Provided is a method and arrangement of estimating replacement schedule of a, in particular mechanical, component of a wind turbine, the method comprising: estimating remaining producible energy until this component is to be replaced.

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 is disclosed for controlling a wind turbine, where the wind turbine includes with a tower and a rotor and comprises having at least one rotor blade with an adjustable blade pitch angle, and where a change in a power value takes place in a time interval (TE) and by the control of one or more operating parameters which determine power to be fed in by the wind turbine. The method comprises determining a parameterized time function of a tower deflection for the time interval (TE). A series of boundary conditions are defined for the parameterized time function of the tower deflection and a thrust of the rotor of the wind turbine is determined for the parameterized time function of the tower deflection. A function is then calculated for controlling the one or more operating parameters from the thrust of the rotor.

A control system and method of control are disclosed. A model predictive control, MPC, unit is configured to determine a control signal for controlling an operation of the wind turbine based at least in part on a cost function comprising a wear cost relating to one or more types of wear of the winding turbine, and a corresponding cost weighting, which defines a relative weighting of the wear cost in the cost function. A weighting determination unit is configured to receive a reference signal comprising a target wear, receive a feedback signal comprising a wear measure of the wind turbine, and determine, based at least in part on a difference between the target wear and the wear measure, a weighting adjustment for at least part of the cost weighting of the cost function. The MPC unit then sets the cost weighting based at least in part on the weighting adjustment.

A wind turbine and method are provided for defining a plurality of thrust limits for the wind turbine located at a site and having a rotor with rotor blades, wherein the thrust limits define values of aerodynamic thrust on the rotor not to be exceeded in operation. The method includes providing a wind speed distribution representative for the site and defining one or more isolines of constant turbulence probability representing a turbulence parameter as a function of wind speed. The isolines correspond to quantile levels of turbulence of the wind speed distribution and the turbulence parameter is indicative of wind speed variation. The turbulence parameter is determined by continuously measuring wind speed upstream of the rotor with an active sensing system and calculating the wind speed variations from the measured wind speed. Turbulence ranges are defined with respect to the isolines and thrust limits are defined for the turbulence ranges.

A wind turbine and method are provided for defining a plurality of thrust limits for the wind turbine located at a site and having a rotor with rotor blades, wherein the thrust limits define values of aerodynamic thrust on the rotor not to be exceeded in operation. The method includes providing a wind speed distribution representative for the site and defining one or more isolines of constant turbulence probability representing a turbulence parameter as a function of wind speed. The isolines correspond to quantile levels of turbulence of the wind speed distribution and the turbulence parameter is indicative of wind speed variation. The turbulence parameter is determined by continuously measuring wind speed upstream of the rotor with an active sensing system and calculating the wind speed variations from the measured wind speed. Turbulence ranges are defined with respect to the isolines and thrust limits are defined for the turbulence ranges.

The invention relates to a method for determining power set points of a power plant comprising a plurality of power generating units with at least one wind turbine generator. The determination of the power set points are based on a prioritization of the power generating units, where the power generating units are prioritized with respect to individual power levels or fatigue levels obtained for the power generating units. The prioritization is adjusted so that the adjusted prioritization depends both on the power and fatigue levels.

Embodiments of the present disclosure include a data processing and control augmentation system capable of identifying overloading of one or more wind turbine assemblies and providing information to a wind farm controller to reduce a power output of each overloaded turbine. The augmentation system thus reduces the power output of each overloaded turbine and, in turn, reduces loads applied to the wind turbine assembly, such as for a period of time until conditions favorably change. A described analysis of the present disclosure is able to utilize several incoming data streams from sensors so arranged to measure wind effects on blades to calculate and compare cyclic loads to threshold limits to o keep the loads within design limits. The control strategy reduces premature failure of components within the wind turbine assembly, and can be applied across an entire wind farm, even with only a subset of wind turbine assemblies being retrofitted.

The present disclosure relates to methods and systems for determining fatigue loads in a wind turbine. Such a method may comprise obtaining operational metadata representative for an operational situation, and determining whether the operational metadata corresponds to operational metadata from one of a plurality of previously defined operational situations for which fatigue loads are known, the plurality of previously defined operational situations being stored in an operational situations database. If the operational metadata representative for the operational situation substantially corresponds to operational metadata from the stored previous operational situation, then the fatigue loads for the stored previously define operational situation are summed to historically accumulated fatigue loads to determine total accumulated fatigue loads. Methods for registering an operational situation in a wind turbine are also provided.

The present invention relates to a wind turbine and a method of operating a wind turbine for reducing edgewise vibrations, wherein the wind turbine comprises a wind turbine control system having at least one vibration sensor for measuring the edgewise vibrations and a controller for receiving the vibration signal from the vibration sensor. The sensor unit is preferably an accelerometer arranged in a stationary frame of reference. The controller determines at least one whirling mode frequency and the vibration level thereof. The controller initiates a corrective action if the measured vibration level exceeds a threshold value. The corrective action is preferably an adjustment of the pitch angle of the wind turbine blades which in turn dampens the edgewise vibrations.