Résumé

The wind energy industry is increasingly focusing on optimal power extraction strategies based on layout design of wind farms and yaw alignment algorithms. Recent field studies by Mikkelsen et al. (Wind Energy, 2013) have explored the possibility of using wind lidar technology installed at hub height to anticipate incoming wind direction and strength for optimizing yaw alignment. In this work we study the benefits of using remote sensing technology for predicting the incoming flow by using large eddy simulations of a wind farm. The wind turbines are modeled using the classic actuator disk concept with rotation, together with a new algorithm that permits the turbines to adapt to varying flow directions. This allows for simulations of a more realistic atmospheric boundary layer driven by a time-varying geostrophic wind. Various simulations are performed to investigate possible improvement in power generation by utilizing upstream data. Specifically, yaw-correction of the wind-turbine is based on spatio-temporally averaged wind values at selected upstream locations. Velocity and turbulence intensity are also considered at those locations. A base case scenario with the yaw alignment varying according to wind data measured at the wind turbine's hub is also used for comparison. This reproduces the present state of the art where wind vanes and cup anemometers installed behind the rotor blades are used for alignment control.

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