Wind turbine control system including an artifical intelligence ensemble engine

A system for generating electric power comprising:

• an environmental engine, operating on one or more computing devices that determines a set of performance metrics for each wind turbine of a plurality of wind turbines deployed at a plurality of windfarms, the plurality of wind turbines comprising a first wind turbine of a first windfarm, the performance metrics associated with the first wind turbine characterizing wind flowing over blades of the first wind turbine based on a wind speed of the first wind turbine;
• an artificial intelligence (AI) ensemble engine operating on the one or more computing devices is configured to:
• generate a set of models for each wind turbine of the plurality of wind turbines, wherein each model of the set of models is generated with a different machine learning algorithm;
• select a model based on a computational resource cost of each model in the set of models for each turbine of the plurality of wind turbines;
• and
• simulate execution of the selected model for each wind turbine of the plurality of wind turbines to determine recommended operating parameters for each of the plurality of wind turbines;
• and
• a plurality of edge computing systems, wherein each edge computing system is proximal to a corresponding windfarm and each edge computing system instantiates a virtual turbine controller for each wind turbine in response to receipt of models for each wind turbine in the first windfarm, and each virtual turbine controller has operating parameters that match operating parameters of a corresponding turbine controller coupled to a corresponding wind turbine in the first windfarm.

A method for controlling a system for generating electric power comprising:

• determining, by an environmental engine operating on one or more computing devices, a set of performance metrics for each wind turbine of a plurality of wind turbines deployed at a plurality of windfarms, the plurality of wind turbines comprising a first wind turbine of a first windfarm, and the performance metrics associated with the first wind turbine characterizing wind flowing over blades of the first wind turbine based on a wind speed of the first wind turbine;
• generating, by an artificial intelligence (AI) ensemble engine operating on the one or more computing devices, a set of models for each wind turbine of the plurality of wind turbines, wherein each model of the set of models is generated with a different machine learning algorithm;
• selecting, by the AI ensemble engine, a model based on an estimated accuracy of each model of the set of models for each turbine of the plurality of wind turbines;
• simulating, by the AI ensemble engine, execution of the selected model for each wind turbine of the plurality of wind turbines to determine recommended operating parameters for each of the plurality of wind turbines;
• receiving, at a plurality of edge computing systems the selected model and corresponding recommended parameters for each wind turbine of the plurality of wind turbines;
• and
• instantiating, by each edge computing system, a virtual turbine controller for each wind turbine in response to receipt of models for each wind turbine, and each virtual turbine controller has operating parameters that match operating parameters of a corresponding turbine controller coupled to a corresponding wind turbine in the first windfarm.