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Sensitivity Analysis to Control the Far-Wake Unsteadiness Behind Turbines

Author

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  • Esteban Ferrer

    (ETSIAE (School of Aeronautics)—Universidad Politécnica de Madrid, Pza Cardenal Cisneros 3, E-28040 Madrid, Spain
    Center for Computational Simulation—Universidad Politécnica de Madrid, Boadilla del Monte, E-28660 Madrid, Spain)

  • Oliver M.F. Browne

    (Department of Aerospace and Mechanical Engineering, University of Arizona, Tucson, AZ 85721, USA)

  • Eusebio Valero

    (ETSIAE (School of Aeronautics)—Universidad Politécnica de Madrid, Pza Cardenal Cisneros 3, E-28040 Madrid, Spain
    Center for Computational Simulation—Universidad Politécnica de Madrid, Boadilla del Monte, E-28660 Madrid, Spain)

Abstract

We explore the stability of wakes arising from 2D flow actuators based on linear momentum actuator disc theory. We use stability and sensitivity analysis (using adjoints) to show that the wake stability is controlled by the Reynolds number and the thrust force (or flow resistance) applied through the turbine. First, we report that decreasing the thrust force has a comparable stabilising effect to a decrease in Reynolds numbers (based on the turbine diameter). Second, a discrete sensitivity analysis identifies two regions for suitable placement of flow control forcing, one close to the turbines and one far downstream. Third, we show that adding a localised control force, in the regions identified by the sensitivity analysis, stabilises the wake. Particularly, locating the control forcing close to the turbines results in an enhanced stabilisation such that the wake remains steady for significantly higher Reynolds numbers or turbine thrusts. The analysis of the controlled flow fields confirms that modifying the velocity gradient close to the turbine is more efficient to stabilise the wake than controlling the wake far downstream. The analysis is performed for the first flow bifurcation (at low Reynolds numbers) which serves as a foundation of the stabilization technique but the control strategy is tested at higher Reynolds numbers in the final section of the paper, showing enhanced stability for a turbulent flow case.

Suggested Citation

  • Esteban Ferrer & Oliver M.F. Browne & Eusebio Valero, 2017. "Sensitivity Analysis to Control the Far-Wake Unsteadiness Behind Turbines," Energies, MDPI, vol. 10(10), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:10:p:1599-:d:114890
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    References listed on IDEAS

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    1. McAdam, R.A. & Houlsby, G.T. & Oldfield, M.L.G., 2013. "Experimental measurements of the hydrodynamic performance and structural loading of the transverse horizontal axis water turbine: Part 2," Renewable Energy, Elsevier, vol. 59(C), pages 141-149.
    2. McAdam, R.A. & Houlsby, G.T. & Oldfield, M.L.G., 2013. "Experimental measurements of the hydrodynamic performance and structural loading of the Transverse Horizontal Axis Water Turbine: Part 1," Renewable Energy, Elsevier, vol. 59(C), pages 105-114.
    3. Myers, L.E. & Bahaj, A.S., 2012. "An experimental investigation simulating flow effects in first generation marine current energy converter arrays," Renewable Energy, Elsevier, vol. 37(1), pages 28-36.
    4. Minh Quan Duong & Francesco Grimaccia & Sonia Leva & Marco Mussetta & Kim Hung Le, 2015. "Improving Transient Stability in a Grid-Connected Squirrel-Cage Induction Generator Wind Turbine System Using a Fuzzy Logic Controller," Energies, MDPI, vol. 8(7), pages 1-22, June.
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    Cited by:

    1. De Cillis, Giovanni & Cherubini, Stefania & Semeraro, Onofrio & Leonardi, Stefano & De Palma, Pietro, 2022. "Stability and optimal forcing analysis of a wind turbine wake: Comparison with POD," Renewable Energy, Elsevier, vol. 181(C), pages 765-785.
    2. David Bastine & Lukas Vollmer & Matthias Wächter & Joachim Peinke, 2018. "Stochastic Wake Modelling Based on POD Analysis," Energies, MDPI, vol. 11(3), pages 1-29, March.
    3. Yuquan Zhang & Jisheng Zhang & Yuan Zheng & Chunxia Yang & Wei Zang & E. Fernandez-Rodriguez, 2017. "Experimental Analysis and Evaluation of the Numerical Prediction of Wake Characteristics of Tidal Stream Turbine," Energies, MDPI, vol. 10(12), pages 1-11, December.
    4. Manuel Viqueira-Moreira & Esteban Ferrer, 2020. "Insights into the Aeroacoustic Noise Generation for Vertical Axis Turbines in Close Proximity," Energies, MDPI, vol. 13(16), pages 1-18, August.
    5. Zhenzhou Shao & Ying Wu & Li Li & Shuang Han & Yongqian Liu, 2019. "Multiple Wind Turbine Wakes Modeling Considering the Faster Wake Recovery in Overlapped Wakes," Energies, MDPI, vol. 12(4), pages 1-14, February.

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