A hydroelectric power generation system includes a water turbine, a generator connected to the water turbine, and a controller. The water turbine is arranged in a flow path through which a fluid flows. The controller performs a pressure control by controlling the generator to regulate a pressure of the fluid downstream of the water turbine. The pressure control includes a first control regulating the pressure in parallel with a regenerative operation of the generator, and a second control regulating the pressure in parallel with a power running operation of the generator.

A rotor blade for a wind turbine having an aerodynamic profile which extends from a blade root up to a blade tip and has a leading edge and a trailing edge. An adjustable aerodynamic flap, which can be adjusted between a retracted and a deployed position by means of a flap drive, is provided on the rotor blade. The flap drive comprises a passive control system which controls a flap position depending on rotation speed. The passive control system of the flap drive is low-maintenance and does not interfere with the safety concept of a wind turbine. In comparison with a reference rotor blade without a flap, the rotor blade has increased lift at low wind speeds.

A wind turbine and associated control method includes a controller configured with a high speed shaft brake in the generator gear train. The controller receives an input signal corresponding to rotational speed of the high speed shaft, wherein upon the high speed shaft reaching a predefined rotational speed and under a braking condition that calls for the rotor to come to a complete standstill, the controller generates an activate signal to activate the brake. An interlock system is in communication with the low speed shaft sensor and the controller and is configured to override the activate signal when the rotational speed of the low speed shaft is above a threshold value.

A system for generating power includes an environmental engine operating on one or more computing devices that determines a wind flowing over a blade of a wind turbine, wherein the wind flowing over the blade of the wind turbine varies based on environmental conditions and operating parameters of the wind turbine. The system also includes an artificial intelligence (AI) ensemble engine operating on the one or more computing devices that generates a plurality of different models for the wind turbine. Each model characterizes a relationship between at least two of a rotor speed, a blade pitch, the wind flowing over the blade, a wind speed and a turbulence intensity for the wind turbine. The AI ensemble engine selects a model with a highest efficiency metric, and simulates execution of the selected model to determine recommended operating parameters.

Provided is a method for transmitting controlling control variables from a windfarm controller to units including at least one wind power installation or at least one energy store. The method include determining first and second controlling control variable components by the windfarm controller, outputting the first controlling control variable component in a first data packet, outputting the second controlling control variable component in a second data packet, receiving the first and second data packets by a first unit, and determining a controlling control variable from the first and second controlling control variable components. The first data packet has a receiver address which is assigned to the first unit and to at least one further unit, and the second data packet has a receiver address which is assigned to at least the first unit. Provided is a windfarm controller, a wind power installation and a windfarm configured to perform the method.

The invention provides a method of reducing noise emissions of a wind turbine. The method includes receiving data indicative of wind conditions in the vicinity of the wind turbine, and determining an operational set point signal in accordance with a desired operation of the wind turbine, the operational set point signal being determined based on the received data. The method includes applying a perturbation signal to the operational set point signal to obtain a modified operational set point signal, and controlling operation of the wind turbine using the modified operational set point signal to reduce noise emissions of the wind turbine. The perturbation signal is applied such that the modified operational set point signal has greater temporal variation than the operational set point signal.

A system for generating power includes an environmental engine operating on one or more computing devices that determines a Reynolds number for a wind turbine, wherein the Reynolds number characterizes wind flowing over a blade of the wind turbine that varies based on the wind speed, a rotor speed and characteristics of the blade of the wind turbine. The system also includes an artificial intelligence (AI) ensemble engine operating on the one or more computing devices that generates a plurality of different models for the wind turbine. Each model characterizes a relationship between the rotor speed and a blade pitch for the wind turbine, the Reynolds number, wind speed and turbulence intensity for the wind turbine. The AI ensemble engine selects a model with a highest efficiency metric; and simulates execution of the selected model to determine recommended operating parameters.

A method, controller, wind turbine, and computer program product are disclosed for collecting data from wind turbines in a wind farm. An example method generally includes receiving, from a client device, a subscription request identifying a plurality of data points to collect from a set of wind turbines. A wind farm server establishes a client interface with the client device. The wind farm server receives data points form the plurality of wind turbines and buffers the identified collected data points from the set of wind turbines in a data repository. Through the client interface, the wind farm server receives a request for data points collected from at least one wind turbine over a specified time period, and responsive to the request, transmits the requested data points to the client device. The wind farm server also may push collected data points from wind turbines to a data analysis system.

Provided is a trailing edge assembly of a wind turbine rotor blade, which includes a mounting portion; a flap portion flexibly connected to the mounting portion so that a flap angle subtended between the mounting portion and the flap portion can be altered; a volume adjustable chamber arranged between the mounting portion and the flap portion and realised to alter its volume between a minimum volume associated with a minimum flap angle and a maximum volume associated with a maximum flap angle; and at least one tube to face into an airflow passing over the airfoil region of the rotor blade, and an inner orifice arranged to face into the interior of the volume adjustable chamber such that an airflow between the outer orifice and the inner orifice alters the volume of the volume adjustable chamber. Embodiments of the invention further describe a wind turbine rotor blade.

A kinetic energy harvesting mechanism has a fixing shaft, a rotating shell, an input member, and a fixing shaft driving assembly. The rotating shell is disposed on the fixing shaft. The input member is axially connected to the fixing shaft. The fixing shaft driving assembly is disposed in the rotating shell and has a first one-way bearing, a second one-way bearing, a first driving member, a second driving member, and a third driving member. Unidirectional transmission functions of the first one-way bearing and the second one-way bearing are adverse to each other. The first driving member is disposed in the rotating shell by the first one-way bearing. The second driving member is disposed in the rotating shell by the second one-way bearing. The third driving member is disposed in the rotating shell and is connected to the first driving member and the second driving member.