Improved Data-Driven Yaw Misalignment Calibration of Wind Turbine via LiDAR Verification

Yaw control system (YCS) is the critical part to actively control nacelle direction parallel to the inflow direction. Aiming at the aged units, the YCS would result in the loss of power production due to a shifting error. In this paper, a yaw zero-point misalignment calibration method is proposed to improve wind direction signal accuracy. A 2MW horizontal-axis wind turbine (HAWT) in Huashan wind farm Hubei Province, is selected as the studied object. From the purpose of quantitative analysis, the zero-point shifting error of wind direction sensor, i.e. wind vane, is firstly constructed to illustrate relevance between sensor data and control signal. The improved SCADA data-driven algorithm is then established to assess the value of misalignment, with the comparison of conventional method. Besides, field test and numerical analysis of misalignment calibration with nacelle-mounted lidar are carried out in the case studies, the calibration of both data-driven algorithm and LiDAR test show great consistency, while offset between LiDAR and wind vane measurement is unexpected. Result and following illustration of the proposed test is presented in conclusion, that data-driven algorithm could be used to assess yaw misalignment and refer to the calibration.