Control of a wind turbine based on predicting amplitude modulation (am) noise

An electronic device comprising a memory circuitry, a processor circuitry, and an interface, wherein the electronic device is configured to perform an operation controlling a wind turbine, the operation comprising:

• obtaining wind turbine data associated with the wind turbine, wherein the wind turbine data is indicative of conditions of operation of the wind turbine;
• predicting an Amplitude Modulation (AM) noise parameter indicative of AM noise within a region at a distance from the wind turbine by applying a machine learning model to the wind turbine data;
• generating, based on the AM noise parameter, control data indicative of a control operation of the wind turbine;
• and
• providing the control data to a controller for controlling the wind turbine in accordance with the control data.

A wind turbine system, comprising:

• a tower;
• a nacelle disposed on the tower;
• a rotor extending from the nacelle and having a plurality of blades at one end thereof;
• and
• an electronic device configured to control an operation, comprising:
• obtaining wind turbine data associated with the wind turbine, wherein the wind turbine data is indicative of conditions of operation of the wind turbine;
• predicting an Amplitude Modulation (AM) noise parameter indicative of AM noise within a region at a distance from the wind turbine by applying a machine learning model to the wind turbine data;
• generating, based on the AM noise parameter, control data indicative of a control operation of the wind turbine;
• and
• providing the control data to a controller for controlling the wind turbine in accordance with the control data.

A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed on any combination of one or more processors, carry out an operation controlling a wind turbine, the operation comprising:

• obtaining wind turbine data associated with the wind turbine, wherein the wind turbine data is indicative of conditions of operation of the wind turbine;
• predicting an Amplitude Modulation (AM) noise parameter indicative of AM noise within a region at a distance from the wind turbine by applying a machine learning model to the wind turbine data;
• generating, based on the AM noise parameter, control data indicative of a control operation of the wind turbine;
• and
• providing the control data to a controller for controlling the wind turbine in accordance with the control data.