Detection of Wind Evolution and Lidar Trajectory Optimization for Lidar-Assisted Wind Turbine Control
As wind turbines become larger and more flexible, the potential benefits of load mitigating control systems become more important to reduce fatigue and extend component life. In the last five years, there has been significant research activity exploring the effectiveness of preview control techniques that may be feasible using advanced wind measurement technologies like LIDAR (light detection and ranging). However, most control development tools use Taylor’s frozen turbulence hypothesis. The end result is that preview measurements made up-stream from the rotor can be obtained with unrealistic accuracy, because the same wind velocities eventually arrive at the turbine. In this study, we extend the spectral methods commonly used to generate turbulent wind fields for controls simulation, but in a way that emulates wind evolution. This changes preview measurements made upwind from the rotor, in such a way that the differences– between the preview measurements and speeds arriving at the turbine– increase with distance from the rotor. We then evaluate the degradation in load mitigation performance of a controller that uses preview measurements obtained at various distances in front of the rotor.