Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm
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Published:2019-05-22
Issue:2
Volume:4
Page:287-302
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ISSN:2366-7451
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Container-title:Wind Energy Science
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language:en
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Short-container-title:Wind Energ. Sci.
Author:
Duc Thomas, Coupiac Olivier, Girard NicolasORCID, Giebel GregorORCID, Göçmen TuhfeORCID
Abstract
Abstract. In this paper, a new calculation procedure to improve the accuracy of the
Jensen wake model for operating wind farms is proposed. In this procedure, the
wake decay constant is updated locally at each wind turbine based on the
turbulence intensity measurement provided by the nacelle anemometer. This
procedure was tested against experimental data at the Sole
du Moulin Vieux (SMV) onshore wind farm in France and the Horns Rev-I offshore wind farm in
Denmark. Results indicate that the wake deficit at each wind turbine is
described more accurately than when using the original model, reducing the
error from 15 % to 20 % to approximately 5 %. Furthermore, this
new model properly calibrated for the SMV wind farm is then used for
coordinated control purposes. Assuming an axial induction control strategy,
and following a model predictive approach, new power settings leading to an
increased overall power production of the farm are derived. Power gains found
are on the order of 2.5 % for a two-wind-turbine case with close spacing
and 1 % to 1.5 % for a row of five wind turbines with a larger
spacing. Finally, the uncertainty of the updated Jensen model is quantified
considering the model inputs. When checked against the predicted power gain,
the uncertainty of the model estimations is seen to be excessive, reaching
approximately 4 %, which indicates the difficulty of field observations
for such a gain. Nevertheless, the optimized settings are to be implemented
during a field test campaign at SMV wind farm in the scope of the national
project SMARTEOLE.
Funder
Agence Nationale de la Recherche
Publisher
Copernicus GmbH
Subject
Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment
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