A method for determining an available power of a wind farm, wherein the wind farm comprises a plurality of wind power installations with a rotor having rotor blades, the blade angle of which can be adjusted is provided. A wind farm which is set up to carry out the method for determining an available power is provided. The method comprises providing a shading matrix which determines at least one effective wind speed of each of the wind power installations in the wind farm as a function of at least one wind speed and wind direction and wind farm throttling using a park wake model. The method makes it possible to accurately determine an available power of a wind farm even when the wind farm is operated with throttled power.

A method for monitoring a wind turbine including: i) obtaining, from a data storage, a plurality of sets of measurement data of at least two measurement variables, the measurement variables being measurement variables of the wind turbine, acquired by first sensors, and/or the environment of the wind turbine, acquired by second sensors, and the measurement data of a respective set of measurement data being acquired at a same time point in the past; ii) processing the measurement data of the at least two measurement variables by creating an image suitable for visualization; iii) determining a deviation type from a predetermined operation of the wind turbine by processing the image by a trained data-driven model configured as a convolutional neural network, where the image is fed as a digital input to the trained data-driven model and the trained data-driven model provides the deviation type as a digital output.

The invention relates to a method for controlling a wind turbine in partial and full load. In order to avoid disadvantages of switching between partial and full load controllers, the wind turbine control system is configured so that both the partial and full load controller provides control action during partial and full load. For that purpose, the partial and full load controllers are configured with variable gains, wherein gain scheduling is performed so that the gain of partial load controller is larger than the gain of the full load controller during partial load and vice verso so that the gain of the full load controller is larger than the gain of the partial load controller during full load.

A blade pitch controller for a wind turbine includes a nominal control system and a tower feedback loop. The tower feedback loop includes a filtering system. The filtering system is arranged to control wind turbine blade pitch so as to provide additional effective stiffness to the wind turbine in response to motion of the wind turbine which is above a filter frequency of the filtering system.

A method for monitoring of a wind turbine including: a) acquiring respective values of one or more operation variables of the wind turbine at the corresponding operation time point; b) determining the value of a tower clearance resulting from the acquired values of the operation variables with the aid of a trained data driven model, where the value of an output variable which is the tower clearance or a variable correlated with the tower clearance is predicted by feeding the acquired value of each operation variable as a digital input to the trained data driven model which outputs the predicted value of the output variable as a digital output, the tower clearance being shortest the distance between the tower and the tip of a specific rotor blade from the rotor blades when the specific rotor blade is in its lowermost position in which it points downward in the vertical direction.

An optimal dispatching method and system for a wind power generation and energy storage combined system are provided. Uncertainty of a wind turbine output is characterized based on spatio-temporal coupling of the wind turbine output and an interval uncertainty set. Compared with a traditional symmetric interval uncertainty set, the uncertainty set that considers spatio-temporal effects effectively excludes some extreme scenarios with a very small probability of occurrence and reduces conservativeness of a model. A two-stage robust optimal dispatching model for the wind power generation and energy storage combined system is constructed, and a linearization technology and a nested column-and-constraint generation (C&CG) strategy are used to efficiently solve the model.

An optimal dispatching method and system for a wind power generation and energy storage combined system are provided. Uncertainty of a wind turbine output is characterized based on spatio-temporal coupling of the wind turbine output and an interval uncertainty set. Compared with a traditional symmetric interval uncertainty set, the uncertainty set that considers spatio-temporal effects effectively excludes some extreme scenarios with a very small probability of occurrence and reduces conservativeness of a model. A two-stage robust optimal dispatching model for the wind power generation and energy storage combined system is constructed, and a linearization technology and a nested column-and-constraint generation (C&CG) strategy are used to efficiently solve the model.

A method for controlling pitching of at least one rotor blade of a wind turbine includes receiving, via one or more position localization sensors, position data relating to the at least one rotor blade of the wind turbine. Further, the method includes determining, via a controller, a blade deflection signal of the at least one rotor blade based on the position data. Moreover, the method includes determining, via a computer-implemented model stored in the controller, a pitch command for the at least one rotor blade as a function of the blade deflection signal and an azimuth angle of the at least one rotor blade.

The invention provides a method for controlling a wind turbine, including predicting behaviour of one or more wind turbine components such as a wind turbine tower over a prediction horizon using a wind turbine model that describes dynamics of the one or more wind turbine components or states. The method includes determining behavioural constraints associated with operation of the wind turbine, wherein the behavioural constraints are based on operational parameters of the wind turbine such as operating conditions, e.g. wind speed. The method includes using the predicted behaviour of the one or more wind turbine components in a cost function, and optimising the cost function subject to the determined behavioural constraints to determine at least one control output, such as blade pitch control or generator speed control, for controlling operation of the wind turbine.

Methods and apparatuses for controlling reactive power of a wind turbine, and a wind farm are provided. An exemplary method includes: obtaining operation data of single wind turbines in a wind turbine group at the current time point; determining the total maximum capacitive reactive capacity and total minimum inductive reactive capacity, satisfying a safety constraint condition at the next time point, of the wind turbine group; calculating a deviation value of a wind turbine group reactive instruction at the current time point; and updating the wind turbine group reactive instruction on the basis of the acquired, determined, and calculated data so as to perform reactive power control.