The invention relates to a method for acquisition and modelling of an incident wind field by a LiDAR sensor. Acquisition and modelling include a step of estimating the wind amplitudes and directions for a set of discretized points, and a step of incident wind field reconstruction in three dimensions and in real time. The invention also relates to a method of controlling and/or monitoring a wind turbine equipped with such a LiDAR sensor from the incident wind field reconstructed in three dimensions and in real time.

Provided are a feedforward control method, apparatus and control system for a wind turbine. The feedforward control method includes: acquiring, by means of a remote sensing measurement apparatus, inflowing wind information of a plurality of spatial point positions in front of a wind turbine, wherein the plurality of spatial points are distributed in a plurality of different cross sections, and the distances between the plurality of different cross sections and the wind turbine are different; combining the acquired inflowing wind information into a target wind velocity; predicting, on the basis of the combined target wind velocity, incoming flow arrival time required for inflowing wind at a target point to arrive at an impeller plane; and performing feedforward control on the wind turbine according to the predicted incoming flow arrival time.

The present invention relates to a method of determining the wind speed in the plane of a rotor (PR) of a wind turbine (1), by measuring (MES2) the rotational speed of the rotor, the angle of the blades and the generated power. The method according to the invention uses a wind turbine model (MOD) constructed from wind speed measurements (LID), and by use of measurement clustering (GRO) and regressions (REG).

The present invention relates to a method of controlling a wind turbine by automatic online selection of a controller that minimizes the wind turbine fatigue. The method therefore relies on an (offline constructed) database (BDD) of simulations of a list (LIST) of controllers, and on an online machine learning step for determining the optimal controller in terms of wind turbine (EOL) fatigue. Thus, the method allows automatic selection of controllers online, based on a fatigue criterion, and switching between the controllers according to the measured evolution of wind condition.

A method of controlling at least one adaptable airflow regulating system, in particular spoiler and/or flap, of at least one rotor blade of a wind turbine having a wind turbine tower includes: determining a quantity related to a distance between the rotor blade and the wind turbine tower; controlling the airflow regulating system based on the quantity.

A method to operate a wind turbine is provided, the method including determining a correction model associated with the wind turbine, determining a corrected turbulence intensity parameter associated with the wind turbine based on the correction model, and operating the wind turbine based on the corrected turbulence intensity parameter.

A control system for yawing a wind turbine rotor relative to the wind and for changing the pitch of rotor blades. A wind direction parameter is measured by a wind direction sensor. The wind direction is calibrated as a function of a predetermined offset parameter, and then adjusted as a function of a wind direction compensation parameter. The adjusted relative wind direction is then used in the determining of a control parameter of the wind turbine. The parameters for the calibration and adjustment of the relative wind direction are obtained from a set of data comprising the wind direction relative to the wind turbine over time and as measured by the wind direction sensor on the wind turbine and as measured by a second wind direction sensor.

A method for operating a wind turbine farm includes a plurality of wind turbines arranged together in a wind turbine farm area. each wind turbine includes a tower, a generator system for generating electric power and a rotor provided with a number of rotor blades on a rotor axis coupled to the electric generator for driving the generator, the rotor being arranged on the tower. The method includes: providing a wind turbine farm control for controlling operational parameters for each of the wind turbines; providing a measurement or a prediction of a vertical wind shear profile located above a level of the rotors of the wind turbines; based on a value of the measured or predicted vertical wind shear profile determining an adjustment of one or more operational parameters for each of the wind turbines such that a yield of electric power of the wind turbine farm is optimized with respect to the measured or predicted vertical wind shear profile, and adapting the operational parameters of the one or more wind turbines according to the adjustment.

A method for controlling a wind energy installation having a rotor which is rotatable about a rotor axis and which has at least one rotor blade and a generator coupled thereto. The method includes detecting a value of a forefield parameter, in particular a forefield wind parameter, which is present at a first point in time and in a first region which first region is at a first distance from the wind energy installation, in particular from the rotor blade, in particular detecting a sequence of values of the forefield parameter up to the first point in time with the aid of at least one sensor, and controlling the generator and/or at least one actuator of the wind energy installation on the basis of this detected forefield parameter value, in particular this detected forefield parameter value sequence, and a machine-learned relationship of a predicted near field parameter, in particular a predicted near field wind parameter, at the wind energy installation and/or of an operating parameter of the wind energy installation predicted for a later, second point in time and/or of a control variable of the actuator and/or of the generator to the forefield parameter or the forefield parameter sequences.

A method for determining a correction function for a wind turbine, a method and system for determining an alignment correction function for a nacelle of a wind turbine, and a method for operating a wind turbine are provided. Measurement values of the power measure of the wind turbine and of the leeward wind direction are assigned to measurement values of the leeward wind speed, corrected by a correction function, and are grouped into at least one wind-speed bin on the basis of instants at which the measurement values were recorded. A model function is determined and outputted for a relationship between the power measure and the leeward wind direction for the wind-speed bin, and an alignment correction function is determined for a target alignment of the nacelle relative to the measured leeward wind direction on the basis of the model function.