Systems and methods for condition-based validation of performance updates are provided. According to one embodiment of the disclosure, a method can include operating an asset under updated settings, ascertaining ambient conditions of the asset and matching the ambient conditions to a condition range, determining whether data completion criteria for the condition range are satisfied and, based at least in part on the determination, selectively switching between using the updated settings for operating the asset and using baseline settings for operating the asset while collecting data points for a predetermined period of time.

A method for operating a wind turbine to avoid stall during derating thereof includes providing an initial pitch setting for one or more rotor blades of the wind turbine. Further, the method includes operating the wind turbine based on a rated power curve with the one or more rotor blades fixed at the initial pitch setting. Further, the method includes identifying at least one condition of the wind turbine that is indicative of stall. The method also includes derating the wind turbine. Further, the method includes modifying the initial pitch setting to an updated pitch setting when the at least one condition is identified.

Embodiments herein describe a system used to estimate the presence of water on a sensor. A parameter maintains a wind sensor temperature. The parameter can be tracked and evaluated to indicate a likelihood of water on the sensor. Alternatively, or in combination with the above, the sensor is adjusted intentionally or deactivated and reactivated to track a parameter response which is then used to indicate a likelihood of water on the sensor.

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.

A method for controlling heating of rotor blades of an aerodynamic rotor of a wind turbine, wherein, the heating of the rotor blades is initiated, if icing of the rotor blades is expected, wherein according to an icing criteria, if icing is expected is evaluated depending on a determined ambient temperature, a determined relative humidity, and a determined wind speed, each defining a determined weather parameter, and further according to the icing criteria, if icing is expected is evaluated depending on a temporal change of at least one of these weather parameters and/or of at least one other weather parameter.

a method of controlling a wind power installation comprising the steps: detecting a precipitation in the region of the wind power installation by a precipitation sensor, and controlling the wind power installation in a first operating mode based on a first pitch angle characteristic in which the pitch angle is set in dependence on the power, and in a second operating mode based on a second pitch angle characteristic, wherein the first operating mode is selected if there is no precipitation and the second operating mode is selected if there is precipitation.

A system for generating power includes an environmental engine operating on one or more computing devices that determines a Reynolds number for a wind turbine, wherein the Reynolds number characterizes wind flowing over a blade of the wind turbine that varies based on the wind speed, a rotor speed and characteristics of the blade of the wind turbine. The system also includes an artificial intelligence (AI) ensemble engine operating on the one or more computing devices that generates a plurality of different models for the wind turbine. Each model characterizes a relationship between the rotor speed and a blade pitch for the wind turbine, the Reynolds number, wind speed and turbulence intensity for the wind turbine. The AI ensemble engine selects a model with a highest efficiency metric; and simulates execution of the selected model to determine recommended operating parameters.

A method for determining an amount of water contamination in oil of a gearbox of a wind turbine includes receiving, via a controller, one or more operational parameters of the wind turbine. The method also includes receiving, via the controller, one or more weather conditions at the wind turbine. Further, the method includes calculating, via the controller, the amount of water contamination in the oil of the gearbox as a function of the one or more operational parameters of the wind turbine and the one or more weather conditions at the wind turbine. In addition, the method includes implementing, via the controller, a corrective action based on the calculated amount of water contamination in the oil of the gearbox.

The present invention relates to a method and controller for heating a wind turbine blade that comprises a plurality of heating zones. An icing factor is determined based on environmental conditions and one or more heating zones are determined based on the determined icing factor, wherein each heating zone comprises one or more Electro-Thermal Heating Elements. The one or more Electro-Thermal Heating Elements corresponding to the determined heating zones are activated to generate heat.

There is presented a method (320) for controlling a wind turbine (100), wherein said wind turbine comprises a wind turbine rotor (102) with one or more blades (103), wherein the wind turbine has a rated angular rotation speed (214) of the wind turbine rotor, said method comprising providing (322) an estimated drop size (324) of rain drops impinging on the one or more blades, determining (326) whether an entry criterion for operation according to a reduced mode is fulfilled, wherein said determining is based at least partially on the estimated drop size (324), controlling (328) the wind turbine according to the reduced mode if the entry criterion is fulfilled, wherein in the reduced mode an angular rotation speed of the wind turbine rotor is limited below an angular rotation speed threshold (216), wherein the angular rotation speed threshold is smaller than the rated angular rotation speed of the wind turbine.