A method (2000) for operating a wind turbine (100) including a rotor (106) having rotor blades (108) and a power conversion system (118, 210, 234) mechanically connected with the rotor (106), configured to convert input motive power into electrical output power, and electrically connected to a network (242) for feeding the electrical output power (P) to the network is provided. The method includes initializing (2000), at a first time (t.sub.0), the wind turbine to operate in an overproduction operating mode in which the electrical output power (P(t)) of the power conversion system is increased from an initial electrical output power of the power conversion system by providing kinetic energy stored in the rotor. At a second time (t.sub.2), decreasing (2200) the electrical output power, and integrating a reference power (P.sub.ref, P.sub.0) to determine an energy recovery value (E.sub.rec) are started. An energy response value (E.sub.resp) corresponding to a product of the reference power (P.sub.ref) with a time difference (T.sub.resp) between the second time and the first time is determined (2300). The wind turbine is operated (2400) in a recovery operating mode from a third time (t.sub.3) at which the electrical output power (P) reaches or crosses the reference power (P.sub.ref, P.sub.0) until the energy recovery value becomes at least equal to the energy response value or until the electrical output power reaches or crosses the reference power again from below. In the recovery operating mode, the electrical output power is, limited upwards depending on the reference power and a currently available maximum electrical power output without reducing a speed of the rotor.

Provided is an apparatus and method for cooperative controlling wind turbines of a wind farm, wherein the wind farm includes at least one pair of turbines aligned along a common axis approximately parallel to a current wind direction and having an upstream turbine and a downstream turbine. The method includes the steps of: a) providing a data driven model trained with a machine learning method and stored in a database, b) determining a decision parameter for controlling at least one of the upstream turbine and the downstream turbine by feeding the data driven model with the current power production of the upstream turbine which returns a prediction value indicating whether the downstream turbine will be affected by wake, and/or the temporal evolvement of the current power production of the upstream turbine; c) based on the decision parameter, determining control parameters for the upstream turbine and/or the downstream turbine.

The present disclosure provides a renewable energy generator including a housing formed to float in a body of water, a main generator unit, frame(s) fixed internally of the housing at intervals, a main rotating shaft for linking the main generator unit rotatably to the frame(s), and a controller for operating the pendulum by driving the main motor, and controlling the main generator unit to cause the housing to behave due to the pendulum operation. The main generator unit includes an inner housing, a pendulum moving inside the inner housing, a pendulum rotation shaft vertically connected to the pendulum and fixed to the inner housing, a main motor for converting kinetic energy of the pendulum into electrical energy, and a gear unit linked to the pendulum rotation shaft and transmitting the kinetic energy of the pendulum to the main motor.

A wind turbine control apparatus, method and non-transitory computer-readable medium are disclosed. The wind turbine control apparatus comprises a generator connected to a wind turbine with a drive train. The drive train comprises a rotor, a low speed shaft, a gear box, a high speed shaft, and a controller module. The controller module is configured to obtain a maximum power within a large range of varying wind velocities by operating the rotor at a neural network determined optimal angular speed for the current wind velocity.

A method for determining improved control parameters of a number of wind turbines of a wind park is provided. The method considers the impact of individual turbine manufacturing tolerances on the turbine performance, thereby avoiding under-utilization of those wind turbines. The method includes the steps of: receiving, by an interface, one or more actual manufacturing tolerances of characteristic values for each of the number of wind turbines; determining, by a processing unit, for each of the number of wind turbines a power versus wind speed map which is calculated from a given turbine model with the one or more actual manufacturing tolerances of the respective wind turbines as input parameters; and deriving, by the processing unit, the control parameters for each of the number of wind turbines from their associated power versus wind speed map.

A method for controlling an inclination of a floating wind turbine platform to optimize power production, or to reduce loads on the turbine, tower, and platform, or both, includes receiving data associated with the inclination of the floating wind turbine platform and wind speed and direction data. An angle of difference between the turbine blade plane and the wind direction is determined, where the angle of difference has a vertical component. A platform ballast system is then caused to distribute ballast to reduce the vertical component to a target angle chosen to optimize power production, or reduce turbine, tower, and platform loads, or both.

An aquifer storage and recovery system can include a pump, an electric motor coupled to the pump, a drive unit configured to control operation of the electric motor, and a controller. The controller can be configured to flow water into a well bore from a source reservoir through the pump such that the pump rotates in a reverse direction and drives the electric motor coupled to the pump in the reverse direction to operate as a generator, determine a power output of the electric motor, determine a difference between the power output of the electric motor and a power output set point, and operate the drive unit to control a rotational speed of the electric motor based at least in part on the difference between the power output of the electric motor and the power output set point.

A wave energy converter (WEC) system includes a float, a drivetrain, a reaction structure coupled to the drivetrain by at least one tendon, and a power dissipation system coupled to the drivetrain. The power dissipation system is configured to manage peak loads in the WEC system by dissipating peak energy spikes caused by relative movement of the reaction structure and the float.

To solve the problem of a mis-calibration of a wind turbine a computer-implemented method for re-calibrating at least one yaw-angle of a wind turbine starting from an initial yaw-angle calibration of said wind turbine, based on determining a turbulence intensity estimation value (20) related to said appropriate yaw-angle (10), wherein the turbulence intensity (TI) being a ratio of wind speed deviation to average wind speed over a pre-determined period of time. Further, to solve the problem of a mis-calibration of a wind turbine a system for re-calibrating at least one yaw-angle of a wind turbine based on above re-calibration method. Further, to solve the problem of a management of a wind park below optimum a computer-implemented method for wind park optimization based on simulation calculation including turbulence intensity estimation values (20) estimating said at least one effecting wind turbine (101,102,103) to suffer from wake from said at least one effected wind turbine (100,101,102). Further, to solve the problem of a management of a wind park below optimum a wind park, including a management system for optimizing that wind park based on above optimization method. Moreover, present invention relates to a computer-readable medium comprising such methods.

A method for controlling a wind turbine connected to an electrical grid includes receiving, via a controller, a state estimate of the wind turbine. The method also includes determining, via the controller, a current condition of the wind turbine using, at least, the state estimate, the current condition defining a set of condition parameters of the wind turbine. Further, the method includes receiving, via the controller, a control function from a supervisory controller, the control function defining a relationship of the set of condition parameters with at least one operational parameter of the wind turbine. Moreover, the method includes dynamically controlling, via the controller, the wind turbine based on the current condition and the control function for multiple dynamic control intervals.