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.

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 mass damper module (600) for a wind turbine installation comprises: an attachment interface (603a-d) adapted to removably attach the mass damper module to structural lifting parts (303a-d) of a nacelle (300) of the wind turbine installation; and an active tuned mass damper (601) controllable to damp vibration of the wind turbine installation when the mass damper module is so attached to the nacelle and the nacelle is attached to a tower (200) to form the wind turbine installation.

A wind turbine has a Lidar device to sense wind conditions upstream of the wind turbine. Signals from the wind turbine are processed to detect an extreme change in wind direction. The detection is performed by differentiating the rate of change of wind direction and filtering for a period of time. On detection of extreme change the system controller takes the necessary evasive action which may include shutting down the turbine, commencing an immediate yawing action, and de-rating the turbine until the yawing action is complete.

A method for predictive monitoring of the condition of wind turbines is disclosed. The method may include selecting at least one wind turbine inside a wind farm and at least one component of the wind turbine; acquiring SCADA data comprising operational data of the wind farm and temperature values of the at least one component of the wind turbine during a preselected time period, calculating differential data as a difference between the temperature values of the selected turbine component of the selected wind turbine and an average temperature of the selected wind turbine component in at least two wind turbines in the wind farm; defining a monitoring time period to monitor the component; calculating at least one predetermined statistic of the differential data during the monitoring time period, and saving the predetermined statistic as a monitoring feature; and testing if at least one monitoring feature exceeds a threshold value.

Model-based predictive control method (MPC) for the reduction of structural load in wind turbines comprising: exclusively proposing a single internal linear model for the MPC for the entire operating range of the turbine; obtaining the adjustable parameters of the linear internal model from the experimental data previously measured in the turbine; choosing the discrete time values for the control and prediction horizons; adjusting the MPC controller and performing a practical implementation test.

A wind turbine has a Lidar device to sense wind conditions upstream of the wind turbine. Wind speed signals from the wind turbine are processed to detect an extreme operating gust. The detection is performed by differentiating the axial wind velocity and filtering for a period of time. On detection of extreme operating gust the system controller takes necessary evasive action which may include shutting down the turbine or varying the blade pitch angle.

The present invention is a method for predicting a swell-resulting characteristic for a floating system. The method updates (MAJ) a spectral model (MSH) of the swell to form a swell prediction model (MPR). This model is applied to real-time measurements (MES) to predict the swell-resulting characteristic (pred).

A method for controlling heating of rotor blades of an aerodynamic rotor of a wind turbine, wherein, the heating of the rotor blades is initiated, if icing of the rotor blades is expected, wherein according to an icing criteria, if icing is expected is evaluated depending on a determined ambient temperature, a determined relative humidity, and a determined wind speed, each defining a determined weather parameter, and further according to the icing criteria, if icing is expected is evaluated depending on a temporal change of at least one of these weather parameters and/or of at least one other weather parameter.