69results about "Active/predictive/anticipative control" 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.

The invention discloses a self-adaptive control method and system for a wind generating set in a low voltage ride through process, and the method comprises the steps: S1, collecting the operation data of the wind generating set in real time, the operation data comprising the rotating speed of a generator and a low voltage ride through process flag bit; s2, judging whether the flag bit in the low-voltage ride-through process is true or not; if so, switching the unit control system from a conventional power generation control mode to a low voltage ride through control mode; otherwise, maintaining the unit in the conventional power generation control mode; in the low-voltage ride-through control mode, transmission chain resistance-increasing self-adaptive control, variable-pitch response self-adaptive control and advanced variable-pitch self-adaptive control are executed in parallel; and S3, according to the final resistance increasing torque, the superposed variable pitch rate and the self-adaptive advanced variable pitch value, comprehensive control over the unit is executed. On the premise that blade clearance and load safety are ensured, unit power fluctuation in the low-voltage ride-through process can be reduced, and unit operation stability and safety are improved.

The invention belongs to the technical field of wind power generation control, and relates to a wind turbine variable pitch control method based on load prediction feedforward compensation, which comprises the following steps: firstly, analyzing the frequency spectrum of a wind speed and a load signal, and distinguishing the current interference as periodic load interference or instantaneous load interference according to discrete peak detection, a cross-power spectrum and an energy ratio; then analyzing the lateral energy ratio and multiband energy distribution of the wind wheel shaft to determine the direction of periodic load interference or the intensity change amplitude of instantaneous load interference; generating a corresponding feed-forward compensation signal; generating a synchronous reverse sine compensation signal for periodic load interference; for the instantaneous load interference, generating a filtering compensation signal in direct proportion to the intensity change amplitude of the instantaneous load interference; and finally, fusing the feedforward signal subjected to amplitude limiting and speed limiting processing with a power feedback signal, and outputting an integrated pitch angle instruction. According to the method, through distinguishing and corresponding compensation of the load types, the active inhibition capability of the variable pitch system on the complex load is improved.

The invention discloses a distributed model prediction control method for an offshore front-end speed regulation type wind turbine generator, and belongs to the technical field of new energy power generation. According to the method, an overall control task is decomposed into three parallel subsystems including a variable pitch subsystem, a hydraulic variable torque speed regulation subsystem and an excitation subsystem, and local discrete prediction models are established respectively. And in each sampling period, rolling optimization of each subsystem is executed in parallel, and future prediction tracks of the rotating speed and the terminal voltage of the generator are introduced as global consistency variables. And by constructing an augmented Lagrangian cost function based on an alternating direction multiplier method and performing iterative solution, driving each local prediction trajectory to converge to a globally consistent optimal trajectory. And finally, outputting a first instruction of an optimal control sequence obtained after iterative convergence to each execution mechanism, and realizing cooperative control of the three subsystems, thereby rapidly and smoothly satisfying frequency and voltage synchronization conditions at the same time before grid connection, effectively inhibiting coupling interference and wind speed fluctuation, and improving grid connection quality and operation reliability.

The invention discloses a control method of an offshore wind power system, and relates to the technical field of offshore wind power generation control, and the offshore wind power system comprises a wind generating set, a converter, a vibration and stress sensor and a controller. According to the invention, the technical problem of how to effectively suppress the key structure load while ensuring the power output is solved. According to the technical scheme, the method is characterized in that a front wind speed sequence is previewed through a cabin type laser radar, and loads of a tower drum and blades are collected in real time; establishing a parameterized state space model, and performing online identification and state estimation on aerodynamic parameters and unmodeled dynamics by adopting an unscented Kalman filter algorithm; in each control period, taking power tracking and load suppression as multiple targets, and based on the updated model and the preview wind speed, solving a finite time domain optimal control problem; and finally, the optimal pitch angle and generator torque increment instruction is analyzed and executed. The method is mainly used for improving the service life and stability of the offshore wind turbine generator.

Wind turbine comprising a tower (2) supporting a nacelle (5) and a rotor (3) having a plurality of rotor blades (4) and an active noise reduction device (7), wherein the active noise reduction device (7) comprises at least one actuator (8), at least one unsteady pressure sensor (9) adapted to generate an output signal corresponding to a turbulent flow condition during operation of the rotor blades (4), at least one noise sensor (10) adapted to generate an output signal corresponding to a noise generated by the rotor blades (4) at the position of the noise sensor (10), wherein the unsteady pressure sensor (9) and the actuator (8) are arranged on at least one of the rotor blades (4) and the noise sensor (10) is arranged at the nacelle (5) and / or at the tower (2), wherein the control unit (11) is adapted to control the actuator (8) depending on the output signals of the unsteady pressure sensor (9) and the noise sensor (10) to emit an anti-noise signal at least partially reducing the noise generated by the rotor blades (4).

A kind of high-power wind turbine control method based on localization PLC, it includes: S1: central data processor reads unit operation history file from unit database, unit operation history file includes the historical failure data of unit and the ten-minute operation data of unit;S2: unit operation history file is split and cleaned, and the data of shutdown is eliminated;S3: from the historical failure data of unit, the occurrence frequency and occurrence time of each unit appearing overspeed, card paddle are counted;S4: according to the occurrence time of unit appearing overspeed, card paddle counted, the operation data of unit before and after corresponding time is inquired from the ten-minute operation data of unit and is carried out variable analysis;S5: central data processor transmits the key variable of each unit and variable operation threshold to the domestic PLC controller of unit, and the domestic PLC controller switches control according to the key variable of each unit and variable operation threshold the variable pitch strategy of unit.

The present disclosure provides a control method, device, and system for a wind turbine set, and a storage medium. The control method comprises: acquiring a preset value of a control parameter and a plurality of historical measurement signals of a wind turbine set in a historical time period; according to the preset value and the plurality of historical measurement signals, determining an estimated distribution parameter of a control signal at a current moment; and determining the control signal at the current moment according to the estimated distribution parameter of the control signal at the current moment.

The application provides a neural network-based yaw control method and device for a wind turbine, and relates to the technical field of wind turbine yaw control. The method comprises the following steps: obtaining state parameters of a target wind turbine; taking the state parameters of the target wind turbine as input, outputting a first predicted yaw angle of the wind turbine through a first yaw angle prediction model, and outputting a second predicted yaw angle of the wind turbine through a second yaw angle prediction model, wherein the first yaw angle prediction model and the second yaw angle prediction model are obtained by training different deep learning algorithms through historical state parameters and corresponding yaw angles of different wind turbines; determining a predicted yaw angle difference between the first predicted yaw angle and the second predicted yaw angle, and determining a target predicted yaw angle of the target wind turbine based on the first predicted yaw angle and the second predicted yaw angle according to the predicted yaw angle difference. The application improves the accuracy of yaw control for the wind turbine, and improves the efficiency and reliability of wind power generation.

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

A system and method are provided for operating a wind farm. Accordingly, a wind direction affecting the wind farm is determined. Based on the wind direction, a controller identifies a turbine cluster, which is a subset of a plurality of wind turbines of the wind farm. The subset includes at least an upwind turbine and a downwind turbine that is affected by a wake emanating from the upwind turbine. With the turbine cluster identified for the given wind direction, the controller then determines a difference between a freestream maximal cluster power output and a wake-affected cluster power output for the turbine cluster. The controller then determines a mitigation setpoint combination for the subset of wind turbines. The mitigation setpoint combination is configured to establish a mitigated cluster power output. Mitigated cluster power output has a difference from the freestream maximal cluster power output that is less than the difference between the freestream maximal cluster power output in the wake-affected cluster power output for the turbine cluster. Based on the mitigation setpoint combination, an operating state of at least one wind turbine of the turbine cluster is changed.

A tension airfoil assembly includes an outer rim located concentrically with a hub supported by a plurality of spokes, each spoke extending therebetween. A series of airfoils, each airfoil having an aerodynamically lifting shape extending between a leading edge and a trailing edge. The tension airfoil assembly can be employed as an electrical power generating system, a propulsion and / or lifting device integrated into a vehicle, such as an airplane, a helicopter, a tandem rotor helicopter, etc. The power generating system can be optimized by applying an electrical load to reduce a rotational rate of the blade assembly. The optimal load can be determined and controlled by a computing system, preferably using Artificial Intelligence, which constantly or periodically monitors the conditions. The load is determined by a stall speed, a wind velocity, and a variation of the wind velocity.

The invention relates to a method for detecting irregular turbine operation using direct and indirect wind speed measurements. The method for operating a wind turbine, the wind turbine comprising a wind characteristic sensor for measuring a wind characteristic and at least one wind turbine state sensor for measuring a state of the wind turbine, the method comprising: determining or adjusting 102 one or more wind characteristic relationships; and performing 104 an operating phase, the operating phase comprising: measuring the wind characteristic with the wind characteristic sensor, thereby obtaining a measured wind characteristic; measuring the state of the wind turbine with the at least one wind turbine state sensor and determining an estimated wind characteristic from the measured state of the wind turbine and a parameter of the wind turbine; comparing the estimated wind characteristic with an expected wind characteristic determined from the measured wind characteristic, wherein the expected wind characteristic is determined based on the one or more wind characteristic relationships; and operating or shutting down the wind turbine based at least partly on the result of the comparison.

The invention relates to a method for determining a spatial position of a portion of an infrastructure element (10), especially a wind energy plant (12). The method comprises obtaining first data (D1) indicative of an operational parameter of the infrastructure element (10) and / or indicative of an environmental parameter of the environment in which the infrastructure element (10) is located. The method further comprises inferring second data (D2) indicative of a position of the portion of the infrastructure element (10) based on the obtained first data (D1) and based on a trained data model (66), wherein the data model (66) is trained to provide a spatial position of the portion of an infrastructure element (10) based on the first data (D1). Moreover, the invention is directed to a method for monitoring the infrastructure element (10), to a method for training the data model (66) as well as to a data processing apparatus (30), a computer program and a computer readable storage medium for executing said methods. Furthermore, a system (28) for monitoring an infrastructure element (10) and an infrastructure element (10) are described.

The invention discloses a wind driven generator control method and system based on dynamic yaw optimization, and relates to the technical field of wind driven generator set control, and the method comprises the steps: carrying out the measurement of the wind speed and the wind direction of a look-ahead measurement point in front of a fan through a laser radar installed on a cabin of a wind driven generator, and obtaining look-ahead wind information, the current yaw angle, the current wind speed, the generator power output and the cabin acceleration of the wind driven generator are obtained in real time, the target yaw angle of the wind driven generator in the prediction time window is predicted based on the look-ahead wind information, the current yaw angle, the current wind speed, the generator power output and the cabin acceleration, and the target yaw angle is calculated according to the target yaw angle. And generating a yaw control instruction, and sending the yaw control instruction to a yaw driving system so as to enable the wind driven generator to perform advanced wind facing control. By means of the mode, the technical problems that in the prior art, due to yaw control response lag, the wind energy capturing efficiency is low, and the unit load is large are solved.

The application discloses a floating wind turbine power control method and device based on wave interval estimation and a medium, relates to the technical field of wind turbine control, and comprises the following steps: acquiring an observation value of a state variable at a current moment and a predicted value of a control input at a previous moment, and determining an estimated value of wave disturbance at the current moment by using an interference interval observer; determining a predicted value of wave disturbance at a next moment based on the estimated values of wave disturbance at the current moment and the previous moment by using a wave disturbance predictor; determining a predicted value of the state variable at the next moment based on the observation value of the state variable at the current moment and the predicted value of wave disturbance at the next moment by using a state predictor, and determining a predicted value of the control input at the current moment by using a time delay controller; and controlling the floating wind turbine at the current moment by using the predicted value of the control input at the current moment. The application realizes accurate compensation and control of wave disturbance.

A controller (10) for a gyroscope structure (2), which is associated with a floating hull (3) and equipped with an electric converter (9) suitable for converting the rotational energy of the floating hull (3) into electrical energy, receives a disturbed output state (x) including the operating variables of the gyroscope structure (2) as input to determine a drive signal (u) for the electric converter (9), the drive signal (u) comprising: a first signal portion (v) determined using a predictive control model of the gyroscope structure (2) calculated based on the disturbed output state (x); and a second signal portion (v * The tube convergence is determined using the parameter deviation (r) of the operated variable of the disturbed output state (x), which is calculated relative to the operated variable of the undisturbed nominal output state (ZNP) of the gyroscope structure (2).

The application discloses a kind of gust control method, device, medium and system of wind generating set, method includes the following steps: 1) obtains the state signal of wind generating set, state signal includes wind speed, wind direction, generator speed, generator acceleration, cabin vibration acceleration, variable pitch speed, generator torque change rate, generator power change rate at least two kinds;2) according to at least two kinds of state information to obtain the correlation coefficient between state information;3) correlation coefficient is compared with preset threshold value;When correlation coefficient is not in preset threshold value, then judge wind generating set is operated in gust mode, and carry out variable pitch action.The application is based on correlation coefficient to detect gust in advance, and the action of pitch angle of actuator is executed by early triggering, reduce the extreme blade load and tower cylinder overturning bending moment of wind generating set under the condition of extreme related gust with wind direction change, guarantee the safety and reliability of wind generating set under the condition of extreme gust.

The application relates to the technical field of fault protection, and discloses a safety control method, system, equipment and medium applied to a wind turbine generator set, which comprises the following steps: setting a monitoring node and performing initialization configuration; the monitoring node collects voltage data of a battery in real time, and uses a sliding time window algorithm to obtain a voltage change trend; the voltage change trend is compared with a preset under-voltage threshold value, and an under-voltage early warning mechanism is triggered according to a comparison result; a main controller combines data of multiple monitoring nodes, judges whether a protection measure is started or not through a voltage prediction model; if a prediction result shows that the voltage will continuously decrease, a hierarchical protection strategy is executed; in a protection mode, a voltage recovery condition is monitored by increasing a sampling frequency, and when the voltage recovers to a safety range and a voltage recovery rate meets a condition, the protection mode is exited. The application significantly improves the stability and safety of a variable pitch system, prolongs the service life of a backup power supply, and provides protection for the safe operation of the wind turbine generator set.

Disclosed is a method, performed by an electronic device, for controlling operation of a wind turbine. The method comprises obtaining wind turbine data associated with the wind turbine. The wind turbine data is indicative of conditions of operation of the wind turbine. The method comprises predicting an Amplitude Modulation, AM, noise parameter indicative of AM noise within a region at a distance from the wind turbine by applying a machine learning model to the wind turbine data. The method comprises generating, based on the AM noise parameter, control data indicative of a control operation of the wind turbine. The method comprises providing the control data to a controller for controlling the wind turbine in accordance with the control data.

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.

This application discloses a wind turbine control method and system based on dynamic yaw optimization, relating to the field of wind turbine control technology. The method includes: measuring wind speed and direction at a forward measurement point in front of the wind turbine using a lidar mounted on the wind turbine nacelle to obtain forward wind information; acquiring the wind turbine's current yaw angle, current wind speed, generator power output, and nacelle acceleration in real time; predicting the target yaw angle of the wind turbine within a prediction time window based on the forward wind information, current yaw angle, current wind speed, generator power output, and nacelle acceleration; generating a yaw control command based on the target yaw angle; and sending the yaw control command to the yaw drive system to enable the wind turbine to control the wind ahead of time. This method solves the technical problems of low wind energy capture efficiency and high turbine load caused by yaw control response lag in existing technologies.

This invention discloses an adaptive control method and system for wind turbine generators during low-voltage ride-through (LVRT). The method includes the following steps: S1, real-time acquisition of wind turbine generator operating data, including generator speed and a LVRT flag; S2, determination of whether the LVRT flag is true; if true, switching the generator control system from conventional power generation control mode to LVRT control mode; otherwise, maintaining the generator in conventional power generation control mode; in LVRT control mode, parallel execution of drivetrain resistance adaptive control, pitch response adaptive control, and advance pitch adaptive control; S3, comprehensive control of the generator based on the final resistance torque, the superimposed pitch rate, and the adaptive advance pitch value. This invention can reduce generator power fluctuations during LVRT while ensuring blade clearance and load safety, thereby improving generator operational stability and safety.

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.

The invention discloses a control method and system for dynamic advanced pitch change of a large-megawatt wind generating set. The method comprises the steps that S1, the wind speed, the wind wheel rotating speed, the generator power and the current pitch angle Pitch of the set in the running process of the wind generating set are obtained; s2, based on the wind speed and the wind wheel rotating speed, the current blade tip speed ratio Lambda of the unit is calculated; calculating a current power coefficient Cp * according to the wind speed, the generator power and the air density; s3, according to the tip speed ratio Lambda and the power coefficient Cp *, an ideal steady-state pitch angle Pitch * is obtained; s4, calculating the deviation E between the current pitch angle Pitch and the ideal steady-state pitch angle Pitch * of the unit, and adjusting an advanced variable pitch value according to the deviation E; wherein the larger the deviation E is, the larger the advance variable pitch value is. The method has the advantages of improving the generating capacity of the unit, improving the safety of the unit and being low in cost.

A method for estimating future risk of failure of a component of an industrial asset. The method includes receiving a plurality of different types of data associated with the industrial asset or a fleet of industrial assets. The plurality of different types of data includes, at least, reliability data (such as time-to-event data). The method also includes generating a failure prediction model for the component based on the reliability data and available time-series measurements. Further, the method includes applying the failure prediction model to the different types of data based on the types of data available in the received data. The applied failure prediction model includes one of a default model, a conditional survival model, or a joint conditional survival model. Thus, the method includes estimating, via the failure prediction model, the future risk of failure of the industrial asset and implementing a control action as needed.

The application discloses a kind of wind farm multi-objective yaw control methods considering power load comprehensive benefits, belong to wind power generation technical field.The wind farm whole tail flow modeling of yaw state is considered by analyzing tail flow model, the inflow data of each wind turbine in wind farm is determined, and the total power and average life of wind farm are quickly and accurately predicted by combining wind turbine power, thrust coefficient curve and S-N curve of transition section pipe node.Single wind turbine power optimization and wind turbine fatigue life optimization with power constraint are integrated to establish a two-stage multi-objective control optimization system, and by building a Bayesian machine learning network, the optimal yaw combination of each stage is located quickly by using efficient and accurate power and life prediction data.The application can accurately and efficiently provide the optimal yaw strategy considering power load comprehensive benefits according to real-time wind speed data, while meeting the power generation demand of wind farm, the load is maximized to extend the service life of wind turbine.

The invention discloses a wind generating set feed-forward control generating capacity increasing method, which relates to the technical field of wind generating set control, and comprises the following steps: carrying out fusion processing on obtained target equipment observation data through an extended Kalman filtering algorithm to obtain a predicted wind speed, and correcting the predicted wind speed; according to the corrected predicted wind speed, generating a propeller pitch correction through a feed-forward mapping function; calculating a dynamic feed-forward control weight according to the predicted wind speed confidence coefficient and the real-time operation state of the target equipment, and combining the dynamic feed-forward control weight with the propeller pitch correction to generate a control instruction; obtaining operation data after the target device executes the control instruction, constructing a target reward function, and dynamically regulating and controlling parameters of the feedforward mapping function through a DDPG algorithm; according to the method, the contradictory problem of generating capacity improvement and load suppression is solved through propeller pitch safety optimization control.

This invention discloses a wind speed estimation method for wind turbine generators under limit control. Addressing the difficulty in estimating wind speed under limit control, this method reveals the essential mapping relationship between pitch angle and wind speed. Based on a polynomial fitting function of this mapping relationship, it effectively estimates the real-time wind speed of wind turbine generators under limit control using the pitch angle value, improving the wind speed estimation capability under multiple operating conditions and ensuring the safe and stable operation of wind turbine generators. Compared with existing methods, this method has the following advantages: (1) simple structure, requiring no additional hardware modifications; (2) strong versatility, applicable to different types of variable-speed, variable-pitch wind turbine generators; (3) high accuracy and small error in wind speed estimation. This method has strong practical engineering value.