Doppler wind lidar has gradually replaced traditional meteorological masts with its advantages of high precision and long-range detection, becoming the main method of wind field measurement. In this paper, the observation research was conducted in Zhangbei test site to test the dual-lidar virtual mast method through the combination of two wind lidars for synchronous scanning. On the basis of achieving pointing calibration and time synchronization, the dual-lidar system is used to measure the horizontal wind speed and wind direction at a height of 136 m of the mast. An environmental sensitivity error analysis is also carried out for 1-second wind speed data. The results show that the highly-synchronous dual-lidar system has the ability of replacing the met mast. By comparing with the wind speed of the 136 m cup anemometer in the mast, the mean deviation between the 10-minute and 1-second wind speeds of the dual-lidar system is within -0.04m/s, and the goodness of fit exceeds 0.98. In terms of error, turbulence intensity, wind veer, and flow inclination angle are significant environmental factors that cause second level wind speed errors, resulting in a total uncertainty of 1.9%.
In order to solve the problem of missing nacelle lidar measured wind speed data, a research study was conducted to predict the wind speed using the cabin lidar data as the primary data source. The study involved data preprocessing, where spatial features of wind speed at different distance layers and time series features were combined. A recurrent neural network model based on gated recurrent unit (GRU) was constructed for wind speed prediction. The predicted wind speed data were evaluated for accuracy. The experimental results showed that the proposed method achieved high prediction accuracy, with a correlation coefficient greater than 0.98, root mean square error below 0.85m/s, and average relative error less than 10%. This approach improved the effectiveness and completeness of the nacelle lidar wind speed data, providing valuable insights for the feedforward control and wake control of wind turbine units.
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