Abstract: A method of determining an orientation of a nacelle of a wind turbine, wherein the nacelle carries a Global Navigation Satellite System (GNSS) sensor, the method comprising: yawing the nacelle between a series of orientations; obtaining locus data based on a series of calibration positions measured by the GNSS sensor, wherein each calibration position is measured by the GNSS sensor when the nacelle is in a respective orientation of the series of orientations; storing the locus data; after storing the locus data, measuring a new position with the GNSS sensor; and determining the orientation of the nacelle on the basis of the stored locus data and the new position.

Abstract: A method of determining an orientation of a nacelle of a wind turbine, wherein the nacelle carries a Global Navigation Satellite System (GNSS) sensor, the method comprising: yawing the nacelle between a series of orientations; obtaining locus data based on a series of calibration positions measured by the GNSS sensor, wherein each calibration position is measured by the GNSS sensor when the nacelle is in a respective orientation of the series of orientations; storing the locus data; after storing the locus data, measuring a new position with the GNSS sensor; and determining the orientation of the nacelle on the basis of the stored locus data and the new position.

Abstract: A method for operating a cluster of a plurality of wind turbines is disclosed. For each of the wind turbines, one or more parameter values of a parameter being indicative for a condition occurring at the wind turbine are derived, based the measurements obtained by the wind turbine. In the case that a derived parameter value for a specific wind turbine exceeds a trigger value, measures for mitigating an effect of the condition at the specific wind turbine are initiated. The derived parameter values for the wind turbines of the cluster of wind turbines are compared to an expected distribution of the parameter values. In the case that a distribution of the derived parameter values differs from the expected distribution of the parameter values, the trigger value is adjusted, and the adjusted trigger value is subsequently applied when comparing the derived parameter values to the trigger value.

Abstract: A method of transitioning a wind turbine from a sleep state is provided in which a wind speed at the wind turbine is measured, and the measured wind speed is compared to a wake-up threshold. If the wind speed exceeds the wake-up threshold, the wind turbine is transitioned to an active state. Before comparing, either the measured wind speed or the wake-up threshold is adjusted based on an outcome of at least one previous transition from the sleep state of the wind turbine.

Abstract: The invention provides a computer-implemented method of controlling operation of a wind turbine in which a plurality of wind turbine zones are defined. The method comprises, for each of the plurality of wind turbine zones: receiving sensor data from at least one electromagnetic radiation sensor arranged to monitor the respective wind turbine zone; and, determining, based on the received sensor data, whether one or more people are in the respective wind turbine zone. The method comprises selecting an operational mode of the wind turbine based on the determination as to which of the plurality of zones have one or more people therein, and controlling the wind turbine to operate in the selected operational mode.

Abstract: The present invention relates to a method of operating a wind turbine with an operational parameter where values of the operational parameter are obtained by different sensors and compared to determine the validity of the value. A first value and a second value of the operational parameter are obtained different sensors and validated by comparing the two values. The wind turbine being operated using a validated value as the operational parameter. The two sensors are selected among a trained machine learning model, a reference sensor and a computerized physical model.

Abstract: A method for operating a cluster of a plurality of wind turbines is disclosed. For each of the wind turbines, one or more parameter values of a parameter being indicative for a condition occurring at the wind turbine are derived, based the measurements obtained by the wind turbine. In the case that a derived parameter value for a specific wind turbine exceeds a trigger value, measures for mitigating an effect of the condition at the specific wind turbine are initiated. The derived parameter values for the wind turbines of the cluster of wind turbines are compared to an expected distribution of the parameter values. In the case that a distribution of the derived parameter values differs from the expected distribution of the parameter values, the trigger value is adjusted, and the adjusted trigger value is subsequently applied when comparing the derived parameter values to the trigger value.

Abstract: There is provided methods and systems for controlling a multi-rotor wind turbine generator having at least two rotor nacelle assemblies mounted to a support arrangement by a common yaw control system and each having a wind direction sensor mounted thereto configured to measure a wind direction relative to forward direction of its rotor nacelle assembly. The methods comprise the steps of measuring, for each rotor nacelle assembly, wind power parameter data over a plurality of relative wind directions, determining, based on the measured data, an optimum relative wind direction, either based on the average of two directions at which the parameter is maximum or on a combined data set, and controlling the yaw system accordingly.

Abstract: Systems and methods for estimating a direction of wind incident on a wind turbine, the wind turbine comprising a tower; a rotor-nacelle-assembly (RNA) carried by the tower; a deflection sensor configured to sense a position of the RNA or a deflection of the tower; and a wind direction sensor. One approach includes: obtaining deflection training data from the deflection sensor; obtaining wind direction training data from the wind direction sensor; training a machine learning model on the basis of the deflection training data and the wind direction training data in order to obtain a trained machine learning model; obtaining further deflection data from the deflection sensor; inputting the further deflection data into the trained machine learning model; and operating the machine learning model to output a wind direction estimate on the basis of the further deflection data.

Abstract: A wind turbine system comprising: a wind turbine; and a monitoring system, wherein the wind turbine comprises: a tower; an arm extending from the tower, a rotor-nacelle assembly (RNA) carried by the arm; and a Global Navigation Satellite System (GNSS) sensor carried by the arm or the RNA. The monitoring system is configured to receive position data from the GNSS sensor and obtain a moment or force measurement on the basis of the position data.

Abstract: A first aspect of the invention provides a method of controlling a rotor of a wind turbine, the method comprising: obtaining a determination of whether there is ice on the rotor; obtaining one or more factors; generating an ice likelihood based on the obtained one or more factors, wherein the ice likelihood is indicative of whether it is likely that ice is building up on the rotor or thawing on the rotor; generating a confidence level based on the determination and the ice likelihood, wherein the confidence level provides an indication of the confidence that the determination is true; and controlling the wind turbine based on the confidence level.

Abstract: A method of determining an orientation of a nacelle of a wind turbine, wherein the nacelle carries a Global Navigation Satellite System (GNSS) sensor, the method comprising: yawing the nacelle between a series of orientations; obtaining locus data based on a series of calibration positions measured by the GNSS sensor, wherein each calibration position is measured by the GNSS sensor when the nacelle is in a respective orientation of the series of orientations; storing the locus data; after storing the locus data, measuring a new position with the GNSS sensor; and determining the orientation of the nacelle on the basis of the stored locus data and the new position.

Abstract: A method of determining an orientation of a nacelle of a wind turbine, wherein the nacelle carries a Global Navigation Satellite System (GNSS) sensor, the method comprising: yawing the nacelle between a series of orientations; obtaining locus data based on a series of calibration positions measured by the GNSS sensor, wherein each calibration position is measured by the GNSS sensor when the nacelle is in a respective orientation of the series of orientations; storing the locus data; after storing the locus data, measuring a new position with the GNSS sensor; and determining the orientation of the nacelle on the basis of the stored locus data and the new position.

Abstract: An apparatus for monitoring an ambient environment of a wind turbine is described. The apparatus comprises a cooling system comprising first and second heat exchangers, and a fluid circuit arranged to enable coolant to flow between the first and second heat exchangers. The apparatus further comprises a processor configured to: monitor one or more operational parameters of the cooling system; determine an efficiency of the cooling system based on the monitored one or more operational parameters; and calculate a liquid water content of the ambient environment based on the measured efficiency of the cooling system.

Abstract: A method for determining a relative position of wind sensors on a wind turbine comprising: obtaining wind data from each of at least two wind sensors installed on a wind turbine at a location where airflow is affected by a rotor of the wind turbine, the obtaining occurring while the rotor is rotating, identifying oscillations in the wind data from each of the wind sensors, determining a phase or amplitude difference between the oscillations, and determining a relative position of the wind sensors based on the phase or amplitude difference.

Abstract: A wind turbine blade is provided comprising a main blade portion and a light detection and ranging (LIDAR) element. The main blade portion has a shell defining an outer aerodynamic surface of the blade. The LIDAR element is disposed within a volume bounded by the outer aerodynamic surface and comprises at least one LIDAR system configured to transmit light beams away from the blade and to detect reflected light beams incident upon the blade.

Abstract: Embodiments herein describe a method and associated controller for a wind turbine. The method comprises determining one or more characteristics of a sensor signal received from a mechanical sensor of the wind turbine; determining, based on the one or more characteristics of the sensor signal, an icing condition of the wind turbine; and controlling operation of one or more wind turbine systems based on the determined icing condition.

Abstract: According to an embodiment of the present invention there is provided an apparatus for controlling a sub-system of a wind turbine. The apparatus comprises a cooling system comprising first and second heat exchangers, and a fluid circuit arranged to enable a coolant to flow between the first and second heat exchangers; and a processor. The processor is configured to: monitor one or more operational parameters of the cooling system; determine an icing risk based on the one or more operational parameters; and generate a control signal for output to the wind turbine sub-system in dependence on the determined icing risk.

Abstract: Systems and methods for estimating a direction of wind incident on a wind turbine, the wind turbine comprising a tower; a rotor-nacelle-assembly (RNA) carried by the tower; a deflection sensor configured to sense a position of the RNA or a deflection of the tower; and a wind direction sensor. One approach includes: obtaining deflection training data from the deflection sensor; obtaining wind direction training data from the wind direction sensor; training a machine learning model on the basis of the deflection training data and the wind direction training data in order to obtain a trained machine learning model; obtaining further deflection data from the deflection sensor; inputting the further deflection data into the trained machine learning model; and operating the machine learning model to output a wind direction estimate on the basis of the further deflection data.

Abstract: A method for monitoring a wind turbine comprises monitoring an acoustic signal and/or a vibrational signal within a tower of the wind turbine, analyzing the signal to identify one or more predetermined characteristic indicative of an event within the tower, recognizing the event has occurred based on the predetermined characteristic and generating an output based on the recognized event. The one or more predetermined characteristic being at least one of: an amplitude of the signal, a duration of the signal, a shape of the signal, one or more frequencies present in the signal and an energy of the signal.