The modelling of wind turbine wakes is investigated in this paper using a Navier-Stokes solver employing the k-ω turbulence model appropriately modifi ed for atmospheric fl ows. It is common knowledge that even single-wind turbine wake predictions with computational fl uid dynamic methods underestimate the near wake defi cit, directly contributing to the overestimation of the power of the downstream turbines. For a single-wind turbine, alternative modelling enhancements under neutral and stable atmospheric conditions are tested in this paper to account for and eventually correct the turbulence overestimation that is responsible for the faster fl ow recovery that appears in the numerical predictions. Their effect on the power predictions is evaluated with comparison with existing wake measurements. A second issue addressed in this paper concerns multi-wake predictions in wind farms, where the estimation of the reference wind speed that is required for the thrust calculation of a turbine located in the wake(s) of other turbines is not obvious. This is overcome by utilizing an induction factor-based concept: According to it, the defi nition of the induction factor and its relationship with the thrust coeffi cient are employed to provide an average wind speed value across the rotor disk for the estimation of the axial force. Application is made on the case of fi ve wind turbines in a row.Modelling of wind turbine wakes J. M. Prospathopoulos et al.
This paper describes an analysis of wake measurements from the research farm at the ECN Wind Turbine Test Site Wieringermeer. This research farm is owned and operated by the Energy Research Centre of the Netherlands. The farm consists of five research turbines that are oriented in a single line with a mutual distance of 3.8D(iameter). The turbines are variable speed and pitch controlled, and they have a diameter and a hub height of 80 m. The rated power of the turbines is 2.5 MW. Extensive machine measurements (power, loads, yaw angle and pitch angles) are carried out on these turbines. In parallel, meteorological measurements are done on a 108 m mast that is instrumented at three heights (hub height and hub height˙70% span) with sonic anemometers and cups and wind vanes. This mast is located at a shortest distance of 2.5D from one of the turbines. Data have been collected over a period of almost 5 years, and they are used to study several phenomena mainly related to wake aerodynamics, e.g. power losses in the wake of up to four wind turbines and meteorological wake phenomena at different distances behind the turbines.
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