Abstract
The present paper addresses the evolution of turbulence characteristics in wind turbine wakes immersed in a turbulent boundary layer. The study thereby focuses on finding physically consistent scaling laws for the wake width, the velocity deficit, and the Reynolds stresses in the far wake region. For this purpose, the concept of an added wake is derived which allows to analyse the self-similarity of the added flow quantities and the applicability of the non-equilibrium dissipation theory. The investigation is based on wind tunnel measurements in the wake of a three-bladed horizontal axis wind turbine model (HAWT) immersed in two neutrally-stratified turbulent boundary layers of different aerodynamic roughness length. The dataset also includes wake measurements for various yaw angles. A high degree of self-similarity is found in the lateral profiles of the velocity deficit and of the added Reynolds stress components. It is shown that these can be described by combined Gaussian shape functions. In the vertical, self-similarity can just be shown in the upper part of the wake. Moreover, it is observed that the degree of self-similarity is affected by the ground roughness. Results suggest an approximately constant anisotropy of the added turbulent stresses in the far wake, and the axial scaling of the added Reynolds stress components is found to be in accordance with non-equilibrium dissipation theory. It predicts a x − 1 decay of the added turbulent intensity I + , and a x − 2 evolution of the added Reynolds shear stresses Δ u i ′ u j ′ ¯ and the velocity deficit Δ u . Based on these findingsa semi-empirical model is proposed for predicting the Reynolds stresses in the far wake region which can easily be coupled with existing analytical wake models. The proposed model is found to be in good agreement with the measurement results.
Highlights
IntroductionWake interactions can reduce the power production of the wind turbines and increase fatigue loads
Within wind farms, wake interactions can reduce the power production of the wind turbines and increase fatigue loads
Before analysing the wake characteristics, the measured performance of the wind turbine immersed in both boundary layers is presented for varying tip-speed ratio and yaw angle
Summary
Wake interactions can reduce the power production of the wind turbines and increase fatigue loads. To maximize the power output and alleviate the loads, wind farm control methods can be applied. To make use of these methods, wind farm controllers rely on fast analytical models to predict the flow field and optimize the power production. To alleviate the fatigue loads turbulence quantities in the wake impinging a downstream turbine have to be predicted. The turbulence and atmospheric conditions seen by this turbine strongly influence the subsequent wake and its trajectory [2,3]. Analytical models capable of predicting the flow field and of the turbulence in the wake, are crucial for an efficient wind farm control
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