Presentations

Abstract

The purpose of this study is to quantify the effects of yaw misalignment on the performance of the turbine sensors at different inflow conditions, as these sensors need to be used to advance wake steering controllers to be independent of external sensors, such as a meteorological tower. The performance of the turbine sensors is strongly dependent on the yaw angle and the inflow conditions. Systematic measurement errors have been identified both in terms of wind speed and wind direction measured on the nacelle. This can be partly explained by sensors being calibrated exclusively for the aligned turbine operation. At an inflow condition with a strong veer and low wind direction variability, the observed bias was the strongest and decreased at a more unstable condition. The detected mismatch is assumed to be turbine specific as the sensors are heavily influenced by the rotor aerodynamics and possible crossflow components on the nacelle. Well-calibrated nacelle sensors are intrinsically required to detect the inflow conditions necessary for the yaw controller. Utilising erroneous input values for a wake steering strategy can lead to unfavourable yaw angles, thus decreasing the wind farm performance. Therefore, it is essential to correct the input parameters, especially the wind speed, the wind direction variability, and the wind vane misalignment as these are the primary variables affecting wind farm control. This contribution will point out some of the main factors for performing such a calibration. It is suggested to perform a calibration of the cup anemometer and the wind vane at different misalignment settings, while accounting for different atmospheric conditions, in the field when planning a wake steering campaign.