This paper gives an evaluation of most of the commonly used models for predicting wind speed decrease (wake) downstream of a wind turbine. The evaluation is based on six experiments where free-stream and wake wind speed profiles were measured using a ship-mounted sodar at a small offshore wind farm. The experiments were conducted at varying distances between 1.7 and 7.4 rotor diameters downstream of the wind turbine. Evaluation of the models compares the predicted and observed velocity deficits at hub height. A new method of evaluation based on determining the cumulative momentum deficit over the profiles is described. Despite the apparent simplicity of the experiments, the models give a wide range of predictions. Overall, it is not possible to establish any of the models as having individually superior performance with respect to the measurements.

Project Objectives and OverviewThe objectives of the ENDOW project were to evaluate, enhance and interface wake and boundary layer models for utilization in the design of offshore wind farms. The research is presented in brief below. BockstigenBockstigen is located to the south-west of the island of Gotland. The wind farm consists of five Wind World 500 kW stall-regulated turbines with a hub height of 41·5 m and D = 37·3 m. There is an offshore mast of 40 m height, a coastal mast of 60 m height and an inland mast of 120 m height. Wind speeds on the offshore mast are measured at four heights with the top anemometer being free of mast shadow effects and two anemometers being available on either side of the mast at the remaining heights. Owing to the wind farm layout, only 226 R. Barthelmie et al.

Two new engineering models are presented for the aerodynamic induction of a wind turbine under dynamic thrust. The models are developed using the differential form of Duhamel integrals of indicial responses of actuator disc type vortex models. The time constants of the indicial functions are obtained by the indicial responses of a linear and a nonlinear actuator disc model. The new dynamic‐inflow engineering models are verified against the results of a Computational Fluid Dynamics (CFD) model and compared against the dynamic‐inflow engineering models of Pitt‐Peters, Øye, and Energy Research Center of the Netherlands (ECN), for several load cases. Comparisons of all models show that two time constants are necessary to predict the dynamic induction. The amplitude and phase delay of the velocity distribution shows a strong radial dependency. Verifying the models against results from the CFD model shows that the model based on the linear actuator disc vortex model predicts a similar performance as the Øye model. The model based on the nonlinear actuator disc vortex model predicts the dynamic induction better than the other models concerning both phase delay and amplitude, especially at high load.

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Wind turbines are usually clustered in wind farms which causes the downstream turbines to operate in the turbulent wakes of upstream turbines. As turbulence is directly related to increased fatigue loads, knowledge of the turbulence in the wake and its evolution are important. Therefore, the main objective of this study is a comprehensive exploration of the turbulence evolution in the wind turbine’s wake to identify characteristic turbulence regions. For this, we present an experimental study of three model wind turbine wake scenarios that were scanned with hot-wire anemometry with a very high downstream resolution. The model wind turbine was exposed to three inflows: laminar inflow as a reference case, a central wind turbine wake, and half of the wake of an upstream turbine. A detailed turbulence analysis reveals four downstream turbulence regions by means of the mean velocity, variance, turbulence intensity, energy spectra, integral and Taylor length scales, and the Castaing parameter that indicates the intermittency, or gustiness, of turbulence. In addition, a wake core with features of homogeneous isotropic turbulence and a ring of high intermittency surrounding the wake can be identified. The results are important for turbulence modeling in wakes and optimization of wind farm wake control.