Abstract: 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.

Abstract: A wind turbine control unit comprising a control module configured to control an actuator system by outputting a first control signal, wherein the first control signal includes a current control sample value and a predicted control trajectory; the control unit further comprising an upsampling module configured to receive the first control signal from the control module, and to output a second control signal for controlling the actuator system, the second control signal having a higher frequency that the first control signal. The upsampling module calculates the second control signal in dependence on the current control sample value and the predicted control trajectory. The embodiments provide a more accurately reproduced control signal at a higher frequency that is suitable for onward processing which does not suffer from the problems of aliasing and delay that exist with conventional upsampling techniques.

Abstract: The invention provides a method for controlling a wind turbine. The method predicts behaviour of the wind turbine components for the time stages over a prediction horizon using a wind turbine model describing dynamics of the wind turbine, where the time stages include a first set of time stages from an initial time stage and a second set of time stages subsequent to the first set. The method determines control outputs, e.g. individual blade pitch, for time stages based on the predicted behaviour. The method then transmits a control signal to implement only the control outputs for each of the second set of time stages so as to control the wind turbine. Advantageously, the invention reduces both average and peak computational loads relative to standard predictive control algorithms.

Abstract: Techniques for controlling loading on a wind turbine blade in the flap-wise direction. A system model has a description of flap loading on the blade and is used to predict flap loading on the blade over a prediction horizon using the system model. A dynamic flap loading limit is determined based on predicted flap loading and a measured flap loading, and a constraint is defined to limit flap loading on the blade based on the dynamic flap loading limit. The predicted flap loading is used in a cost or performance function, and the cost function is optimized subject to the constraint to determine pitch for the blade to control flap loading on the blade. Advantageously, the dynamic limit varies based on discrepancies between predicted and measured flap loading to allow for adaptive back-off from extreme loads prior to such loads building up or being exceeded.

Abstract: A wind turbine system comprising a nacelle mounted on a tower, a rotor having a plurality of blades and a boundary layer control system configured to control airflow through blade surface openings in each of the blades. The wind turbine system includes a control system configured to: monitor an operational speed parameter of the wind turbine, and activate the boundary layer control system if it is determined that the operational speed parameter exceeds a predetermined speed parameter threshold; monitor tower motion and to activate the boundary layer control system based on a determination of excessive tower motion; monitor for a wind turbine shutdown condition, activate the boundary layer control system if it is determined that the shutdown condition has been identified; monitor the aerodynamic loads on the blades, and activate the boundary layer control system based on a determination of excessive blade loads.

Abstract: The invention provides a method for controlling rotor speed of a wind turbine. The method includes defining a system model describing resonance dynamics of a wind turbine component, such as a wind turbine tower, where the system model has a nonlinear input term, e.g. a periodic forcing term. The method includes applying a transform to the system model to obtain a transformed model for response oscillation amplitude of the wind turbine component, where the transformed model has a linear input term. The method includes defining a wind turbine model describing dynamics of the wind turbine, and including the transformed model. A model-based control algorithm, e.g. model predictive control, is applied using the wind turbine model to determine at least one control output, e.g. generator torque, and the control output is used to control rotor speed of the wind turbine.

Abstract: A wind turbine control unit comprising a control module configured to control an actuator system by outputting a first control signal, wherein the first control signal includes a current control sample value and a predicted control trajectory; the control unit further comprising an upsampling module configured to receive the first control signal from the control module, and to output a second control signal for controlling the actuator system, the second control signal having a higher frequency that the first control signal. The upsampling module calculates the second control signal in dependence on the current control sample value and the predicted control trajectory. The embodiments provide a more accurately reproduced control signal at a higher frequency that is suitable for onward processing which does not suffer from the problems of aliasing and delay that exist with conventional upsampling techniques.

Abstract: A main computing system maintains and optimizes a predictive control model for an energy system, wherein the main computing system receives state information for the energy system, optimizes the predictive control model, and generates control rules for control of the energy system. The one or more local computing systems, each have a local memory for storing control rules for controlling the associated local state. The main computing system receives local state information and updates control rules, wherein the updated control rules comprise a subset of the control rules generated by the main computing system selected to be appropriate to the local state information received at the main computing system.

Abstract: The invention relates to control of a wind turbine comprising a plurality of multi-axial accelerometers mounted at different positions in the nacelle and/or in a top portion of the tower. The position and orientation of each accelerometer as mounted is obtained, accelerations in at least two different directions by each accelerometer are measured during operation of the wind turbine. From a number of predetermined mode shapes for the movement of the wind turbine is then determined an absolute position of at least one of the accelerometers during operation of the wind turbine based on the measured accelerations, the mount position and orientation of each accelerometer and the pre-determined mode shapes. Hereby a more precise absolute position during operation is obtained which can be used in the controlling of the turbine.

Abstract: A method of controlling pitch of individual blades in a wind turbine is described, together with a suitable controller. Wind speed is determined as a function of azimuthal angle. Wind speed is then predicted for individual blades over a prediction horizon using this determination of wind speed as a function of azimuthal angle. The predicted wind speed for each individual blade is used in a performance function, which is optimized to control individual blade pitches.

Abstract: The present invention relates to control of a wind turbine system comprising a plurality of wind turbine modules mounted to a common support structure, i.e. to control of a multi-rotor wind turbine system. The invention discloses a control system for a multi-rotor wind turbine system which comprises local controllers operable to control the wind turbine modules in accordance with local control objectives and a central controller configured to monitor the operation of the wind turbine system and based thereon calculate the local control objectives. The central controller is implemented as a model predictive controller (MPC).

Abstract: A method of controlling a wind turbine comprising at least one rotor blade, and at least one accelerometer housed within a nacelle or a tower of the wind turbine. The method comprises: determining a whirling mode frequency for the wind turbine; measuring an acceleration signal that is indicative of the movement of the nacelle of the wind turbine; determining a frequency spectrum of the measured acceleration signal in the proximity of the determined whirling mode frequency; determining a characteristic value that is representative of the energy content of the measured acceleration signal having the determined frequency spectrum; and performing at least one control action if the characteristic value exceeds a predetermined threshold.

Abstract: The present disclosure relates to a control of a wind turbine in connection with power boosting or fast increase of active power production. A boost command is received (63) and based on the current operational state and the boost level a predicted control trajectory is calculated using a model predictive control (MPC) routine (64). The wind turbine is controlled using the calculated control trajectory during the power boost (65).

Abstract: The present invention relates to control of wind turbines where a noise measure is taken into account. Control of a wind turbine is described where a control trajectory is calculated based on noise measure, the noise measure being determined from a predicted operational trajectory. In embodiments the predicted operational trajectories are calculated by using a model predictive control (MPC) routine.

Abstract: The present invention relates to control of wind turbines where a fatigue load measure is taken into account. Control of a wind turbine is described where a control trajectory is calculated based on a fatigue load measure, the fatigue load measure being determined from a predicted operational trajectory. In embodiments the predicted operational trajectories are calculated by using a model predictive control (MPC) routine, and the fatigue load measure includes a rainflow count algorithm.

Abstract: A wind turbine including yaw control comprising a controller receiving an input signal, and providing an output control signal to a yaw actuator. The input signal to the controller is based on: a first feedback signal that is indicative of the relative wind direction determined with respect to the wind turbine, wherein the first feedback signal is filtered with a first low pass filter; and a second feedback signal that is indicative of the activity of the yaw actuator. The control technique of the invention significantly improves the ability of a yaw system to maintain a zero degree yaw error during steady state wind conditions, or in other words to maintain an accurate heading of the nacelle pointing into the wind, as well as reducing the maximum yaw error experienced during yaw system activation.

Abstract: The present invention relates to a method for controlling a power plant for reducing spectral disturbances in an electrical grid being operative connected to the power plant, the power plant comprising a plant controller, at least one wind turbine and at least one auxiliary energy source, wherein the at least one wind turbine comprises a rotor adapted to drive a power generator via a shaft, wherein the generator is connectable with the electrical grid, and at least one damping controller configured to compensate structural oscillations of the wind turbine by controlling a torque on the shaft, wherein the at least one damping controller is capable of setting a limit of a control action on the shaft, the method comprising the steps of determining disturbance information for the power plant in the form of an electrical disturbance at a point of measurement electrically connected to the power plant, determining set-points for the at least one auxiliary energy source based on the determined disturbance information

Abstract: The present disclosure relates to a control system for a wind turbine comprising more controllers and where at least some of the controllers operate at different sample frequencies. The control system comprises at least two controller units, a first controller (10) for determining an operational value (OV) of a sub-system and a second controller (20) for the sub-system. The second controller operates at a higher sample frequency than the first controller. It is disclosed that a faster reaction to a received demand value (V1), received for controlling the sub-system, can be obtained by setting the operational value (OV) of the sub-system as the sum of an internal operational value (V5) and a difference value (V4).

Abstract: The present invention relates to control of wind turbines in a situation where a fault condition is detected. Control of a wind turbine is described where a control trajectory and a safe-mode trajectory are calculated based on the current operational state of the wind turbine. If the fault condition is detected the wind turbine is controlled using the safe-mode trajectory, otherwise, the normal operation of the wind turbine is continued where the wind turbine is controlled using the control trajectory.

Abstract: The present invention relates to control of wind turbines based on predicted operational trajectories. A control system for a wind turbine is described where a main controller calculating one or more predicted operational trajectories and a safety controller validates at least one of the one or more predicted operational trajectories. The control system controls the wind turbine with the predicted control trajectory if the validation is valid, and controls the wind turbine with a safe-mode control trajectory if the validation is invalid. In an embodiment, the main controller is implemented as a receding horizon controller, e.g. in the form of a model predictive controller (MPC).