Abstract
Turbulence-resolving simulations of wind turbine wakes are presented using a high-order flow solver combined with both a standard and a novel dynamic implicit spectral vanishing viscosity (iSVV and dynamic iSVV) model to account for subgrid-scale (SGS) stresses. The numerical solutions are compared against wind tunnel measurements, which include mean velocity and turbulent intensity profiles, as well as integral rotor quantities such as power and thrust coefficients. For the standard (also termed static) case the magnitude of the spectral vanishing viscosity is selected via a heuristic analysis of the wake statistics, while in the case of the dynamic model the magnitude is adjusted both in space and time at each time step. The study focuses on examining the ability of the two approaches, standard (static) and dynamic, to accurately capture the wake features, both qualitatively and quantitatively. The results suggest that the static method can become over-dissipative when the magnitude of the spectral viscosity is increased, while the dynamic approach which adjusts the magnitude of dissipation locally is shown to be more appropriate for a non-homogeneous flow such that of a wind turbine wake.
Highlights
Understanding and modelling wake–turbine and wake–wake interactions within wind farms have been recognised as one of the long–term challenges in wind energy research (van Kuik et al, 2016)
We have investigated the ability of static and dynamic spectral vanishing viscosity (SVV) operators to act as a SGS model and predict the wake statistics behind a single wind turbine as well as two turbines operating in-line
This was motivated by previous studies in the field of wind turbine wakes (Mehta et al, 2014; Sarlak et al, 2015) which have pointed out that implicit large-eddy simulations (LES) formulations which rely on numerical dissipation for the SGS modelling can predict the wake well
Summary
Understanding and modelling wake–turbine and wake–wake interactions within wind farms have been recognised as one of the long–term challenges in wind energy research (van Kuik et al, 2016). In the context of LES, we argue that this entails two factors: first the need for subgrid–scale (SGS) models that do not act in an over–dissipative manner so that larger coherent structures of turbulence can be retained, and second the use of high–order schemes with spectral or “spectral-like” accuracy which can capture more flow field details with the same degree of freedom count Starting with the former, the development and validation of SGS models has long been an active area of research, with numerous models having been suggested and applied to turbine wakes. To parametrise the wind turbines we make use of the actuator line technique (Sørensen and Shen, 2002) based on a turbine parametrisation which has been previously shown to better capture the key features of the near wake field (e.g. tip vortices) This remainder of this paper begins with a presentation of the numerical discretisation techniques employed, including details on the static and dynamic SVV methods and a short description of the actuator line turbine parametrisation used in this work.
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