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Register a new userEnhanced wind-farm performance using windbreaks
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The flow speed-up generated by windbreaks can be used to increase the power production of wind turbines. However, due to the increased drag imposed by the windbreaks, their use in large wind turbine arrays has been questioned. We use large eddy simulations to show that windbreaks can increase the power production of large wind farms. A crucial finding is that windbreaks in a wind farm should be much lower than for a single turbine case. In fact, the optimal windbreak for an isolated turbine can reduce wind farm performance. The optimal windbreak height in a wind farm namely depends on the right balance between flow speed-up over the windbreak and the drag imposed by all windbreaks in the farm. The increased performance is a result of the favorable total pressure flux created by the windbreaks.
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In this study, we focus on Langmuir turbulence in the deep ocean with the presence of a large macroalgal farm using a Large Eddy Simulation method. The wave-current interactions are modelled by solving the wave-averaged equations. The hydrodynamic process over the farm is found to drive a persistent flow pattern similar to Langmuir circulations but is locked in space across the farm. These secondary circulations are generated because the cross-stream shear produced by the rows of canopy elements leads to a steady vertical vorticity field, which is then rotated to the downstream direction under the effect of vortex force. Since the driving mechanism is similar to the CraikLeibovich type 2 instability theory, these secondary circulations are also termed as attached Langmuir circulations. We then apply a triple decomposition on the flow field to unveil the underlying kinematics and energy transfer between the mean flow, the secondary flow resulting from the farm drag, and the transient eddies. Flow visualizations and statistics suggest that the attached Langmuir circulations result from the adjustment of the upper ocean mixed layer to the macroalgal farm, and they will weaken (if not disappear) when the flow reaches an equilibrium state within the farm. The tripledecomposed energy budgets reveal that the energy of the secondary flow is transferred from the mean flow under the action of canopy drag, while the transient eddies feed on wave energy transferred by the Stokes drift and energy conversion from the secondary flow.
Being considered as a prototype for description of oceanic rogue waves (RWs), the Peregrine breather solution of the nonlinear Schrodinger equation (NLS) has been recently observed and intensely investigated experimentally in particular within the context of water waves. Here, we report the experimental results showing the evolution of the Peregrine solution in the presence of wind forcing in the direction of wave propagation. The results show the persistence of the breather evolution dynamics even in the presence of strong wind and chaotic wave field generated by it. Furthermore, we have shown that characteristic spectrum of the Peregrine breather persists even at the highest values of the generated wind velocities thus making it a viable characteristic for prediction of rogue waves.
The wake effect is one of the leading causes of energy losses in offshore wind farms (WFs). Both turbine placement and cooperative control can influence the wake interactions inside the WF and thus the overall WF power production. Traditionally, greedy control strategy is assumed in the layout design phase. To exploit the potential synergy between the WF layout and control so that a system-level optimal layout can be obtained with the greatest energy yields, the layout optimization should be performed with cooperative control considerations. For this purpose, a novel two-stage WF layout optimization model is developed in this paper. Cooperative WF control of both turbine yaw and axis-induction are considered. However, the integration of WF control makes the layout optimization much more complicated and results in a large-scale nonconvex problem, hindering the application of current layout optimization methods. To increase the computational efficiency, we leverage the hierarchy and decomposability of the joint optimization problem and design a decomposition-based hybrid method (DBHM). Case studies are carried out on different WFs. It is shown that WF layouts with higher energy yields can be obtained by the proposed joint optimization compared to traditional separate layout optimization. Moreover, the computational advantages of the proposed DBHM on the considered joint layout optimization problem are also demonstrated.
In this work the accuracy of the Actuator Line Model (ALM) in Large Eddy Simulations of wind turbine flow is studied under the specific conditions of very coarse spatial resolutions. For finely-resolved conditions, it is known that ALM provides better accuracy compared to the standard Actuator Disk Model (ADM) without rotation. However, we show here that on very coarse resolutions, flow induction occurring at rotor scales can affect the predicted inflow angle and can adversely affect the ALM predictions. We first provide an illustration of coarse LES to reproduce wind tunnel measurements. The resulting flow predictions are good, but the challenges in predicting power outputs from the detailed ALM motivate more detailed analysis on a case with uniform inflow. We present a theoretical framework to compare the filtered quantities that enter the Large-Eddy Simulation equations as body forces with a scaling relation between the filtered and unfiltered quantities. The study aims to apply the theoretical derivation to the simulation framework and improve the current results for an ALM, especially in the near wake where the largest differences are observed.
The atmospheric incoming flow of a wind turbine is intimately connected to its power production as well as its structural stability. Here we present an incoming flow measurement of a utility-scale turbine at the high spatio-temporal resolution, using super-large-scale particle image velocimetry (SLPIV) with natural snowflakes. The datasets include over a one-hour duration of incoming flow with a field of view of 85 m (vertical) x 40 m (streamwise) centered at 0.2 rotor diameter upstream of the turbine. The mean flow shows the presence of the induction zone and a distinct region with enhanced vertical velocity. Time series of nacelle sonic anemometer and SLPIV measured streamwise velocity outside the induction zone show generally matched trends with time-varying discrepancies potentially due to the induction effect and the flow acceleration around the nacelle. These discrepancies between the two signals, characterized by the sonic-SLPIV velocity ratio, is normally distributed and is less than unity 85% of the time. The velocity ratio first decreases with increasing wind speed up to around the rated speed of the turbine, then plateaus, and finally rises with a further increase in wind speed. With conditional sampling, the distribution of the velocity ratio shows that larger yaw error leads to an increase in both the mean and the spread of the distribution. Moreover, as the incident angle of the incoming flow changes from negative to positive (i.e. from pointing downward to upward), the velocity ratio first decreases as the angle approaches zero. With further increase of the incidence angle, the ratio then plateaus and fluctuations are augmented. Finally, our results show that the intensity of short-term velocity fluctuation has a limited impact on the sonic-SLPIV velocity ratio.
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