A large eddy simulation was performed on an National Renewable Energy Laboratory (NREL) phase VI wind turbine (10 m diameter), using the exact blade geometry, to determine the influence of different inflow conditions on the aerodynamic loadings and the near wake characteristics. The effects of the three inflow conditions, uniform inflow, linear wind shear and linear wind shear with turbulence, are investigated. Wind shear causes periodic variations in power and aerodynamic loading with an additional force component exerted along the lateral direction. Significant separation occurs in the high wind region on the suction side of the blades, resulting in unstable loading in off-design inflow conditions. Because of the shear effect between the near-blade tip vortex and ambient flow, the strong vortex core in the helical structure dissipates and transforms into a continuous vorticity sheet when x=D > 1.5. The combination of inflow turbulence and wind shear enhances the turbulence generation mechanism in the near wake, where energy is withdrawn from large wake structures and converted into energy of small-scale structures.
It is well known that turbulence can cause fluctuations in the resulting sound fields. In the issue of wind turbine noise, such effect is non-negligible since either the inflow turbulence from nearby turbine wakes or the atmospheric turbulence generated by rotating turbine blades can increase the sound output of individual turbines. In this study, a combined approach of the Finite Element Method (FEM) and Parabolic Equation (PE) method is employed to predict the sound levels from a wind turbine. In the prediction procedure, the near field acoustic data is obtained by means of a computational fluid dynamic program which serves as a good starting field of sound propagation. It is then possible to advance wind turbine noise in range by using the FEM/PE marching algorithm. By incorporating the simulated turbulence profiles near wind turbine, more accurate predictions of sound field in realistic atmospheric conditions are obtained.
In this paper, the Large Eddy Simulation coupled with the Actuator line (LES-AL) method is employed to analyze the performance of the downstream wind turbine under varying inflow conditions. A direct LES, which solves the flow physics around turbine blades using exact three-dimensional blade geometries, is carried out to predict the aerodynamic loadings and output powers of the downstream turbines by prescribing the wake profiles predicted by LES-AL simulation as the inflow boundary conditions. The upstream tower shadow effect is presented in this study by carrying out two simulations with no tower wake and real tower wake inflow conditions. The LES results show that both the power and aerodynamic loading components fluctuate periodically due to the presence of upstream tower. In additional, an additional force component is exerted on the downstream wind turbine in the vertical direction (z direction). The increase in velocity deficit in wake in behind the downstream turbine is due to a sequence of momentum extraction by the wind turbines. The tower shadow effect accumulates and generates lower velocity regions in wake, and the low velocity regions shift due to the rotational motion of wake vortex. The development of the asymmetric and velocity deficit region has the potential to generate more unstable power output and fatigue loading on turbines in further downstream.
This paper presents a numerical simulation of unsteady flow over wind turbine arrays to understand rotor-rotor and rotor-tower wake interaction in wind farms. The computations are carried out by incorporating Actuator Line method into a large eddy simulation. This methodology is validated by comparing the results to predictions of large eddy simulation using exact 3D blade geometries from a two-blade NREL Phase VI turbine. The method is then used to simulate the wake development in a two-turbine case. It is discovered that in the full wake setting the tower has a significant influence on the central part of the turbine wake. It is observed that the tower wake is twisted due to the rotation of the turbine wake. As a result, this tower wake is expected to have impact on the performance of downstream wind turbines, which cannot be overlooked. The present work also demonstrates the potential of combining AL method with LES to predict wake interactions in wind farms.
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