A method calibrates a load sensor in a rotor blade of a wind turbine. The method includes checking a state and/or operating parameters of the wind turbine; continuously measuring a calibration condition for the wind turbine and comparing the measured calibration condition with predefined calibration prerequisites; switching to a calibration mode when the measured calibration condition meets the predefined calibration prerequisites or switching to a restricted production mode when the measured calibration condition does not meet the predefined calibration prerequisites; and, collecting measurement data in the calibration mode. The calibration mode is terminated when the required data have been collected for the calibration; and, switched from the calibration mode to an interruption mode. The mode is switched from the interruption mode to the restricted production mode when the measured calibration condition does not meet the predefined calibration prerequisites for longer than a predefined period of time.

A method for determining control parameters of a turbine by consideration of component-relevant temperature limits is provided. The method considers the impact of individual turbine manufacturing tolerances on the turbine performance in a turbine model to determine control parameters for the turbine without damaging it. The method includes the steps of: receiving, by an interface, one or more measurement values of turbine sensors; determining, by a processing unit, at components or turbine places being equipped or not with turbine sensors, one or more virtual parameters and/or temperatures by a simulation of the operation of the turbine, the simulation being made with a given turbine model in which the one or more measurement values and one or more characteristic values of the wind turbine are used as input parameters; and deriving, by the processing unit, the control parameters for the wind turbine from the one or more virtual parameters and/or temperatures.

Provided is a method of estimation of rotor operational characteristics, in particular rotor speed, rotor azimuth and rotation direction, of a rotating rotor of a wind turbine, the method including: measuring pulse rising edge time and pulse falling edge time of pulses generated by each of multiple proximity sensors originating from multiple detection targets arranged on the rotor; estimating values of parameters associated with the sensors and/or targets, in particular parameters associated with the positioning and/or detection range of at least one sensor and/or the parameters associated with the positioning and/or size of at least one target, based on the measured pulse rising edge times and pulse falling edge times; estimating rotor operational characteristics, in particular a rotor speed and/or a rotor azimuth and/or a rotation direction, based on the measured pulse rising and/or falling edge times and/or the estimated values of parameters associated with the sensors and/or targets.

Provided is a method for computer-implemented monitoring of wind turbines in a wind farm each wind turbine including, an upper section being pivotable around a vertical yaw axis wherein the following steps are performed: i) obtaining a digital image of the upper section of the first wind turbine, the image being a current image taken by a camera installed on the upper section of the second wind turbine; ii) determining a yaw misalignment angle between the first and second wind turbines by processing the image by a trained data driven model, where the image is fed as a digital input to the trained data driven model and the trained data driven model provides the yaw misalignment angle as a digital output, the yaw misalignment angle being the obtuse angle between the rotor axis of the first wind turbine and the rotor axis of the second wind turbine.

The present disclosure relates to pitch assemblies and methods for determining one or more pitch references for a pitch control system of a wind turbine. The assembly comprises a wind turbine hub; a pitch bearing including a hub bearing ring configured to be attached to a hub flange and a blade bearing ring configured to be attached to a wind turbine blade; a target configured to be attached to one of the blade bearing ring and the hub; and a sensor configured to be connected to the other of the wind turbine hub and the blade bearing ring, and configured to sense the target such that a position of the target with respect to the sensor can be determined.

A method is provided for determining an orientation of a rotor plane of a wind turbine, including the following steps: determining direction information of a moving part of a wind turbine on basis of at least one signal of a positioning system received at the moving part, determining the orientation of the rotor plane on basis of the determined direction information. Further, a wind turbine and a device as well as a computer program product and a computer readable medium are suggested for performing the method.

The disclosure proposes a yaw calibration method and system for a wind turbine. The calibration method includes: establishing a cylindrical coordinate graph of wind resource distribution based on historical wind farm operation data, to determine a wind direction interval of main inflow wind conditions of a wind farm; calculating an effective value of active power of each wind speed sub-interval, and obtaining a fitted power curve of each refined interval through curve fitting; and setting an angle between a central axis of a refined interval for a fitted power curve corresponding to a calibration curve in each wind speed range and a central axis of the to-be-calibrated wind direction interval as a yaw error calibration value in the wind speed range, to establish a wind speed-yaw error calibration value lookup table; and determining a yaw error calibration value under a current wind direction and a current wind.

A measurement system is provided for a wind turbine having a plurality of rotor blades mounted to a spinner at the front of a nacelle and arranged to rotate in a rotor plane. The measurement system includes a measuring device for determining a pressure at a number of pressure measurement points. The pressure measurement points are arranged in front of the rotor plane, an analysis module for generating a control signal on the basis of the pressure measurements, and output means for issuing the control signal to a controller of the wind turbine.

A method 400 of predicting tonal noise produced by a wind turbine is disclosed. The method comprises acquiring 410 a first set of vibration data, the first set of vibration data being from a plurality of vibration sensors positioned at different locations about a wind turbine drivetrain when the wind turbine drivetrain is undergoing testing in a test rig; acquiring 420 a second set of vibration data, the second set of vibration data being from a plurality of vibration sensors positioned at different locations about the same or a similar wind turbine drivetrain when located in a wind turbine; acquiring 430 noise data including tonal noise produced by the wind turbine; identifying 440 a vibration sensor of interest using vibration data of the second set of vibration data and the noise data; determining 450, for the identified sensor, a first relationship between vibration data of the first set of vibration data and the second set of vibration data; and determining 460, for the identified vibration sensors, a second relationship between the first set of vibration data and tonal noise produced by a wind turbine based on the first relationship.

This application describes a method of detecting an error in a rotor angle sensing system of a wind turbine, where the wind turbine comprises a rotor including a plurality of wind turbine blades, a blade load sensor associated with a respective one of the wind turbine blades, and a rotor angle sensing system configured to output a rotor angle signal. The blade load sensor is configured to output a measured blade load signal. The method comprises generating an estimated blade load signal based on at least the rotor angle signal; comparing the estimated blade load signal with the measured blade load signal to determine a phase difference between them; and identifying an error if the phase difference between the estimated blade load signal and the measured blade load signal exceeds a predetermined threshold.