Characterizing Impacts of Atmospheric Turbulence on Wind Farms Through Large Eddy Simulation (LES)

Alam, Jahrul M; Afanassiev, Anton; Singh, Jagdeep

doi:10.1115/omae2019-95837

Cited by 3 publications

(2 citation statements)

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“…The scale-adaptive LES framework discussed in this article has been implemented in an updated version of the (collocated grid) Navier-Stokes solver that was detailed previously by [35]. Previous utilization of the code investigated the interaction of geophysical turbulent flow over an array of wind turbines using classical ADM [11], as well as turbulent flow over the Askervein hill, UK [15]. Here, we investigate the new development of the Gaussian actuator disk model of the wind turbine and compare the numerical results against the experimental data.…”

Section: Results Analysismentioning

confidence: 99%

“…Such errors are adequately controlled with an actuator line model if the nacelle, rotational effects of turbines, tip vortices, and the atmospheric boundary layer (ABL) region below the rotor bottom are sufficiently resolved [10]. However, neither of such methods is appropriate for LES of utility-scale large wind farms in which two-way feedback of atmospheric boundary layer becomes essential [5,6,11]. Therefore, a scale-adaptive LES using an improved actuator disk model can be a promising solution to balance the efficiency and accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Vortex-Stretching based Large Eddy Simulation Framework for Wind Farms

Singh¹,

Alam²

2022

Preprint

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In large wind farms, wake distribution behind a wind turbine causes a considerable reduction of wind velocity for downstream wind turbines, resulting in a significant amount of power loss. Therefore, it is very crucial to predict wind turbine wakes efficiently. Thus, we propose a large-eddy simulation (LES) methodology, which takes the vorticity stretching to model transients in wind turbine wakes. In addition, we present an improved actuator disk model, which accounts for two-way feedback between the atmosphere and the wakes. First, we show that the vertical profile of the mean wind predicted with the new model has an excellent agreement with experimental measurements. Next, we validate the predicted Reynolds stresses against wind tunnel data and show that the dispersive stresses account for about 40% of Reynolds stresses. Finally, we show that the proposed LES method accurately predicts the characteristics of wind turbine wakes. Comparing the LES results with previously reported data, we have found that the new LES framework accurately predicts the flow statistics in both the near-wake and the far-wake regions.

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Section: Results Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Vortex-Stretching based Large Eddy Simulation Framework for Wind Farms

Singh¹,

Alam²

2022

Preprint

Self Cite

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Interaction of vortex stretching with wind power fluctuations

Alam

2022

Physics of Fluids

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The transfer of turbulence kinetic energy from large to small scales occurs through vortex stretching. Also, statistical properties of the subgrid-scale energy fluxes depend on the alignment of the vorticity vector with the principal strain axis. A heuristic analysis of the present study indicates that vortex-stretching and the second invariant of the velocity gradient tensor provide a scale-adaptive parameterization of the subgrid-scale stresses and the local energy fluxes in the wakes of wind turbines. The scale-adaptivity underlies the restricted Euler dynamics of the filtered motion where vortex-stretching plays in the growth of the second invariant of filtered velocity gradient and the local energy transfer. We have analyzed wind power fluctuations in a utility-scale wind farm with 41 actuator disks. The numerical results show that the spectrum of the wind power fluctuations follows a power law with a logarithmic slope of −5/3. Furthermore, a brief analysis with the proper orthogonal decomposition method indicates that the maximum variability of wind power fluctuations depends on the incoming turbulence and its modulation by the wake interactions in wind farms.

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Statistical Analysis of Dynamic Subgrid Modeling Approaches in Large Eddy Simulation

2021

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In large eddy simulation (LES) of turbulent flows, dynamic subgrid models would account for an average cascade of kinetic energy from the largest to the smallest scales of the flow. Yet, it is unclear which of the most critical dynamical processes can ensure the criterion mentioned above. Furthermore, evidence of vortex stretching being the primary mechanism of the cascade is not out of the question. In this article, we study essential statistical characteristics of vortex stretching. Our numerical results demonstrate that vortex stretching rate provides the energy dissipation rate necessary for modeling subgrid-scale turbulence. We have compared the interaction of subgrid stresses with the filtered quantities among four models using invariants of the velocity gradient tensor. The individual and the joint probability of vortex stretching and strain amplification show that vortex stretching rate is highly correlated with the energy cascade rate. Sheet-like flow structures are correlated with viscous dissipation, and vortex tubes are more stretched than compressed. The overall results indicate that the stretching mechanism extracts energy from the large-scale straining motion and passes it onto small-scale stretched vortices.

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Characterizing Impacts of Atmospheric Turbulence on Wind Farms Through Large Eddy Simulation (LES)

Cited by 3 publications

References 0 publications

Vortex-Stretching based Large Eddy Simulation Framework for Wind Farms

Vortex-Stretching based Large Eddy Simulation Framework for Wind Farms

Interaction of vortex stretching with wind power fluctuations

Statistical Analysis of Dynamic Subgrid Modeling Approaches in Large Eddy Simulation

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