Abstract
The calculation of the velocity deficit in the wake of individual wind turbines is a fundamental part of the wind farm analysis. A good approximation of the wake deficit behind a single wind turbine will improve the power estimation for downwind turbines. Large-eddy simulation (LES) is a research tool widely used in studying the velocity deficit and turbulence intensity in the wake. However, the computational cost of the LES prevents its application in wind farm performance analysis and control. Existing analytical wake models provide a fast estimation of the velocity deficit and the wake expansion rate downstream from the rotor. The Gaussian wake models use a Gaussian distribution to improve the prediction of the wake velocity deficit. With the number of analytical models available, an extensive evaluation of their performance under different flow parameters is needed. In this work, we simulate a wake of a single wind turbine using the LES code PALM (Parallelized LES Model) combined with an actuator disc model with rotation. We compare the computed flow field with the predictions made by Gaussian models and fit their parameters to obtain the best possible fit for the wake field data as computed by LES.
Highlights
Inside a wind farm, the wind turbines are subjected to the influence of upstream turbines
We simulate a wake of a single wind turbine using the Large-eddy simulation (LES) code PALM (Parallelized LES Model) combined with an actuator disc model with rotation
Since the available wind power is proportional to the cube of wind speed U 3, it is crucial to predict the wake velocity deficit accurately
Summary
The wind turbines are subjected to the influence of upstream turbines. The wake, an area with reduced mean velocity and increased turbulence intensity, is formed behind a working wind turbine due to the extraction of kinetic energy from the flow. The wake velocity eventually recovers to the free-flow velocity. The distances between wind turbines in a wind farm are usually shorter than needed for the full recovery. The wind turbines subjected to a wake operate under reduced wind speed. Since the available wind power is proportional to the cube of wind speed U 3, it is crucial to predict the wake velocity deficit accurately
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