Modelling of wind turbine wake using large eddy simulation

Nima Sedaghatizadeh, Maziar Arjomandi, Richard Kelso, Benjamin Cazzolato and Mergen H. Ghayesh

Renewable Energy, 2018, vol. 115, issue C, 1166-1176

Abstract: In an array of wind turbines, the interaction of the downstream machines with the wakes from the upstream ones results in a reduction in the overall wind farm performance. Turbine wakes are a major source of turbulence which exerts fluctuating loads on the blades of the downstream turbines, resulting in the generation of noise and fatigue of the turbine blades. There are many semi-empirical wind turbine wake models in the literature. This paper, develops a fully numerical model of wind turbine wakes using CFD by means of a Large Eddy Simulation (LES). The new LES model is tested against experimental data, showing very good agreement. The advantages of the LES model compared to the available semi-empirical models in the literature are discussed and it is shown that the LES model is very accurate compared to the conventional semi-empirical wake models usually used in industry. Moreover, the LES model is used as a benchmark to compare the accuracy of these semi-empirical models; it is shown that the model proposed by Jensen can predict the velocity deficit most accurately among the semi-empirical models, while the highest degree of accuracy in the wake expansion is achieved by using the Larsen model.

Keywords: Wind farm; Wind turbine wake; Engineering wake models; Velocity deficit in the wake; Wake expansion (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:115:y:2018:i:c:p:1166-1176

DOI: 10.1016/j.renene.2017.09.017

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