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.

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 controlling a wind turbine is disclosed, the wind turbine comprising a set of wind turbine blades (1), each wind turbine blade (1) being provided with at least one air deflector (2) being movable between an activated position in which it protrudes from a surface of the wind turbine blade (1) and a de-activated position. The occurrence of an event causing a change in operational conditions is registered, and a new operating state for the wind turbine is determined, the new operating state meeting requirements of the changed operational conditions. The air deflectors (2) of the wind turbine blades (1) and pitch angles of the wind turbines blades (1) are controlled in order to reach the new operating state for the wind turbine, and in such a manner that the control of the pitch angles of the wind turbine blades (1) is performed while taking information regarding the control of the air deflectors (2) into account.

An airfoil performance monitor comprising a housing mounted on a low pressure face of an airfoil, and defining pitot and static pressure orifices; an airspeed-dependent sensor that senses airflow impinging on the pitot orifices and generates a digital airflow signal indicative of turbulence of the airflow; and a controller that derives a turbulence intensity ratio by filtering turbulence values calculated from the digital airflow signal.

A method for determining an incident flow at a rotor blade of a wind power installation is provided. The method includes recording at least part of a pressure spectrum of pressure, in particular wall pressure, at the rotor blade at at least one measurement position. The method includes determining at least two characteristic values from the pressure spectrum, determining an indicator value from a relationship between the at least two characteristic values and assessing whether a critical incident flow is present depending on the indicator value.

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.

Described herein are wave energy conversion systems including actuated geometry components. An example system may include at least one body portion configured to transfer wave energy to a power take off device, and at least one actuated geometry component that is connected to the at least one body portion, the at least one actuated geometry component operable to modify a geometric profile of the system.