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. In this paper, a new calculation procedure to improve the accuracy of theJensen wake model for operating wind farms is proposed. In this procedure, thewake decay constant is updated locally at each wind turbine based on theturbulence intensity measurement provided by the nacelle anemometer. Thisprocedure was tested against experimental data at the Soledu Moulin Vieux (SMV) onshore wind farm in France and the Horns Rev-I offshore wind farm inDenmark. Results indicate that the wake deficit at each wind turbine isdescribed more accurately than when using the original model, reducing theerror from 15 % to 20 % to approximately 5 %. Furthermore, thisnew model properly calibrated for the SMV wind farm is then used forcoordinated control purposes. Assuming an axial induction control strategy,and following a model predictive approach, new power settings leading to anincreased overall power production of the farm are derived. Power gains foundare on the order of 2.5 % for a two-wind-turbine case with close spacingand 1 % to 1.5 % for a row of five wind turbines with a largerspacing. Finally, the uncertainty of the updated Jensen model is quantifiedconsidering the model inputs. When checked against the predicted power gain,the uncertainty of the model estimations is seen to be excessive, reachingapproximately 4 %, which indicates the difficulty of field observationsfor such a gain. Nevertheless, the optimized settings are to be implementedduring a field test campaign at SMV wind farm in the scope of the nationalproject SMARTEOLE.

Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm