A system for computing wind turbine estimated operational parameters and/or control commands, includes sensors monitoring the wind turbine, a control processor implementing a model performing a linearization evaluation to obtain a structural component dynamic behavior, a fluid component dynamic behavior, and/or a combined structural and fluid component dynamic behavior of wind turbine operation, and a module performing a calculation utilizing the linearization evaluation of the structural component dynamic behavior, the fluid component dynamic behavior, and/or the combined structural and fluid component dynamic behavior. The module being at least one of an estimation module and a multivariable control module. The estimation module generating signal estimates of turbine or fluid states. The multivariable control module determining actuator commands that include wind turbine commands that maintain operation of the wind turbine at a predetermined setting in real time. A method and a non-transitory medium are also disclosed.

A wind turbine control unit includes an upsampling module that receives a first control signal that includes a current control sample value and a predicted control trajectory. The upsampling module also calculates a second control signal in dependence on the current control sample value and the predicted control trajectory. The second control signal has a higher frequency than the first control signal. The upsampling module further outputs the second control signal for controlling an actuator.

A method for controlling a wind turbine connected to an electrical grid includes receiving, via a controller, a state estimate of the wind turbine. The method also includes determining, via the controller, a current condition of the wind turbine using, at least, the state estimate, the current condition defining a set of condition parameters of the wind turbine. Further, the method includes receiving, via the controller, a control function from a supervisory controller, the control function defining a relationship of the set of condition parameters with at least one operational parameter of the wind turbine. Moreover, the method includes dynamically controlling, via the controller, the wind turbine based on the current condition and the control function for multiple dynamic control intervals.

The invention provides a wind turbine method that includes receiving alarm state data indicating that the wind turbine has entered an alarm state in which operation of the wind turbine has stopped, and receiving sensor data from a plurality of sensors of the wind turbine indicative of operating conditions associated with the wind turbine. When the alarm state data is received, the method includes executing a trained machine learning model based on the received sensor data and the alarm state to obtain an output, where the machine learning model is trained based on historical data associated with a plurality of wind turbines, the historical data being indicative of the plurality of wind turbines previously being in the alarm state. The method includes providing, based on the obtained output, an action to be performed to allow the wind turbine to resume operation.

A computer system suitable for estimating the expected change in annual energy production (AEP) of a wind turbine due to structural deterioration of blades of the wind turbine, said computer system being arranged to execute the following steps: loading a dataset representing estimated lift and drag curves at specific radial locations along the original blade of the wind turbine, building a baseline BEM model of the wind turbine based on said estimated lift and drag curves of the original blade and analysing the model to provide a baseline AEP estimation of the wind turbine with original blades, loading a dataset representing aerodynamic effects of identified structural deteriorations at specific radial locations along each of the blades of the wind turbine, using the dataset of aerodynamic effects to generate modified lift and drag curves at specific radial locations along each of the blades.

A modular wind turbine system and a method of use thereof are provided. The system comprises: a mounting frame; a fixed toroidal support structure attached to the mounting frame, the toroidal support structure having a concave portion and a convex portion; a wind turbine located proximal to the concave portion of the toroidal support structure, wherein the wind turbine travels about at least a portion of the concave portion of the toroidal support structure; and a first baffle, wherein the first baffle extends about the portion of the concave portion of the toroidal support structure about which the first turbine travels, wherein the baffle surrounds a portion of the wind turbine opposite the fixed toroidal support structure, and wherein the baffle includes at least one component selectively variably adjustable so as to vary the force, direction, or disruption of flow of fluid thereby, relative to the wind turbine.

A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller implements a first model to determine a modeled performance parameter for the first wind turbine. The modeled performance parameter is based, at least in part, on an operation of a designated grouping of wind turbines of the plurality of wind turbines, which is exclusive of the first wind turbine. The controller then determines a performance parameter differential for the first wind turbine at multiple sampling intervals. The performance parameter differential is indicative of a difference between the modeled performance parameter and a monitored performance parameter for the first wind turbine. A second model is implemented to determine a predicted performance parameter of the first wind turbine at each of a plurality of setpoint combinations based, at least in part, on the performance parameter differential the first wind turbine. A setpoint combination is then selected based on the predicted performance parameter and an operating state of the first wind turbine is changed based on the setpoint combination.

A control arrangement of a wind turbine includes a watchdog including a reset module and a trigger module, wherein the watchdog reset module is configured to perform an internal reset when a sign-of-life signal is received from a remote communication system within a predetermined time limit, and wherein the watchdog trigger module is configured to issue a watchdog trigger when the predetermined time limit is exceeded; a sensor arrangement including a number of sensors configured to observe local parameters and to report local sensor data; and a wind turbine controller that initiates a local control sequence in response to the watchdog trigger, which local control sequence is configured to switch between a first mode of operation and a second mode of operation on the basis of the local sensor data. A method of operating a wind turbine is further provided.

A control system for a dynamic system including at least one measurement sensor. The system includes at least one computing device configured to generate and transmit at least one regulation device command signal to at least one regulation device to regulate operation of the dynamic system based upon at least one inferred characteristic.

A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller prepares a yaw bias correction function based, at least in part, on a yaw offset function, and on wind speed measurement data and wind direction reference data of a wind event acting on at least a portion of the wind farm. The controller also applies the yaw bias correction function based at least in part on position data of a nacelle of the wind turbine, to yaw the nacelle of the wind turbine.