A method for retrieving operational data from a wind farm via one or more data hubs is disclosed. Operational data is collected from at least one of the wind turbines of the wind farm at a first data hub at the wind farm. The first data hub initiates transfer of the collected operational data towards a data recipient arranged outside the wind farm, and the operational data is received at the data recipient. The first data hub adds transfer information to the operational data, prior to transferring the operational data towards the data recipient. The added transfer information is transferred along with the operational data, the data recipient thereby receiving the transfer information along with the operational data, thereby enabling the data recipient to back trace a transfer history of the received operational data.

A method for operating a cluster of a plurality of wind turbines is disclosed. For each of the wind turbines, one or more parameter values of a parameter being indicative for a condition occurring at the wind turbine are derived, based the measurements obtained by the wind turbine. In the case that a derived parameter value for a specific wind turbine exceeds a trigger value, measures for mitigating an effect of the condition at the specific wind turbine are initiated. The derived parameter values for the wind turbines of the cluster of wind turbines are compared to an expected distribution of the parameter values. In the case that a distribution of the derived parameter values differs from the expected distribution of the parameter values, the trigger value is adjusted, and the adjusted trigger value is subsequently applied when comparing the derived parameter values to the trigger value.

A method for operating a cluster of a plurality of wind turbines is disclosed. For each of the wind turbines, one or more parameter values of a parameter being indicative for a condition occurring at the wind turbine are derived, based the measurements obtained by the wind turbine. In the case that a derived parameter value for a specific wind turbine exceeds a trigger value, measures for mitigating an effect of the condition at the specific wind turbine are initiated. The derived parameter values for the wind turbines of the cluster of wind turbines are compared to an expected distribution of the parameter values. In the case that a distribution of the derived parameter values differs from the expected distribution of the parameter values, the trigger value is adjusted, and the adjusted trigger value is subsequently applied when comparing the derived parameter values to the trigger value.

A method for monitoring the validity of a calibration of a system parameter is provided. A calibrated system parameter is generated based on the calibration by each of a plurality of spatially associated wind turbines of a wind park. The plurality of spatially associated wind turbines includes a first wind turbine and a second wind turbine. The method includes subtracting from a first signal representing the calibrated system parameter measured at the first wind turbine a second signal representing the calibrated system parameter measured by the second wind turbine in order to generate a difference signal, processing the difference signal by a function based on a stochastic model to generate a decision data signal and determining, based on the decision data signal, if the calibrated system parameter of at least one of the first wind turbine and the second wind turbine is based on an invalid calibration.

A method for retrieving operational data from a wind farm via one or more data hubs is disclosed. Operational data is collected from at least one of the wind turbines of the wind farm at a first data hub at the wind farm. The first data hub initiates transfer of the collected operational data towards a data recipient arranged outside the wind farm, and the operational data is received at the data recipient. The first data hub adds transfer information to the operational data, prior to transferring the operational data towards the data recipient. The added transfer information is transferred along with the operational data, the data recipient thereby receiving the transfer information along with the operational data, thereby enabling the data recipient to back trace a transfer history of the received operational data.

The present invention relates to a multirotor wind turbine comprising at least two rotor nacelle assemblies mounted to a support arrangement via respective yawing systems, and a toe angle control system for controlling the toe angles of the rotor nacelle assemblies with respect to the support arrangement; wherein the toe angle control system is configured to operate in a first mode in which the rotor nacelle assemblies are held at positive toe angles while the wind turbine is generating power in a main production mode; wherein the toe angle control system is further configured to monitor the operating mode of the wind turbine, and to switch to a second mode in which the yawing systems of the rotor nacelle assemblies are operated to reduce the toe angles of the rotor nacelle assemblies if an operating mode-based trigger condition has been met.

An example method includes receiving time-series vibration data for multiple components of multiple wind turbines. Based on the time-series vibration data, multiple groups of wind turbines are defined, as well as first and second vibration thresholds for each group. Time-series vibration data for a component of a particular wind turbine is received. A particular group that includes the particular wind turbine, as well as particular first and second vibration thresholds are identified. A vibration of the component has exceeded the particular first vibration threshold is determined. A forecast of at least one of a period of time before the vibration may exceed the particular second vibration threshold and a future date at which the vibration may exceed the particular second vibration threshold is generated. An alert that includes the particular wind turbine and at least one of the period of time and the future date is generated and provided.

The present invention is a method of determining the free-flow wind speed (V.sub.?) for a wind farm, using measurements (MES), a wind farm model (MOD) and an ensemble Kalman filter (KEN).

A control method, a control device and a wind farm system for a wind turbine frequency support are provided. The control method includes the following: calculating a comprehensive inertia power value by using a wind farm frequency modulation capability level coefficient when a frequency accident occurs in the wind farm; obtaining a real-time rotational speed of each wind turbine to calculate a state factor that changes in real time, where each wind turbine adjusts a state reference power value of its own by exchanging the state factor with a neighboring wind turbine; and determining instantaneous stator power of each wind turbine by using a MPPT part corresponding to the rotational speed, the comprehensive inertia power value, and the state reference power value, so as to control each wind turbine to perform frequency support until a predetermined frequency support time is reached.

The disclosure notably relates to a computer-implemented method for simulating together a plurality of physics simulation instances included in a global physics simulation. The method includes creating a database of local simulation instances. The creating includes providing a set of local simulations. The set of local simulations includes at least two local simulations. A local simulation is a physics simulation that is part of the global physics simulation and that can be computed alone and independently of the multi-physics simulation. Each local simulation of the set of local simulations is already computed. The creating further includes, for each local simulation of the set of local simulations, computing a respective reduced model of the local simulation. The creating further includes, for each local simulation of the set of local simulations, storing in the database a respective local simulation instance. The respective local simulation instance includes the respective computed reduced model.