A wind turbine controller for controlling power production of a wind turbine is provided. The wind turbine is arranged within a wind farm coupled to a public power network via a point of common coupling. The wind turbine controller has a receiving unit for receiving a measured value of a property of the wind farm taken at the point of common coupling and for receiving a reference value for the property, and a control unit for controlling the power production of the wind turbine by regulating a local property of the wind turbine based on the received measured value and the received reference value such that the measured value of the wind farm taken at the point of common coupling corresponds to the reference value. Further, a wind turbine having such a controller, a wind farm and a method for controlling a power production of a wind turbine are provided.

A battery storage and/or a wind turbine including the battery storage. A generator for generation of an electric current. An electric flow path configured for conducting the electric current to an electric grid via a power converter, the power converter. The battery storage electrically connected to the electric flow path, the battery storage comprising a plurality of battery cells, each battery cell comprising at least one battery element and at least two semiconductor switches. A controller is configured for selectively controlling the voltage over the battery storage by controlling the status of the at least two semiconductor switches of a plurality of the battery cells, and thereby whether a current path through the battery storage is bypassing the at least one battery element or passing through the at least one battery element of one or more of the plurality of battery cells.

The present disclosure describes an air filtration device that operates a fan-speed sensor error elimination process. The air filtration device uses a PID control module to ensure its fan operates at a desired fan speed. The fan-speed sensor error elimination process ensures that the air filtration device's controller does not send a measured fan speed determined using data that represent the time it takes the fan blade to complete a fraction of a revolution to the PID control module. This ensures the PID control module accurately controls electrical current supplied to the fan motor.

A direct-drive wind turbine comprises a wind turbine rotor and a generator mounted on a frame. The wind turbine rotor comprises a hub carrying blades and the generator comprises a generator stator comprising a track structure and a stator surface connected to the track structure, wherein the stator surface has coil windings, and carriages connected one after the other and adapted to run on the track structure, wherein the carriages carry an electrically magnetically active material facing the stator surface such that when the carriages run along the track structure a magnetic field is generated across an air gap provided between the carriages active materials and the stator coil windings, wherein one or more carriages are directly coupled to the wind turbine rotor by rigid connectors such that rotation of the wind turbine rotor causes displacement of the carriages along the track.

The disclosure provides a method and a system for calculating a stability margin domain of the control parameters of a hydraulic turbine regulating system, which belongs to the technical field of stability margin analysis of the hydraulic turbine regulating system. The method includes: determining a high-order state space model of the hydraulic turbine regulating system; determining a dominant eigenvalue and an interference eigenvalue of a state matrix of the high-order state space model; determining an associated state variable of the interference eigenvalue; determining the interference eigenvalues under different target control parameter conditions; determining whether a target control parameter meets a stability margin requirement; and determining the stability margin domain of the control parameter. The present disclosure can accurately calculate the stability margin domain of the complex hydraulic turbine system and help operators quickly identify the control parameters adjustment range meeting adjustment and attenuation requirements of the system.

A power generator comprises a casing (110) that in use is deployed in an environment in which the casing is subjected to an excitation motion such as wave motion. A series of masses (101, 103a-c) is located within the casing, wherein at least a first mass is coupled to the casing by a first spring (102), each of the masses is coupled to at least one adjacent mass by a respective spring, and wherein the casing and the series of masses bring a motion of the power generator into resonance with the excitation motion. A plurality of electric machines each comprising a stator and a field source are each associated with a corresponding mass such that a relative motion of a mass and associated electric machine generates electrical power. A power takeoff circuit receives generated electrical power from the plurality of electric machines and outputs electrical power from the power generator.

A wave power generator comprises a buoyant casing (500) intended to float in a body of water. An electric machine (103) located within the casing has an armature and a field source, the electric machine having a fixed part coupled to the casing and a moving part. A counterweight assembly (104) is movable within the casing, comprising the moving part of the electric machine and wherein a relative movement of the counterweight assembly and the fixed part of the electric machine generates electric power. Power storage (400) stores power generated by the electric machine and a control system (200) determines a bi-directional energy flow between the power storage and the armature, wherein energy is returned to the electric machine to drive a motion of the counterweight assembly anti-symmetrically to a motion of the casing.

A battery storage and/or a wind turbine including the battery storage. A generator for generation of an electric current. An electric flow path configured for conducting the electric current to an electric grid via a power converter, the power converter. The battery storage electrically connected to the electric flow path, the battery storage comprising a plurality of battery cells, each battery cell comprising at least one battery element and at least two semiconductor switches. A controller is configured for selectively controlling the voltage over the battery storage by controlling the status of the at least two semiconductor switches of a plurality of the battery cells, and thereby whether a current path through the battery storage is bypassing the at least one battery element or passing through the at least one battery element of one or more of the plurality of battery cells.

An energy recovery system for machines each having a mechanical power transmission system that generate energy in a first portion of a mechanical power transmission system cycle and draw energy from an energy source in a second portion of the cycle incudes a power distribution assembly configured to receive energy generated during the first portion of the cycle, a plurality of actuator controller devices configured to selectively output energy to a corresponding actuator of each of the plurality of machines, each of the plurality of actuator controller devices electrically coupled to the power distribution assembly and configured to reuse energy received by the power distribution assembly, and, a controller for each of the plurality of actuator controller devices programmed to adjust the output energy of the corresponding actuator controller device to substantially maintain a voltage level of the power distribution assembly relative to a voltage level setpoint.

The present disclosure relates to a method (100) for controlling a wind turbine (10) having a plurality of actuators (364). The method (100) comprises receiving operational data (366) of the wind turbine (10) and determining an operational state of the wind turbine (10). The method (100) comprises using a control model (370) to predict potential operational states depending on operation of the actuators (364) over a finite period of time. The control model (370) comprises an aeroelastic model (371) to determine loads (375) based on operational data (366). The control model (370) further comprises a strength calculation module (372) to calculate secondary load parameters (374) from the loads (375), constraints being defined for the secondary load parameters. The method (100) comprises optimizing a cost function over an optimization period of time, subject to the constraints, to determine an optimum trajectory comprising commands for the actuators (364). Finally, the method (100) comprises using the first commands of the optimum trajectory to control the actuators (364). The disclosure also relates to a controller (360) for a wind turbine (10) configured to implement such method (100).