56results about "Optimise machine performance" patented technology

A method for optimizing control of a wind turbine includes receiving, via a control system, a condition of the wind turbine. The method also includes estimating a current state of the wind turbine using the condition. The method further includes calculating, via a model implemented by the control system, a linearized representation of operation of the wind turbine for a future time interval after the current state. The method further includes defining an optimization problem to be solved. The method also includes determining a pitch adjustment factor for modifying a current state of the wind turbine. The method further includes calculating, via the optimization solver, an optimized pitch parameter of a rotor blade of the wind turbine. The method also includes adjusting a pitch parameter of the rotor blade to an optimized pitch parameter to improve the control.

A method for optimizing performance of a wind farm having at least one wind turbine includes maneuvering a first unmanned aerial vehicle (UAV) having at least one sensor to a first location near the at least one wind turbine of the wind farm; collecting, via the at least one sensor of the first UAV, data corresponding to one or more wind conditions at the at least one wind turbine; receiving the data corresponding to the one or more wind conditions at the at least one wind turbine via a controller; generating a control action for the at least one wind turbine using the data corresponding to the one or more wind condition at the at least one wind turbine; and implementing, via the controller, the control action.

A method of operating a wind turbine is provided. The wind turbine is operable in plural different operating modes that differ by at least one of lifetime consumption of the wind turbine and energy production by the wind turbine. A sequence of operating modes is determined for a future period of time, wherein an optimization parameter is estimated based on an estimated external parameter. A sequence of operating modes is selected for which the optimization parameter meets an optimization target. The method further includes obtaining a current value for the consumed lifetime of the wind turbine and determining an actual operating mode for the wind turbine for a current point in time under consideration of a deviation between the current value of the consumed lifetime and a consumed lifetime expected for operation in the selected sequence of operating modes. The wind turbine is operated in the determined actual operating mode.

Method for controlling a wind farm, each wind turbine having an operating point adjustable by an actuator: a) a determination by modeling of a region of space approximating the wake of each wind turbine for a misalignment angle (θ) and for a wind speed deficit threshold (δ), b) an identification, from the modeled wakes, of the wind turbines which are in the modeled wake of another wind turbine, then a storage of identification parameters linking each wind turbine to the wind turbine in the modeled wake of which it is, c) a taking into account of the identification parameters stored in step b) to group wind turbines into a plurality of sub-farms, d) a determination of at least one setpoint operating point, for the wind turbines of each sub-farm, by a method of optimizing the power generated by each sub-farm e) an application of said setpoint operating point to the wind turbines.

Disclosed is an apparatus that adapts the rate of its computational work to match the availability of energy harvested from a stochastic energy source; and, with respect to some types of energy harvesting, regulates the rate of energy capture, the rate of energy conversion, and the rate of consumption of stored potential energy, through its alteration, regulation, and / or adjustment, of that same computational work load.

The present invention relates to a power generation system (1), comprising: a hydro-turbine system (3) having an undesirable power output setpoint and a specific safe power output setpoint; an energy storage system (14); a feeder link (6) connected to the energy storage system (14), an electric machine of the hydro-turbine system (3), and the feeder link (6) connected to an AC power network (2); a device for determining a state of charge (19); and a control circuit (18) for controlling the transmission of power between the feeder link (6) and the energy storage system (14), the control circuit (18) being configured to receive a power setpoint Reps and to determine that the received power setpoint Reps belongs to the undesirable power output setpoint, and to generate a power transmission setpoint Epts and an actual power output setpoint Aepos that satisfy the relationship Reps=Epts+Aepos and belong to the safe power output setpoint.

Disclosed is an apparatus that adapts the rate of its computational work to match the availability of energy harvested from a stochastic energy source; and, with respect to some types of energy harvesting, regulates the rate of energy capture, the rate of energy conversion, and the rate of consumption of stored potential energy, through its alteration, regulation, and / or adjustment, of that same computational work load.

A system for controlling cavitation in a turbine of a hydroelectric dam is described. The system comprises at least one inflatable weir positioned at a location between a tailrace portion of the hydroelectric dam and a downstream waterway of the hydroelectric dam; a monitoring system configured for monitoring cavitation in the turbine; and a water level controller configured for communicating with the monitoring system and with the inflatable weir, the water controller controlling inflation or deflation of the inflatable weir, thereby raising or lowering, respectively, water level in the tailrace portion of the hydroelectric dam. Also described is a failsafe system for maintaining a minimal water level in the tailrace portion of the hydroelectric dam in case of abnormal functioning.

Disclosed is an apparatus that adapts the rate of its computational work to match the availability of energy harvested from a stochastic energy source; and, with respect to some types of energy harvesting, regulates the rate of energy capture, the rate of energy conversion, and the rate of consumption of stored potential energy, through its alteration, regulation, and / or adjustment, of that same computational work load.

A marine energy system comprising: a torpedo housing; a wing housing coupled to and separated from the torpedo housing by a shaft; and an energy converter located within the torpedo housing, wherein the wing housing is configured to move through a fluid current to drive the energy converter. The energy converter may comprise a generator configured to produce electrical energy or a pump adapted to move fluid from a depth location to a shallow location. The wing housing may be configured to move in a figure-8 pattern through the fluid current at 4-8 times the speed of the fluid current. A propeller may be coupled to the wing housing and configured to drive the energy converter.

The application discloses a control method based on acceleration guarantee safety and a wind driven generator, and the method comprises the following steps: calculating current turbulence data corresponding to current acceleration data by using a turbulence prediction mapping function, determining that the current turbulence data is in a certain region of a weak turbulence region, a medium turbulence region and a strong turbulence region; and adopting different strategies. The method has no error in space, is more accurate in turbulence data calculation, reduces the steps of waiting for a weather station or a wind measurement tower test and transmitting turbulence data compared with the related art, and improves the efficiency of obtaining turbulence data. Meanwhile, the intensity of turbulence encountered by the wind driven generator is judged based on the turbulence data, and reasonable strategies are made according to the judgment result, so that the safety of the wind driven generator and the power grid downstream of the wind driven generator is guaranteed.

To provide a system and a method for optimizing control of a wind turbine.SOLUTION: The present disclosure relates to a method of optimizing control of a wind turbine comprising receiving, via a control system, a state of the wind turbine. The method also includes estimating a current condition of the wind turbine using the state. The method also includes computing, via a model implemented by the control system, a linearized representation of the operation of the wind turbine for a future time interval following the current condition. The method also includes defining an optimization problem to be solved. The method also includes determining a pitch adjustment factor for modifying a current state of the wind turbine. The method also includes calculating, via an optimization solver, an optimized pitch parameter of a rotor blade of the wind turbine. The method also includes adjusting a pitch parameter of the rotor blade to an optimized pitch parameter to improve control.SELECTED DRAWING: Figure 6

The aim of the invention is to provide a floatable wave energy converter (100) which has a high degree of efficiency and can also be simply and cost-effectively produced and installed. This is achieved by providing a floatable wave energy converter (100) for converting energy from a wave movement of a fluid into electric energy, comprising a rotor unit (10) having a rotor shaft (11) and rotor support surfaces (12) for generating a buoyancy force (71) which is induced by the wave movement and rotates the rotor unit (10), a generator (20) for generating electric energy, the generator (20) being coupled to the rotor shaft (11) of the rotor unit (10) in order to transmit a torque, and a receiving structure (30) for receiving the rotor unit (10) and the generator (20), the wave energy converter (100) having a control element (40), which comprises at least one movable guiding surface (41), for controlling the movement of the wave energy converter (100) in the sea.

Wind-resistant energy harvesting tower including a main column extending vertically from a base, and a plurality of ledges extending laterally outward from main column, each ledge including solar panel for absorbing and converting solar energy into electricity. Tower includes wind turbine positioned between ledges, for converting wind energy into alternate energy. At least one of main column and ledges is rotatable to orient tower to minimize drag when subject to wind loads. A rotor may rotate ledges to a ledge orientation for increasing wind resistance of tower. Main column may include wind resistance geometry to enable rotation of main column about its longitudinal axis when subject to wind loads. Ledges may include first ledge portion having lower wind resistance and second ledge portion having higher wind resistance and longer than first ledge portion, for compelling a rotation of ledge along wind direction when subject to a wind load.

A method of operating a wind turbine (100) is provided, wherein the wind turbine (100) is operable in plural different operating modes (41-46) that differ by at least one of lifetime consumption of the wind turbine and energy production by the wind turbine. A sequence (305; 741-745) of operating modes is determined for a future period of time (301), wherein an optimization parameter (op) is estimated based on an estimated external parameter (ep). A sequence (305) of operating modes is selected for which the optimization parameter meets an optimization target. The method further includes obtaining a current value (705) for the consumed lifetime of the wind turbine (100)and determining an actual operating mode for the wind turbine (100) for a current point in time (702) under consideration of a deviation (720) between the current value (705) of the consumed lifetime and a consumed lifetime expected for operation in the selected sequence (305) of operating modes. The wind turbine (100) is operated in the determined actual operating mode.

A control method and associated system provide for thermal management of cables within a structure of a wind turbine. An airflow is established through the structure, the airflow moving along and around the cables within the structure to remove heat generated in the cables via heat transfer from a core of the cables through a surrounding insulation layer of the cables. Ambient temperature and a volumetric flow rate of the airflow adjacent the cables is measure. Based on the flow rate and the ambient temperature, a threshold current capacity limit for the cables is determined and used as a control factor for increasing power production of the wind turbine within thermal limits of the cables.

A method for controlling a wind farm (i.e. A wind turbine farm), each wind turbine having an operating setpoint adjustable by an actuator, comprises: a) determining, by modeling, a spatial region approximately representing the wake of each wind turbine for a deviation angle () and a wind speed loss threshold (); b) identifying each wind turbine within another wind turbine modeled wake based on the modeled wake, followed by storing identification parameters linking each wind turbine with its wind turbine within the modeled wake; c) clustering the wind turbines into a plurality of sub-farms taking into account the identification parameters stored in step b), d) determining at least one operating setpoint for the wind turbines of each sub-farms by means of a method for optimizing the generation power of each sub-farms, e) applying said operating setpoint to each wind turbine.

The present disclosure is directed to a method for optimizing control of a wind turbine that includes receiving, via a control system, a condition of the wind turbine. The method also includes estimating a current state of the wind turbine using the condition. The method also includes calculating, via a model implemented by the control system, a linearized representation of an operation of the wind turbine for a future time interval following the current state. The method also includes defining an optimization problem to be solved. The method also includes determining a pitch adjustment factor for modifying the current state of the wind turbine. The method also includes calculating, via the optimization solver, an optimized pitch parameter for a rotor blade of the wind turbine. The method also includes adjusting a pitch parameter of the rotor blade to the optimized pitch parameter to improve control.

The invention relates to a Vortex Micro Hydropower Plant (HPP) designed to address irregularities in water supply to turbines, enabling efficient electricity generation from small rivers. The vortex micro HPP comprises a vertical pressure cell with upper conical and lower cylindrical parts, an inlet channel peripherally connected to the upper edge of the pressure cell, and an outlet tube channel connected to the cylindrical part of the pressure cell, a hydro turbine placed in the cylindrical part of the pressure cell, while in the conical part of the pressure cell, the wings are located at equal intervals along the wall, which are rigidly attached to radial joints placed in the wall of the pressure cell, to which the telescopic levers with loads are rigidly connected from the outside of the cell.

A control method (100) for controlling a wind farm comprising a plurality of wind turbines, based on a plurality of estimated wind velocities and a plurality of estimated wind directions of the wind on the wind farm. The method comprises determining (120), for each wind turbine, a respective rotation command by solving an optimization problem. The optimization problem aims at maximizing an objective function, comprising a first component and a second component. The first component is representative of power generated by the wind farm for said set of successive time instants. The second component is representative of the fatigue of each wind turbine of the wind farm, surrogated over the set of successive time instants. Said second component depends on the fatigue induced by mechanical moments of wind forces on each wind turbine, at each time instant.

A control method (100) for controlling a wind farm comprising a plurality of wind turbines, based on an estimated wind velocity and an estimated wind direction of the wind on the wind farm. The method comprises receiving a wind direction and a wind velocity. The method further comprises determining (120) a group of yaw angles sets and evaluating (130), for each yaw angle set, a power generated by the wind farm. The method further comprises generating (150) new yaw angle sets and modifying (160) the value of each yaw angle according to a probability law. The method further comprises adjusting (170). The method further comprises selecting (190), among the adjusted yaw angle sets, the set for which the power generated is the highest, the yaw angles of such selection set being the desired yaw angles, and sending (200), to each wind turbine, the respective desired yaw angle.

The present invention relates to a method for controlling a wind turbine farm, in which a reinforcement learning (RL) method is implemented in a decentralized manner (for each wind turbine), for which the reward (REC) is calculated as a function of a wake propagation time (DEL). Thus, the reward is well representative of the effect of the last action (for example the control of the previous yaw). Figure 2 to be published

A dual wind turbine system is provided. The dual wind turbine system includes two individually rotating turbines mounted vertically on top of each other, each connected to an independent directional scoop for enhanced wind capture. The stacked first and second rotors rotate in opposite directions, maximizing power generation efficiency. The system includes a stabilizer positioned at the top, which aligns the directional scoops and rotors into the wind. The rotors are supported by a central shaft, with the stabilizer and directional scoops pivotally connected at a same point, allowing continuous alignment with wind direction. The first and second rotors are coaxially aligned, wherein the first directional scoop channels wind into the first rotor from one direction and the second directional scoop channels wind into the second rotor from an opposite direction.

The present invention relates to a system and method for controlling a wind turbine. A system and method for controlling wind turbines of a wind farm is provided. Accordingly, a controller determines a performance difference for a wind turbine at a plurality of sampling intervals of a yaw event. The controller determines a trend line for the wind turbine relating the performance difference to a deviation of a wind direction at each of the plurality of sampling intervals from a first yaw angle. A difference between an angle associated with an apex of the trend line and the first yaw angle is utilized by the controller to determine a yaw angle offset. The yaw angle offset is used to adjust a second yaw angle of the wind turbine.

The invention relates to a wave energy generation system for producing electrical energy from the kinetic wave energy of a fluid, comprising a frame through which the fluid flows, with a wave inlet and a wave outlet, and at least a first energy absorption device and a second energy absorption device, which are arranged in a region between the wave inlet and the wave outlet and generate electrical energy when accelerated, wherein the first energy absorption device is connected to the second energy absorption device by means of a first connecting element and / or the first energy absorption device is connected to the frame of the wave energy generation system by means of a second connecting element and / or the second energy absorption device is connected to the frame of the wave energy generation system by means of a third connecting element, such that by means of the first connecting element,of the second connecting element and / or the third connecting element, a predefined range of movement of the second energy absorption device relative to the first energy absorption device and / or of the second energy absorption device and / or of the first energy absorption device relative to the frame is realized.

This invention relates to systems and methods for operating wind turbine power systems during low wind speeds. A method for operating a wind turbine power system supplying active and reactive power to the power grid includes operating the generator of the wind turbine power system up to a first speed limit. The method also includes monitoring the wind speed at the wind turbine power system. When the wind speed drops below a predetermined threshold, the method includes reducing the first speed limit of the generator to a reduced speed limit of the generator. Furthermore, the method includes operating the generator at the reduced speed limit for a period of time during which the wind speed remains below the predetermined threshold to optimize the tip speed ratio of the wind turbine power system during low wind speeds, thereby increasing the power output of the wind turbine power system at low wind speeds.

Method and arrangement for controlling a wind farm. A method of controlling a plurality of wind turbines (3a, 3b, 3c) of a wind farm (1) is described. The method comprises determining an axial induction zone (48) of at least one wind turbine (3a, 3b, 3c) of the wind farm (1), and modifying the axial induction zone (48) by adjusting at least one of the following operational variables in order to control wind farm congestion: a yaw angle (γ) of a blade rotor (11a, 11b, 11c) of the wind turbine (3a, 3b, 3c), a pitch offset angle of at least one blade (11a, 11b, 11c) of the blade rotor (13a, 13b, 13c), a rotor speed of the blade rotor (13a, 13b, 13c).

A method for optimizing operation of a wind farm includes receiving sensor information from one or more measurement systems of respective wind turbines of the wind farm indicative of operation of the respective wind turbines. The method also includes determining, via turbine estimators, estimates of one or more local wind parameters and a turbine state of each of a plurality of wind turbines based on the sensor information. Further, the method includes determining, via a farm estimator, estimates of one or more farm wind parameters based on, at least, the estimates and the turbine states. The method further includes estimating, via the farm estimator, a wind farm resource based on the estimates and determining one or more setpoints for each of the wind turbines based on the wind farm resource. Thus, the method includes controlling, via the plurality of turbine controllers, the plurality of wind turbines based on the setpoint(s).

To provide wind turbine control that maintains efficiency while consuming little to no computing power. [Solution] Each wind turbine has an operating point adjustable by an actuator, a) model a spatial region approximating the wake of each wind turbine with respect to a range of misalignment angles and a predetermined threshold for insufficient wind speed, b) identify wind turbines in the modeled wake of another wind turbine based on the modeled wake, and store identification parameters that associate each wind turbine with the wind turbines in the modeled wake where it is located, c) consider the identification parameters stored in step b) in order to cluster the wind turbines into a plurality of subfarms, d) optimize the power generated by each subfarm by setting at least one operating setpoint for the wind turbines in each subfarm, and e) apply the operating setpoint to the wind turbine.

The present disclosure relates to wind turbine blade assemblies comprising a wind turbine blade and a plurality of aerodynamic add-ons. The aerodynamic add-ons may be asymmetrically arranged on the suction and pressure side of the blade. The aerodynamic addons may include add-ons of a plurality of different types. The present disclosure further relates to computer-implemented methods for determining a configuration of a wind turbine blade assembly including a wind turbine blade and a plurality of aerodynamic add-ons, and to computer programs and data processing systems configured to carry out such methods.