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Development of a Computational System to Improve Wind Farm Layout, Part I: Model Validation and Near Wake Analysis

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  • Rafael V. Rodrigues

    (Department of Mechanical and Materials Engineering, University of Denver, Denver, CO 80210, USA)

  • Corinne Lengsfeld

    (Department of Mechanical and Materials Engineering, University of Denver, Denver, CO 80210, USA)

Abstract

The first part of this work describes the validation of a wind turbine farm Computational Fluid Dynamics (CFD) simulation using literature velocity wake data from the MEXICO (Model Experiments in Controlled Conditions) experiment. The work is intended to establish a computational framework from which to investigate wind farm layout, seeking to validate the simulation and identify parameters influencing the wake. A CFD model was designed to mimic the MEXICO rotor experimental conditions and simulate new operating conditions with regards to tip speed ratio and pitch angle. The validation showed that the computational results qualitatively agree with the experimental data. Considering the designed tip speed ratio (TSR) of 6.6, the deficit of velocity in the wake remains at rate of approximately 15% of the free-stream velocity per rotor diameter regardless of the free-stream velocity applied. Moreover, analysis of a radial traverse right behind the rotor showed an increase of 20% in the velocity deficit as the TSR varied from TSR = 6 to TSR = 10, corresponding to an increase ratio of approximately 5% m·s −1 per dimensionless unit of TSR. We conclude that the near wake characteristics of a wind turbine are strongly influenced by the TSR and the pitch angle.

Suggested Citation

  • Rafael V. Rodrigues & Corinne Lengsfeld, 2019. "Development of a Computational System to Improve Wind Farm Layout, Part I: Model Validation and Near Wake Analysis," Energies, MDPI, vol. 12(5), pages 1-24, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:940-:d:212986
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    References listed on IDEAS

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    1. Shives, Michael & Crawford, Curran, 2016. "Adapted two-equation turbulence closures for actuator disk RANS simulations of wind & tidal turbine wakes," Renewable Energy, Elsevier, vol. 92(C), pages 273-292.
    2. Sarlak, H. & Meneveau, C. & Sørensen, J.N., 2015. "Role of subgrid-scale modeling in large eddy simulation of wind turbine wake interactions," Renewable Energy, Elsevier, vol. 77(C), pages 386-399.
    3. Zhong, Hongmin & Du, Pingan & Tang, Fangning & Wang, Li, 2015. "Lagrangian dynamic large-eddy simulation of wind turbine near wakes combined with an actuator line method," Applied Energy, Elsevier, vol. 144(C), pages 224-233.
    4. Park, Jinkyoo & Law, Kincho H., 2016. "A data-driven, cooperative wind farm control to maximize the total power production," Applied Energy, Elsevier, vol. 165(C), pages 151-165.
    5. Sturge, D. & Sobotta, D. & Howell, R. & While, A. & Lou, J., 2015. "A hybrid actuator disc – Full rotor CFD methodology for modelling the effects of wind turbine wake interactions on performance," Renewable Energy, Elsevier, vol. 80(C), pages 525-537.
    6. Son, Eunkuk & Lee, Seungmin & Hwang, Byeongho & Lee, Soogab, 2014. "Characteristics of turbine spacing in a wind farm using an optimal design process," Renewable Energy, Elsevier, vol. 65(C), pages 245-249.
    7. Hossain, M.Z. & Hirahara, H. & Nonomura, Y. & Kawahashi, M., 2007. "The wake structure in a 2D grid installation of the horizontal axis micro wind turbines," Renewable Energy, Elsevier, vol. 32(13), pages 2247-2267.
    8. Park, Jinkyoo & Law, Kincho H., 2015. "Layout optimization for maximizing wind farm power production using sequential convex programming," Applied Energy, Elsevier, vol. 151(C), pages 320-334.
    9. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2012. "Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation," Renewable Energy, Elsevier, vol. 38(1), pages 16-30.
    10. Serrano González, Javier & Burgos Payán, Manuel & Riquelme Santos, Jesús & González Rodríguez, Ángel Gaspar, 2015. "Maximizing the overall production of wind farms by setting the individual operating point of wind turbines," Renewable Energy, Elsevier, vol. 80(C), pages 219-229.
    11. Rafael V. Rodrigues & Corinne Lengsfeld, 2019. "Development of a Computational System to Improve Wind Farm Layout, Part II: Wind Turbine Wakes Interaction," Energies, MDPI, vol. 12(7), pages 1-27, April.
    12. Lee, Jaejoon & Son, Eunkuk & Hwang, Byungho & Lee, Soogab, 2013. "Blade pitch angle control for aerodynamic performance optimization of a wind farm," Renewable Energy, Elsevier, vol. 54(C), pages 124-130.
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    Cited by:

    1. Takanori Uchida & Susumu Takakuwa, 2019. "A Large-Eddy Simulation-Based Assessment of the Risk of Wind Turbine Failures Due to Terrain-Induced Turbulence over a Wind Farm in Complex Terrain," Energies, MDPI, vol. 12(10), pages 1-19, May.
    2. Regodeseves, P. García & Morros, C. Santolaria, 2020. "Unsteady numerical investigation of the full geometry of a horizontal axis wind turbine: Flow through the rotor and wake," Energy, Elsevier, vol. 202(C).
    3. Rafael V. Rodrigues & Corinne Lengsfeld, 2019. "Development of a Computational System to Improve Wind Farm Layout, Part II: Wind Turbine Wakes Interaction," Energies, MDPI, vol. 12(7), pages 1-27, April.
    4. Shantanu Purohit & Ijaz Fazil Syed Ahmed Kabir & E. Y. K. Ng, 2021. "On the Accuracy of uRANS and LES-Based CFD Modeling Approaches for Rotor and Wake Aerodynamics of the (New) MEXICO Wind Turbine Rotor Phase-III," Energies, MDPI, vol. 14(16), pages 1-26, August.

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