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The influence of yaw misalignment on turbine power output fluctuations and unsteady aerodynamic loads within wind farms

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  • Aju, Emmanuvel Joseph
  • Kumar, Devesh
  • Leffingwell, Melissa
  • Rotea, Mario A.
  • Jin, Yaqing

Abstract

Systematic wind tunnel experiments were performed to quantify the power output fluctuations and unsteady aerodynamic loads of modeled wind farms with 3 rows and 3 columns across various yaw angles. Time-resolved particle image velocimetry (PIV) was applied to characterize the flow statistics, while the power output and aerodynamic loads on the turbine tower were measured by a data logger and force cell at high temporal resolution. Results showed that the growth of the yaw misalignment angle mitigates the turbine power output fluctuation. However, this can increase the power fluctuations of downstream turbines. Measurements of the aerodynamic loads on the turbine tower revealed that the growth of the yaw angle significantly increased the fatigue loading in the side-force direction across all frequency components. At the same time, such impact was less distinctive for the thrust force. The dominating unsteady aerodynamic loads are always in the direction perpendicular to the rotor surface. Flow statistics demonstrated that yaw misalignment could effectively increase mean wake velocity, and integral time scale and reduce the turbulence intensity. Finally, theoretical models based on the coupling between turbine properties and local incoming flow statistics were derived to reveal the evolution of turbine power fluctuations and unsteady aerodynamic loads in the wake flow across various yaw misalignment.

Suggested Citation

  • Aju, Emmanuvel Joseph & Kumar, Devesh & Leffingwell, Melissa & Rotea, Mario A. & Jin, Yaqing, 2023. "The influence of yaw misalignment on turbine power output fluctuations and unsteady aerodynamic loads within wind farms," Renewable Energy, Elsevier, vol. 215(C).
  • Handle: RePEc:eee:renene:v:215:y:2023:i:c:s0960148123007917
    DOI: 10.1016/j.renene.2023.06.015
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    References listed on IDEAS

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    1. Fleming, Paul A. & Gebraad, Pieter M.O. & Lee, Sang & van Wingerden, Jan-Willem & Johnson, Kathryn & Churchfield, Matt & Michalakes, John & Spalart, Philippe & Moriarty, Patrick, 2014. "Evaluating techniques for redirecting turbine wakes using SOWFA," Renewable Energy, Elsevier, vol. 70(C), pages 211-218.
    2. Emmanuvel Joseph Aju & Dhanush Bhamitipadi Suresh & Yaqing Jin, 2020. "The Influence of Winglet Pitching on the Performance of a Model Wind Turbine: Aerodynamic Loads, Rotating Speed, and Wake Statistics," Energies, MDPI, vol. 13(19), pages 1-15, October.
    3. Nicolas Tobin & Ali M. Hamed & Leonardo P. Chamorro, 2015. "An Experimental Study on the Effects ofWinglets on the Wake and Performance of a ModelWind Turbine," Energies, MDPI, vol. 8(10), pages 1-18, October.
    4. Ciri, Umberto & Rotea, Mario A. & Leonardi, Stefano, 2017. "Model-free control of wind farms: A comparative study between individual and coordinated extremum seeking," Renewable Energy, Elsevier, vol. 113(C), pages 1033-1045.
    5. Zong, Haohua & Porté-Agel, Fernando, 2021. "Experimental investigation and analytical modelling of active yaw control for wind farm power optimization," Renewable Energy, Elsevier, vol. 170(C), pages 1228-1244.
    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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