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Wind Turbine Wake Mitigation through Blade Pitch Offset

Author

Listed:
  • Deepu Dilip

    (Wind Engineering and Renewable Energy Laboratory (WIRE), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland)

  • Fernando Porté-Agel

    (Wind Engineering and Renewable Energy Laboratory (WIRE), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland)

Abstract

The reduction in power output associated with complex turbine-wake interactions in wind farms necessitates the development of effective wake mitigation strategies. One approach to this end entails the downregulation of individual turbines from its maximum power point with the objective of optimizing the overall wind farm productivity. Downregulation via blade pitch offset has been of interest as a potential strategy, though the viability of this method is still not clear, especially in regard to its sensitivity to ambient turbulence. In this study, large-eddy simulations of a two-turbine arrangement, with the second turbine in the full wake of the first, were performed. The effects of varying the blade pitch angle of the upstream turbine on its wake characteristics, as well as the combined power of the two, were investigated. Of specific interest was the effect of turbulence intensity of the inflow on the efficacy of this method. Results showed enhanced wake recovery associated with pitching to stall, as opposed to pitching to feather, which delayed wake recovery. The increased wake recovery resulted in a noticeable increase in the power of the two-turbine configuration, only in conditions characterized by low turbulence in the incoming flow. Nevertheless, the low turbulence scenarios where the use of this method is favorable, are expected in realistic wind farms, suggesting its possible application for improved power generation.

Suggested Citation

  • Deepu Dilip & Fernando Porté-Agel, 2017. "Wind Turbine Wake Mitigation through Blade Pitch Offset," Energies, MDPI, vol. 10(6), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:6:p:757-:d:99940
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    References listed on IDEAS

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    Cited by:

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    4. Yin, Xiuxing & Zhang, Wencan & Jiang, Zhansi & Pan, Li, 2020. "Data-driven multi-objective predictive control of offshore wind farm based on evolutionary optimization," Renewable Energy, Elsevier, vol. 160(C), pages 974-986.
    5. Javier Serrano González & Bruno López & Martín Draper, 2021. "Optimal Pitch Angle Strategy for Energy Maximization in Offshore Wind Farms Considering Gaussian Wake Model," Energies, MDPI, vol. 14(4), pages 1-18, February.
    6. Xiong, Xue-Lu & Lyu, Pin & Chen, Wen-Li & Li, Hui, 2020. "Self-similarity in the wake of a semi-submersible offshore wind turbine considering the interaction with the wake of supporting platform," Renewable Energy, Elsevier, vol. 156(C), pages 328-341.
    7. Jong-Hyeon Shin & Jong-Hwi Lee & Se-Myong Chang, 2019. "A Simplified Numerical Model for the Prediction of Wake Interaction in Multiple Wind Turbines," Energies, MDPI, vol. 12(21), pages 1-14, October.
    8. 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.
    9. De-Zhi Wei & Ni-Na Wang & De-Cheng Wan, 2021. "Modelling Yawed Wind Turbine Wakes: Extension of a Gaussian-Based Wake Model," Energies, MDPI, vol. 14(15), pages 1-26, July.

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