Abstract
The turbulence in the interior of an idealised wind farm is simulated using Large Eddy Simulation and the Actuator Line technique implemented in the Navier-Stokes equations. The simulation is carried out for an 'infinitely' long row of turbines simulated by applying cyclic boundary conditions at the inlet and outlet. The simulations investigate the turbulence inherent to the wind turbines as no ambient turbulence or shear is added to this idealised case. A Reduced Order Model for the highly turbulent flow deep inside a wind farm is proposed based on a Proper Orthogonal Decomposition. The reconstructed flow is shown to capture the large scale motions of the highly turbulent flow.
Highlights
In large wind farms, both onshore and offshore, the wind turbines in the interior will operate in the wake of the upstream turbines irrespective of the wind direction
Frandsen [5] proposed a model for fatique loading on rotors using the effective turbulence intensity as the only governing parameter, arguing that the various changes in turbulence properties usually correlates with the standard deviation of wind speed fluctuations
The model has shown improved accuracy compared to the existing engineering models, albeit still occassionally resulting in large discrepancies compared to measurements
Summary
Both onshore and offshore, the wind turbines in the interior will operate in the wake of the upstream turbines irrespective of the wind direction. A wind turbine operating in the wake of one or more wind turbines yields less power and is subject to greater loadings from the induced turbulence, leading to increased fatique Understanding this highly dynamic wake interaction is important for wind farm optimization. Several analytical wake models exist, e.g. Jensen [8] and Frandsen et al [4] These models are based on simple single wake calculations and different assumptions are used to superpose merging wakes to describe the overall wake interaction inside wind farms. These methods are based on steady state considerations, and are developed with the aim of predicting mean quantities, e.g. the mean velocity deficit in the wake.
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