Disclosed are a method and apparatus for detecting a yaw-to-wind abnormality. The method includes: acquiring a wind direction deviation angle within a specified time period; calculating a power performance index, wherein the power performance index is a dimensionless number used to characterize power generation performance of a wind turbine; determining an optimal wind direction deviation angle based on the power performance index; determining a current wind direction deviation angle according to probability distribution of the wind direction deviation angle; and if a difference between the optimal wind direction deviation angle and the current wind direction deviation angle is greater than a preset threshold, determining that a yaw-to-wind abnormality is detected. Compared with the related technology in which yaw-to-wind detection is performed through a power fitting curve, in the technical solution according to the embodiments of the present disclosure, a power index is directly used, which avoids the problem of poor power curve fitting effect and improves the accuracy of yaw-to-wind detection.

In a vertical rotor apparatus that rotates in response to a moving fluid, a shaft defines an axis of rotor rotation. Rotor blades are longitudinally aligned in parallel with the shaft and each rotor blade defines an axis of blade rotation. A sensor generates a signal when any of the rotor blades are within rotor azimuthal angles of blade stall regions. A controller generates blade pitch information for the blade stall regions and an actuator, which is mechanically coupled to each of the rotor blades, alters blade pitch about the axis of blade rotation in accordance with the blade pitch information.

A system and method are provided for controlling a wind farm during low wind speeds. Accordingly, the farm controller designates at least one of the plurality of wind turbines of the wind farm as a designated turbine. The designated turbine is operating in a full auxiliary mode when the speed of the wind acting on the wind farm is below a wind speed threshold. The remaining wind turbines are operated in a reduced auxiliary mode. The reduced auxiliary mode includes the disabling of at least one of pitching and yawing of the remaining wind turbines. When a power output for the designated wind turbine exceeds a power threshold, the farm controller directs at least one group of the remaining wind turbines to transition from the reduced auxiliary mode to the full auxiliary mode. During certain grid conditions, the transition between auxiliary modes may be delayed.

The present disclosure is directed to a system and method for assessing farm-level performance of a wind farm. The method includes operating the wind farm in a first operational mode and identifying one or more pairs of wind turbines having wake interaction. The method also includes generating a pairwise dataset for the wind turbines pairs. Further, the method includes generating a first wake model based on the pairwise dataset and predicting a first farm-level performance parameter based on the first wake model. The method also includes operating the wind farm in a second operational mode and collecting operational data during the second operational mode. Moreover, the method includes predicting a first farm-level performance parameter for the second operational mode using the first wake model and the operational data from the second operational mode. The method further includes determining a second farm-level performance parameter during the second operational mode. Thus, the method includes determining a difference in the farm-level performance of the wind farm as a function of the first and second farm-level performance parameters.

Methods, apparatuses, and systems for collecting the installation error of the wind vane are provided. The image of the blades of the wind turbine and the outer rotor of the generator is obtained. It is determined whether the wind vane is aligned with the center line of the wind turbine, according to a relationship between the center line of the wind turbine and the orienting plane of the wind vane in the image. In a case that the wind vane is not aligned with the center line of the wind turbine, the deviation angle between the wind vane and the center line of the wind turbine is calculated, and a direction of the wind vane is corrected according to the deviation angle. Therefore, installation errors of the wind vane are accurately determined and corrected, and accuracy is improved for installation of the wind vane.

Methods for assessing the useful life that may remain for a portion of a wind turbine support structure. The methods may include identifying an overall expected useful life for the portion of the support structure and estimating an expended life from the extent of loading that has occurred to the portion of the support structure during the operative life of a wind turbine. The useful life remaining for the portion may be determined by subtracting the expended life from the overall expected useful life.

A wind turbine has a Lidar device to sense wind conditions upstream of the wind turbine. Signals from the wind turbine are processed to detect an extreme change in wind direction. The detection is performed by differentiating the rate of change of wind direction and filtering for a period of time. On detection of extreme change the system controller takes the necessary evasive action which may include shutting down the turbine, commencing an immediate yawing action, and de-rating the turbine until the yawing action is complete.

Embodiments of the present disclosure include a retrofit auxiliary nacelle yaw position control system that enables advanced nacelle yaw position control of a wind turbine by comparing a desired nacelle yaw position signal with the actual nacelle yaw position and generating a virtual relative wind direction signal that is provided to the existing turbine control unit. This method and system enable implementation of wake steering, collective yaw optimization and dynamic yaw optimization of a collection of wind turbines referred to as a wind plant. Modification of the existing turbine control unit is not required, greatly simplifying the implementation process of advanced yaw control strategies on existing wind plants.

A method is for controlling a wind turbine. The wind turbine has a tower, a nacelle, a rotor with at least two rotor blades and a yaw system with at least one yaw drive configured to rotate the nacelle about a vertical axis of the tower (yaw axis). A control signal for the at least one yaw drive depends on at least one signal indicative of the wind direction. The control signal for the at least one yaw drive further depends on at least one value indicative of a vibration mode of the rotor blades.

The present disclosure is directed to a system and method for micrositing a wind farm having a plurality of wind turbines. The method includes (a) determining, via a loads optimization function, one or more wind directions with or without turbine shadow for each of the wind turbines in the wind farm, (b) determining, via the loads optimization function, at least one additional wind parameter for each of the wind directions, (c) calculating, via simulation, loads for each of the wind turbines in the wind farm based on the identified wind directions with or without turbine shadow for each of the wind turbines in the wind farm and the at least one additional wind parameter for each of the wind directions, and (d) determining a site layout for the wind farm based on the calculated loads.