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Energies 2016, 9(9), 741; doi:10.3390/en9090741

Analytical Modeling of Wind Farms: A New Approach for Power Prediction

1
Wind Engineering and Renewable Energy Laboratory (WIRE), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-ENAC-IIE-WIRE, 1015 Lausanne, Switzerland
2
Stream Biofilm and Ecosystem Research Laboratory (SBER), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-ENAC-IIE-SBER, 1015 Lausanne, Switzerland
*
Author to whom correspondence should be addressed.
Academic Editor: Frede Blaabjerg
Received: 11 April 2016 / Revised: 18 August 2016 / Accepted: 31 August 2016 / Published: 15 September 2016
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Abstract

Wind farm power production is known to be strongly affected by turbine wake effects. The purpose of this study is to develop and test a new analytical model for the prediction of wind turbine wakes and the associated power losses in wind farms. The new model is an extension of the one recently proposed by Bastankhah and Porté-Agel for the wake of stand-alone wind turbines. It satisfies the conservation of mass and momentum and assumes a self-similar Gaussian shape of the velocity deficit. The local wake growth rate is estimated based on the local streamwise turbulence intensity. Superposition of velocity deficits is used to model the interaction of the multiple wakes. Furthermore, the power production from the wind turbines is calculated using the power curve. The performance of the new analytical wind farm model is validated against power measurements and large-eddy simulation (LES) data from the Horns Rev wind farm for a wide range of wind directions, corresponding to a variety of full-wake and partial-wake conditions. A reasonable agreement is found between the proposed analytical model, LES data, and power measurements. Compared with a commonly used wind farm wake model, the new model shows a significant improvement in the prediction of wind farm power. View Full-Text
Keywords: analytical model; Gaussian velocity deficit; turbulence intensity; velocity deficit superposition; wake growth rate; wind farm power production analytical model; Gaussian velocity deficit; turbulence intensity; velocity deficit superposition; wake growth rate; wind farm power production
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Niayifar, A.; Porté-Agel, F. Analytical Modeling of Wind Farms: A New Approach for Power Prediction. Energies 2016, 9, 741.

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