Large‐eddy simulations of wind‐farm wake characteristics associated with a low‐level jet

Abstract

In this study, we performed a suite of flow simulations for a 12-wind-turbine array with varying inflow conditions and lateral spacings, and compared the impacts of the flow on velocity deficit and wake recovery. We imposed both laminar inflow and turbulent inflows, which contain turbulence for the Ekman layer and a low-level jet (LLJ) in the stable boundary layer. To solve the flow through the wind turbines and their wakes, we used a large-eddy simulation technique with an actuator-line method. We compared the time series for the velocity deficit at the first and rear columns to observe the temporal change in velocity deficit for the entire wind farm. The velocity deficit at the first column for LLJ inflow was similar to that for laminar inflow. However, the magnitude of velocity deficit at the rear columns for the case with LLJ inflow was 11.9% greater because of strong wake recovery, which was enhanced by the vertical flux of kinetic energy associated with the LLJ. To observe the spatial transition and characteristics of wake recovery, we performed statistical analyses of the velocity at different locations for both the laminar and LLJ inflows. These studies indicated that strong wake recovery was present, and a kurtosis analysis showed that the probability density function for the streamwise velocity followed a Gaussian distribution. In a quadrant analysis of the Reynolds stress, we found that the ejection and sweep motions for the LLJ inflow case were greater than those for the laminar inflow case. KEYWORDS actuator line method, low-level jet, velocity deficit, vertical flux of kinetic energy, wake recovery, wind farm 1 | INTRODUCTION The investigation of wind-turbine wakes is important because it is closely related to the power efficiency and duration of the entire wind farm. 1,2The wake caused by rotation of turbine blades recovers from the free-stream flow due to kinetic energy flux. If the wake does not recover fully, it enters the downstream wind turbines, which causes their power efficiency to drop drastically and fatigue failure of the blades. 3,4 The main factors that determine the wake characteristics of a wind farm are its design and the condition of the incoming wind. 5,6 Design factors such as the spacing between turbines and the alignment of the wind farm affect the interference and interaction between the wakes generated by each turbine. Moreover, the conditions of the incoming wind-such as speed, direction, and turbulence characteristics-influence both wake generation and recovery.Studies of wind-farm designs and incoming winds have been performed mainly using numerical approaches, because it is difficult to observe the detailed structure of a wake due to limitations such as low Reynolds number and low resolution of the flow. 7,8 Wake studies of various alignments and spacings in wind farms have compared the power output at each row of a wind farm. 9 These studies found that the key factor in minimizing the wake effects of turbines is a small angle of alignment between the turbines and the win...

Interaction between low-level jets and wind farms in a stable atmospheric boundary layer

“…A similar phenomenon has been observed in the mesoscale weather model simulations of an infinite wind farm [48]. Recently, Na et al [49] performed LES of a small wind farm with 12 turbines arranged in three columns and four rows with an LLJ above it in a spanwise periodic domain. They report faster wake recovery due to the enhanced vertical kinetic energy flux created by the LLJ.…”

An Experimental Study on the Actuator Line Method with Anisotropic Regularization Kernel

“…For ALM, although the relationship between velocity and force is correct, a tip loss correction is suggested by Shen [19] due to the inconsistency between 2D airfoil data and attack angle of the 3D blade. This tip loss correction is employed in this study to compensate for the tip loss effect of wind turbine blade as shown in Equations (7) and (8)…”

“…Combining with the LES model, ALM can make good simulations of velocity field and turbulence field in the wake region [2,3] and it has advantages in wind turbine simulations when the inlet condition is complex, such as the atmospheric boundary layer condition [4,5]. Secondly, due to 2 of 19 its low computational cost, ALM can be used in large-scale problems [4,[6][7][8] and can be easily coupled with structural models [9,10]. Therefore, ALM is suitable for wind farm simulations and fluid-structure interaction simulations.…”

Occurrence of Low-Level Jets over the Eastern U.S. Coastal Zone at Heights Relevant to Wind Energy

“…Further, the increasing physical dimensions of wind turbine heights over time, and particularly offshore, mean LLJs may more frequently intersect with the wind turbine rotor plane [24,25]. When a LLJ occurs within the rotor plane, changes to the distributions of turbulent kinetic energy, shear, wind speed and wind direction [26,27] may increase energy production and enhance wind turbine wake recovery [28,29]. However, it is also likely to be associated with enhanced static and mechanical loading, fatigue cycles and deflections [30].…”