According to an embodiment, a method of controlling a temperature of a blade includes generating a first power production curve based on current weather conditions and generating a second power production curve based on future weather conditions. The method also includes, in response to determining that the second power production curve reduces a net power production loss of the blade more than the first power production curve, adjusting a heating cycle of the blade based on the second power production curve rather than the first power production curve.

A system for generating power includes an environmental engine operating on one or more computing devices that determines a wind flowing over a blade of a wind turbine, wherein the wind flowing over the blade of the wind turbine varies based on environmental conditions and operating parameters 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 at least two of a rotor speed, a blade pitch, the wind flowing over the blade, a wind speed and a 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 operating a wind turbine, in particular at a location characterized by a cold climate is provided. The method includes specifying an air density at a location of the wind turbine, setting a blade angle of an adjustable rotor blade based on an output power, torque and/or rotor speed. The method includes setting the blade angle as a function of a pitch characteristic curve which specifies the blade angle as a function of the output power, the torque and/or the rotor speed and as a function of the air density. According to the pitch characteristic curve, the blade angle has a minimum as a function of the air density in a region of a reference density of an atmosphere at the location which is characterized by a cold climate.

A wind turbine control system is disclosed. The wind turbine control system includes a wind turbine, at least one sensor configured to detect at least one environmental condition associated with the wind turbine, and a wind turbine controller communicatively coupled to the wind turbine and the at least one sensor. The wind turbine controller includes at least one processor in communication with at least one memory device. The at least one processor is configured to retrieve at least one wind condition variable associated with the wind turbine, retrieve a power curve, the power curve generated based on the at least one wind condition variable by computing, for each of a plurality of wind speed values, a power value, receive, from the at least one sensor, sensor data, and control the wind turbine using the generated power curve based on the received sensor data.

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.

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 obtaining (322) information (323) on ambient conditions, determining, based on said information, if an erosion criterion is fulfilled, controlling (328) the wind turbine according to an extended mode if the erosion criterion is fulfilled, wherein in the extended mode an angular rotation speed of the wind turbine rotor is allowed to exceed the rated angular rotation speed (214).

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.

According to an embodiment of the present invention there is provided an apparatus for monitoring an ambient environment of a wind turbine. 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; measure 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.

Temperature Control Based on Weather Forecasting Examples are generally directed to techniques for controlling a temperature of a blade, such as a blade in a wind turbine system. One example of the present disclosure is a method of controlling a temperature of a blade. The method includes inputting current weather conditions and future weather conditions into a processor, generating a first power production, generating a second power production curve based on future weather conditions, comparing the first power production curve to the second power production curve, determining which power production curve minimizes a new power production loss of the blade, and adjusting a heating cycle of the blade based on the power production curve that minimizes the net power productions loss of the blade.

Method for de-icing at least one rotor blade of a rotor of a wind power installation, wherein the rotor is able to be operated at a variable rotating speed and the wind power installation generates an output from wind, said method comprising the following steps: checking for an icing situation on the at least one rotor blade, and changing from a normal operation of the wind power installation without de-icing to a de-icing operation if an icing situation has been identified; wherein in the de-icing operation the at least one rotor blade is heated for de-icing, and the rotating speed and/or the generated output are/is reduced as a function of at least one environmental condition of the wind power installation; wherein the at least one environmental condition is selected from the list including an external temperature of the wind power installation and a wind speed in the region of the wind power installation.