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Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects

Author

Listed:
  • Jay P. Goit

    (Department of Mechanical Engineering, University of Leuven, Celestijnenlaan 300A, Leuven B3001, Belgium)

  • Wim Munters

    (Department of Mechanical Engineering, University of Leuven, Celestijnenlaan 300A, Leuven B3001, Belgium)

  • Johan Meyers

    (Department of Mechanical Engineering, University of Leuven, Celestijnenlaan 300A, Leuven B3001, Belgium)

Abstract

We investigate the use of optimal coordinated control techniques in large eddy simulations of wind farm boundary layer interaction with the aim of increasing the total energy extraction in wind farms. The individual wind turbines are considered as flow actuators, and their energy extraction is dynamically regulated in time, so as to optimally influence the flow field. We extend earlier work on wind farm optimal control in the fully-developed regime (Goit and Meyers 2015, J. Fluid Mech. 768, 5–50) to a ‘finite’ wind farm case, in which entrance effects play an important role. For the optimal control, a receding horizon framework is employed in which turbine thrust coefficients are optimized in time and per turbine. Optimization is performed with a conjugate gradient method, where gradients of the cost functional are obtained using adjoint large eddy simulations. Overall, the energy extraction is increased 7% by the optimal control. This increase in energy extraction is related to faster wake recovery throughout the farm. For the first row of turbines, the optimal control increases turbulence levels and Reynolds stresses in the wake, leading to better wake mixing and an inflow velocity for the second row that is significantly higher than in the uncontrolled case. For downstream rows, the optimal control mainly enhances the sideways mean transport of momentum. This is different from earlier observations by Goit and Meyers (2015) in the fully-developed regime, where mainly vertical transport was enhanced.

Suggested Citation

  • Jay P. Goit & Wim Munters & Johan Meyers, 2016. "Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects," Energies, MDPI, vol. 9(1), pages 1-20, January.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:1:p:29-:d:61778
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    References listed on IDEAS

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    1. Hansen, Anca D. & Sørensen, Poul & Iov, Florin & Blaabjerg, Frede, 2006. "Centralised power control of wind farm with doubly fed induction generators," Renewable Energy, Elsevier, vol. 31(7), pages 935-951.
    2. Mohd Ashraf Ahmad & Shun-ichi Azuma & Toshiharu Sugie, 2014. "A Model-Free Approach for Maximizing Power Production of Wind Farm Using Multi-Resolution Simultaneous Perturbation Stochastic Approximation," Energies, MDPI, vol. 7(9), pages 1-23, August.
    3. Stevens, Richard J.A.M. & Graham, Jason & Meneveau, Charles, 2014. "A concurrent precursor inflow method for Large Eddy Simulations and applications to finite length wind farms," Renewable Energy, Elsevier, vol. 68(C), pages 46-50.
    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. Mahdi Abkar & Fernando Porté-Agel, 2013. "The Effect of Free-Atmosphere Stratification on Boundary-Layer Flow and Power Output from Very Large Wind Farms," Energies, MDPI, vol. 6(5), pages 1-24, April.
    6. 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.
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    Cited by:

    1. 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.
    2. Aditya H. Bhatt & Mireille Rodrigues & Federico Bernardoni & Stefano Leonardi & Armin Zare, 2023. "Stochastic Dynamical Modeling of Wind Farm Turbulence," Energies, MDPI, vol. 16(19), pages 1-24, September.
    3. van den Broek, Maarten J. & De Tavernier, Delphine & Sanderse, Benjamin & van Wingerden, Jan-Willem, 2022. "Adjoint optimisation for wind farm flow control with a free-vortex wake model," Renewable Energy, Elsevier, vol. 201(P1), pages 752-765.
    4. Yolanda Vidal & Leonardo Acho & Ignasi Cifre & Àlex Garcia & Francesc Pozo & José Rodellar, 2017. "Wind Turbine Synchronous Reset Pitch Control," Energies, MDPI, vol. 10(6), pages 1-16, June.
    5. Wim Munters & Johan Meyers, 2018. "Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization," Energies, MDPI, vol. 11(1), pages 1-32, January.

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