Wind farm power maximization through wake steering with a new multiple wake model for prediction of turbulence intensity

A new multiple wake model is developed for wind farm power prediction and wind farm control. First, numerical simulations are conducted for two wind turbines under different layout sets, and the characteristics of mean velocity and turbulence intensity in multiple wakes are systematically investigated. A new multiple wake model considering the local effective turbulence on the rotor and the wake interaction effects is proposed. The proposed model can favorably predict the mean velocity and turbulence intensity distributions in multiple wake regions, as well as the power production in wind farm comparing with numerical simulations and field measurements. Finally, the new proposed multiple wake model is applied to wind farm modelling and optimization framework, which enables the maximization of wind farm power production by wake steering control. The wind sector width of 2 degrees with the wind speed bin of 0.5 m/s is proposed for the lookup-table-based wake steering optimization. The proposed values reduce the prediction error of annual energy production gain from 34.5% to 3.2% comparing with the conventional values of 5 degrees and 1 m/s. In addition, the yaw offset limit of +/- 15 degrees is recommended to satisfy both the maximization of power production and the safety requirement of International Electrotechnical Commission (IEC) standard. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

A new multiple wake model is proposed for wind farm power prediction and control, which accurately predicts the characteristics of mean velocity and turbulence intensity in multiple wake regions. By applying the model to wind farm modeling and optimization, the power production can be maximized through wake steering control. Configuring wind sector width of 2 degrees and wind speed bin of 0.5 m/s significantly reduces the prediction error of annual energy production gain.