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Unraveling the Mysteries of Turbulence Transport in a Wind Farm

Author

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  • Pankaj K. Jha

    (Department of Aerospace Engineering, the Pennsylvania State University, University Park, PA 16802, USA)

  • Earl P. N. Duque

    (Applied Research Group, Intelligent Light, Rutherford, NJ 07070, USA)

  • Jessica L. Bashioum

    (Department of Aerospace Engineering, the Pennsylvania State University, University Park, PA 16802, USA)

  • Sven Schmitz

    (Department of Aerospace Engineering, the Pennsylvania State University, University Park, PA 16802, USA)

Abstract

A true physical understanding of the mysteries involved in the recovery process of the wake momentum deficit, downstream of utility-scale wind turbines in the atmosphere, has not been obtained to date. Field data are not acquired at sufficient spatial and temporal resolutions to dissect some of the mysteries of wake turbulence. It is here that the actuator line method has evolved to become the technology standard in the wind energy community. This work presents the actuator line method embedded into an Open source Field Operation and Manipulation (OpenFOAM) large-eddy simulation solver and applies it to two small wind farms, the first one consisting of an array of two National Renewable Energy Laboratory 5 Megawatt (NREL 5-MW) turbines separated by seven rotor diameters in neutral and unstable atmospheric boundary-layer flow and the second one consisting of five NREL 5-MW wind turbines in unstable atmospheric conditions arranged in two staggered arrays of two and three turbines, respectively. Detailed statistics involving power spectral density (PSD) of turbine power along with standard deviations reveal the effects of atmospheric turbulence and its space and time scales. High-resolution surface data extracts provide new insight into the complex recovery process of the wake momentum deficit governed by turbulence transport phenomena.

Suggested Citation

  • Pankaj K. Jha & Earl P. N. Duque & Jessica L. Bashioum & Sven Schmitz, 2015. "Unraveling the Mysteries of Turbulence Transport in a Wind Farm," Energies, MDPI, vol. 8(7), pages 1-29, June.
  • Handle: RePEc:gam:jeners:v:8:y:2015:i:7:p:6468-6496:d:51732
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    References listed on IDEAS

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    1. Kiran Bhaganagar & Mithu Debnath, 2014. "Implications of Stably Stratified Atmospheric Boundary Layer Turbulence on the Near-Wake Structure of Wind Turbines," Energies, MDPI, vol. 7(9), pages 1-24, September.
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    4. Claire VerHulst & Charles Meneveau, 2015. "Altering Kinetic Energy Entrainment in Large Eddy Simulations of Large Wind Farms Using Unconventional Wind Turbine Actuator Forcing," Energies, MDPI, vol. 8(1), pages 1-17, January.
    5. Yu-Ting Wu & Fernando Porté-Agel, 2012. "Atmospheric Turbulence Effects on Wind-Turbine Wakes: An LES Study," Energies, MDPI, vol. 5(12), pages 1-23, December.
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    Cited by:

    1. Fei Zhao & Yihan Gao & Tengyuan Wang & Jinsha Yuan & Xiaoxia Gao, 2020. "Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    2. Nicolas Tobin & Adam Lavely & Sven Schmitz & Leonardo P. Chamorro, 2019. "Spatiotemporal Correlations in the Power Output of Wind Farms: On the Impact of Atmospheric Stability," Energies, MDPI, vol. 12(8), pages 1-12, April.
    3. Matthias Schramm & Hamid Rahimi & Bernhard Stoevesandt & Kim Tangager, 2017. "The Influence of Eroded Blades on Wind Turbine Performance Using Numerical Simulations," Energies, MDPI, vol. 10(9), pages 1-15, September.
    4. Behnam Moghadassian & Aaron Rosenberg & Anupam Sharma, 2016. "Numerical Investigation of Aerodynamic Performance and Loads of a Novel Dual Rotor Wind Turbine," Energies, MDPI, vol. 9(7), pages 1-30, July.
    5. Neunaber, Ingrid & Hölling, Michael & Whale, Jonathan & Peinke, Joachim, 2021. "Comparison of the turbulence in the wakes of an actuator disc and a model wind turbine by higher order statistics: A wind tunnel study," Renewable Energy, Elsevier, vol. 179(C), pages 1650-1662.

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