A method for operating a wind turbine for generating a settable turbine power, where the wind turbine includes a rotor having rotor blades adjustable in their blade angle, is operable at a settable rotor speed, and is installed at an installation site at a distance to an obstacle, comprises the obstacle causing a wind disturbance, which, in dependence on current wind direction and wind velocity, can reach the wind turbine as a wind wake, and the wind turbine reducing its turbine operation by throttling down for protection against loads due to the wind wake, wherein the throttling down is controlled in dependence on the current wind direction and the current wind velocity, wherein a weather prediction is used in order to take into consideration at least one further weather property in addition to the wind direction and wind velocity, and wherein the throttling down is additionally controlled in dependence on the weather prediction, in particular on the further weather property.

A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

In some examples, a system receives first sensor data from respective wind turbines of a plurality of wind turbines. For instance, the first sensor data may include at least a power output and a wind speed per time interval. The system trains at least one respective model for each respective wind turbine based on the first sensor data received from that respective wind turbine. Further, the system receives, for a second time period, respective second sensor data from the respective wind turbines. The system executes, using the respective second sensor data, the respective model trained using the first sensor data received from that respective wind turbine to determine, for each respective wind turbine, a predicted power output for an upcoming period. The predicted power outputs may be aggregated to determine a total predicted power output and at least one action is performed based on the total predicted power output.

A method, system and device for an electric generator comprising dynamically selectable number of generator disk assemblies.

The present invention relates to a method allowing short-term prediction of the wave motion (force, elevation, . . . ), from a time series of past wave measurements. The prediction method according to the invention is based on the estimation of the variable coefficients of an autoregressive model while allowing multi-step minimization, that is over a horizon of several time steps in the future, of the prediction error.

A method includes training a prediction model to forecast a likelihood of curtailment for at least one wind turbine. The prediction model is trained, by a processor system, using historical information and historical instances of curtailment. The method also includes forecasting the likelihood of curtailment for the at least one wind turbine using the trained prediction model. The method also includes outputting the forecasted likelihood.

Wind turbine farms are presented including: a number of steerable wind turbines, where each of the steerable wind turbines includes a turbine diameter and a blade center locus, where each of the steerable wind turbines are separately and axially steerable about a vertical axis to align with one or more prevailing wind directions, where the steerable wind turbines is arranged in one or more modules, where each of the modules is defined by at least two steerable wind turbines, where each of the at least two steerable wind turbines in a module is positioned in a fixed position.

A method of parameterizing a controller of a first wind energy installation wherein the controller sets a manipulated variable of the wind energy installation as a function of an input variable. An artificial intelligence determines at least one value of a parameter of the controller for at least one state/degree of being iced up of the wind energy installation based on a power curve, load, and/or downstream flow of the wind energy installation predicted with a mathematical model of the wind energy installation for at least one state/degree of being iced up, and/or determines at least one value of a parameter of the controller for at least one state/degree of being iced up of the wind energy installation, based on at least one determined state/degree of being iced up and a power, load, and/or downstream flow of the wind energy installation and/or at least one second wind energy installation.

A multi-farm wind power dispatch management system is provided which includes wind turbine dispatch controllers for controlling wind power dispatch of respective wind farm components and wind farm dispatch management systems for receiving respective wind farm component operating parameters and generating respective farm-level operating parameters. The system also includes group dispatch management systems for receiving the farm-level operating parameters and generating respective group level operating parameters. The system also includes a master dispatch management system for receiving the group-level operating parameters; computing a real time output power generated by the wind farm components; determining a difference between the real time output power and a committed output power; and generating reference commands, based on the difference, for controlling at least one of, the wind farm component operating parameters, the farm-level operating parameters, the group level operating parameters, or combinations thereof to reduce the difference and dispatch the committed output power.

A method of controlling a wind turbine having a nacelle, a rotor, a rotating hub, a first rotor blade and at least a second rotor blade, both rotor blades being mounted to the hub. The method includes measuring the strain in the first rotor blade by a strain measurement device attached to the first rotor blade; and choosing the operational parameters of the wind turbine based on the measured strain such that fatigue damage of the second rotor blade is reduced. A wind turbine is controlled by such a method.