A wind turbine is disclosed which comprises a control system configured to execute at least one ice removal routine which comprises a heating stage of at least one of the blades (3), and a mechanical removal ice stage. A wind turbine removing ice method is also disclosed which comprises a stage wherein the presence of ice is detected on at least one of the blades and, once said presence of ice is detected, comprises a stage wherein at least one ice removal routine is activated which comprises, in turn, a heating stage of at least one of the blades and a mechanical removing ice stage on at least said blade.

A method of controlling a wind turbine, wherein a minimum required hydraulic pressure represents a hydraulic pressure of at least one accumulator of the wind turbine which is required to pitch at least one blade of the wind turbine which is associated with the accumulator into a stop position of the wind turbine, and wherein a pitch angle represents a pitch angle of a normal of the at least one blade of the wind turbine relative to an incoming wind direction. The method includes (a) determining a minimum requirement function of the minimum required hydraulic pressure dependent on the pitch angle, (b) detecting a current hydraulic pressure in the at least one accumulator at a current pitch angle of the at least one blade, and (c) controlling the wind turbine such that the current hydraulic pressure is above the minimum required hydraulic pressure at the current pitch angle.

The present disclosure relates to a method for operating a wind power installation, in particular for identifying unusual oscillation events, and an associated wind power installation and a wind farm. The method comprises the steps of: providing a parametrized limit for a value of an observed oscillation of a component of the wind power installation; determining a current limit from the parametrized limit taking account of at least one current ambient parameter, in particular an ambient parameter that is indicative for the current incident flow; determining a current value of the observed oscillation of the component; comparing the current value of the observed oscillation of the component with the current limit; and operating the wind power installation on the basis of the result of the comparison.

A wind turbine control architectures, including a turbine control portion which is configured to control at least one component of a wind turbine, and a turbine data storage portion which is configured to store a data storage container therein is provided. The turbine control portion and the turbine data storage portion communicate with each other via an inter-process communication.

A method includes receiving, via one or more turbine-level controllers, an indication of at least one of a communication loss between the one or more turbine-level controllers and a farm-level controller, a detection of an absence of reactive power regulation by the farm-level controller, or a reactive power command of the farm-level controller being equal to or above a saturation threshold during transitioning between a baseline operational mode and reactive power mode, the reactive power mode being characterized in that only reactive power is generate. Upon receipt of the indication, the method includes adjusting a reactive power response of one or more reactive power regulators of the one or more turbine-level controllers so as to avoid an overshoot reactive power event or an undershoot reactive power event at the point of interconnection.

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.

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.

A wind turbine is disclosed which comprises a control system configured to execute at least one ice removal routine which comprises a heating stage of at least one of the blades (3), and a mechanical removal ice stage. A wind turbine removing ice method is also disclosed which comprises a stage wherein the presence of ice is detected on at least one of the blades and, once said presence of ice is detected, comprises a stage wherein at least one ice removal routine is activated which comprises, in turn, a heating stage of at least one of the blades and a mechanical removing ice stage on at least said blade.

A method and apparatus for applying optimized yaw settings to wind turbines including receiving operating data from at least one wind turbine on a wind farm and sending the data to a supervisory control and data acquisition (SCADA) system on the at least one wind turbine to generate current SCADA data. The current SCADA data is sent a central processing center away from the wind farm. The central processing center includes an optimization system that can generate a new look up table (LUT) including at least one new wind turbine yaw setting calculated using information comprising wind direction, wind velocity, wind turbine location in the wind farm, information from a historic SCADA database, and yaw optimizing algorithms. The new LUT is then sent to a yaw setting selection engine (YSSE) where instructions regarding the use of the new LUT are generated.

According to the disclosure, an artificial intelligence (AI) model receives a power production amount, a power production efficiency, a control variable and the like states as input information through information exchange between a wind turbine and the AI model, and therefore it is possible to provide a control method using the AI model with regard to even the wind turbine given no power coefficient.