimental Investigation of Wake Characteristics and Power Generation Efficiency of a Small Wind Turbine under Different Tip Speed Ratios," Energies, MDPI, vol. 13(8), pages 1-19, April.
    7. Mou Lin & Fernando Porté-Agel, 2019. "Large-Eddy Simulation of Yawed Wind-Turbine Wakes: Comparisons with Wind Tunnel Measurements and Analytical Wake Models," Energies, MDPI, vol. 12(23), pages 1-18, November.
    8. Francesco Mazzeo & Derek Micheletto & Alessandro Talamelli & Antonio Segalini, 2022. "An Experimental Study on a Wind Turbine Rotor Affected by Pitch Imbalance," Energies, MDPI, vol. 15(22), pages 1-16, November.
    9. He, Ruiyang & Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2022. "Wind tunnel tests for wind turbines: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    10. Öztürk, Buğrahan & Hassanein, Abdelrahman & Akpolat, M Tuğrul & Abdulrahim, Anas & Perçin, Mustafa & Uzol, Oğuz, 2023. "On the wake characteristics of a model wind turbine and a porous disc: Effects of freestream turbulence intensity," Renewable Energy, Elsevier, vol. 212(C), pages 238-250.
    11. Ingrid Neunaber & Michael Hölling & Richard J. A. M. Stevens & Gerard Schepers & Joachim Peinke, 2020. "Distinct Turbulent Regions in the Wake of a Wind Turbine and Their Inflow-Dependent Locations: The Creation of a Wake Map," Energies, MDPI, vol. 13(20), pages 1-20, October.
    12. Dongqin Zhang & Yang Liang & Chao Li & Yiqing Xiao & Gang Hu, 2022. "Applicability of Wake Models to Predictions of Turbine-Induced Velocity Deficit and Wind Farm Power Generation," Energies, MDPI, vol. 15(19), pages 1-26, October.
    13. Tristan Revaz & Mou Lin & Fernando Porté-Agel, 2020. "Numerical Framework for Aerodynamic Characterization of Wind Turbine Airfoils: Application to Miniature Wind Turbine WiRE-01," Energies, MDPI, vol. 13(21), pages 1-18, October.
    14. Subbulakshmi, A. & Verma, Mohit & Keerthana, M. & Sasmal, Saptarshi & Harikrishna, P. & Kapuria, Santosh, 2022. "Recent advances in experimental and numerical methods for dynamic analysis of floating offshore wind turbines — An integrated review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    15. Huilai Ren & Xiaodong Zhang & Shun Kang & Sichao Liang, 2018. "Actuator Disc Approach of Wind Turbine Wake Simulation Considering Balance of Turbulence Kinetic Energy," Energies, MDPI, vol. 12(1), pages 1-19, December.
    16. Nikolaos Chrysochoidis-Antsos & Gerard J.W. van Bussel & Jan Bozelie & Sander M. Mertens & Ad J.M. van Wijk, 2021. "Performance Characteristics of A Micro Wind Turbine Integrated on A Noise Barrier," Energies, MDPI, vol. 14(5), pages 1-29, February.
    17. Majid Bastankhah & Fernando Porté-Agel, 2017. "A New Miniature Wind Turbine for Wind Tunnel Experiments. Part I: Design and Performance," Energies, MDPI, vol. 10(7), pages 1-19, July.

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