116results about "Active/predictive/anticipative control" patented technology

The invention relates to the field of wind power generation, and discloses a wind power generation control system and method. The data acquisition module is used for acquiring front three-dimensional wind field information detected by the laser radar, near-field wind speed and direction information measured by the ultrasonic sensor, regional wind regime data issued by the meteorological satellite and operation parameters of the wind generating set. According to the invention, through multi-source information fusion, wind regime accurate perception is realized, power generation stability is improved from the source, through multi-source fusion of the laser radar, the ultrasonic sensor and meteorological satellite data, a three-dimensional wind regime perception system is constructed, wind speed and wind direction changes can be predicted in advance, wind regime measurement errors are reduced, and power generation efficiency is improved. The problem of power generation fluctuation caused by wind energy intermittency is solved from the source, and accurate data support is provided for dynamic adjustment of the pitch angle.

The invention discloses a yaw wind error compensation method and system based on wind measurement data, and relates to the technical field of wind power generation equipment control, and the method comprises the steps: setting a wind measurement point position, and collecting an original wind field data set; calculating an incoming flow and a cabin wind direction angle according to the original wind field data set; performing deviation calculation to obtain a yaw wind error angle; triggering a dual-channel compensation module, accumulating errors, constructing an error queue, and performing batch compensation to obtain a compensation result; yawing control parameters are called, the cabin attitude is analyzed according to the compensation result, the yawing control parameters are updated, and self-adaptive compensation of yawing to the wind error is achieved. The technical problems that in the operation process of the wind driven generator, due to wake flow, terrain, turbulent flow and other environmental factors and equipment loss, a traditional yaw system cannot accurately detect the wind direction and compensate the wind alignment error, the power generation efficiency is low, and the potential safety hazard of equipment is large are solved, and the purposes of accurately improving the wind alignment precision of a wind wheel and improving the power generation efficiency are achieved. The power generation efficiency is obviously improved; and the equipment operation safety is enhanced.

The invention discloses a wind power generation system with a self-adaptive compensation function. The wind power generation system comprises a wind power generator, an energy storage device, a self-adaptive compensation controller and a power grid connection module, the self-adaptive compensation controller comprises a real-time monitoring module, a prediction analysis module, a self-adaptive compensation decision module and a control execution module, and the real-time monitoring module obtains operation parameters of the wind power generator and state parameters of the energy storage device; the predictive analysis module predicts and analyzes the wind power change trend and the power grid load demand, the self-adaptive compensation decision module generates control instructions of the wind driven generator and the energy storage device, the control execution module adjusts the operation state of the wind driven generator, and meanwhile the charging and discharging process of the energy storage device is controlled. By monitoring the states of the wind power and the power grid in real time, applying an intelligent algorithm to predict and analyze, and combining with an energy storage technology, self-adaptive compensation of wind power generation fluctuation is realized, the stability and reliability of wind power generation are improved, and adverse effects on the power grid are reduced.

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 relates to the field of efficiency optimization, and discloses a wind turbine generator power generation efficiency optimization method and system based on wind direction and wind speed monitoring, which are used for realizing long-term stable and efficient operation of a wind turbine generator. Comprising the following steps: acquiring an original wind speed and wind direction sequence by using a sensor, generating an enhanced standardized wind speed sequence containing turbulence intensity characteristics and a standardized wind direction sequence containing variable quantity characteristics through calculation, outputting a standardized wind speed and wind direction prediction sequence, and combining turbulence intensity correction to improve prediction precision and practicability. A continuous differentiable energy capture efficiency curved surface is constructed, a yaw angle instruction sequence and a pitch angle instruction sequence are obtained through analysis in the gradient direction of the curved surface, global optimization control is achieved, and instructions can be dynamically adjusted to adapt to wind regime changes. According to the method, the fan wind power efficiency evaluation report can be generated, and the power generation efficiency is optimized according to the fan wind power efficiency evaluation report.

The embodiment of the invention provides a wind turbine generator blade clearance control system and method. The system comprises a strain measurement module which comprises a plurality of optical fiber strain sensors arranged on the inner surface of a wind turbine generator blade at intervals and is used for measuring the strain of the blade; the distance calculation module is used for calculating a predicted distance between the tip of the blade and the tower according to the strain of the blade, the current azimuth angle of the blade, the rotating speed of a wind wheel, the wind speed, the static distance between the tip of the blade and the tower, the length of the blade and the pitch angle of a cabin; the interference judgment module is used for judging whether the blade and the tower drum have interference risks or not according to the predicted distance; and the variable pitch control module is used for carrying out independent variable pitch control adjustment on the pitch angle of the blade when the interference risk exists between the blade and the tower drum. The embodiment of the invention is not influenced by environmental factors, and has the capability of protecting the blades from interference with the tower drum in all-weather operation; the independent variable pitch is used for achieving blade clearance protection control, and the generating capacity loss can be effectively reduced.

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.

According to the variable-pitch control optimization method for the offshore wind turbine generator, flapping matrixes of three blades are converted into d-axis and q-axis signal components under a rotating coordinate system through extended Collmann transformation in combination with a dynamic compensation angle technology, a compensation angle delta is dynamically calculated through a pneumatic unbalance factor (delta a) and a mass unbalance factor (delta m), and the compensation angle delta is calculated through a dynamic balance factor (delta m). And the adaptability of a load unbalance state is obviously improved. And then, a robust controller based on a product perturbation model is adopted to generate a control signal in a dq domain, and the robustness of the system to complex wind conditions (such as turbulence and wind shearing) on the sea is enhanced by minimizing weighted norms of a sensitivity function and a complementary sensitivity function and optimizing parameters by using a DK iterative algorithm. And finally, the control signals are mapped back to the independent control quantity of each blade through anti-Collman transformation, and the blade angle is adjusted in real time by combining a closed-loop P I execution system.

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 method of correcting turbine underperformance includes calculating a power production curve using monitored data, detecting changes between the monitored data and a baseline power production curve, generating operability curves for paired operational variables from the monitored data, detecting changes between the operability curves and corresponding baseline operability curves, comparing the changes to a respective predetermined metric, and if the change exceeds the metric, providing feedback to a turbine control system identifying at least one of the paired operational variables for each paired variable in excess of the metric. A system and a non-transitory computer-readable medium are also disclosed.

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 present invention discloses a method and system for dynamic optimization of a wind farm based on real-time data adaptive regulation, which relates to the technical field of wind farm optimization. The method includes: acquiring wind farm environmental data and wind turbine status data, mapping them to a state space model, and aligning them within the same time step; constructing a wind farm dynamic optimization objective, calculating the uncertainty degree, dynamic importance degree, and target collaborative contribution rate, constructing a fuzzy analytic hierarchy process matrix, solving to obtain the weight of the wind farm dynamic optimization objective, and constructing a dynamic optimization objective function; constructing wind farm constraints, solving the dynamic optimization objective function to generate an optimal control parameter set, inputting it into a safety barrier function for verification, and after passing the verification, performing wind farm dynamic optimization. By constructing a wind farm dynamic optimization objective, power coordination optimization within the entire field is achieved, and wake damage is reduced; by introducing a safety barrier function and a fault tolerance control mechanism, the overall optimization efficiency and reliability of the wind farm are improved.

The present invention discloses a yaw error compensation method and system based on wind measurement data, which relates to the field of wind power generation equipment control technology. The method includes: setting wind measurement points to collect original wind field data sets; calculating the incoming flow and the nacelle wind direction angle based on the original wind field data sets; performing deviation calculation to obtain the yaw error angle; triggering a dual-channel compensation module, accumulating errors to build an error queue and performing batch compensation to obtain compensation results; retrieving yaw control parameters, analyzing the nacelle attitude based on the compensation results, updating the yaw control parameters and realizing adaptive compensation of yaw error. The present invention solves the technical problem that during the operation of a wind turbine, due to environmental factors such as wake, terrain, turbulence, and the loss of the equipment itself, the traditional yaw system is unable to accurately detect wind direction and compensate for wind error, resulting in low power generation efficiency and great equipment safety risks. The present invention achieves the technical effect of accurately improving the wind rotor wind accuracy, significantly improving power generation efficiency, and enhancing equipment operation safety.

The present invention relates to wind turbine model-based control and estimation using accurate online models. A system for calculating estimated operating parameters and / or control commands for a wind turbine includes: a sensor that monitors a wind turbine; a control processor that implements a linearized evaluation to obtain a model of structural component dynamic behavior, fluid component dynamic behavior, and / or combined structural and fluid component dynamic behavior of wind turbine operation; and a module that performs operations using the linearized evaluation of the structural component dynamic behavior, fluid component dynamic behavior, and / or combined structural and fluid component dynamic behavior. The module is at least one of an estimation module and a multivariable control module. The estimation module generates a signal estimate of a turbine or fluid state. The multivariable control module determines an actuator command, the actuator command including a wind turbine command to maintain the operation of the wind turbine to a predetermined setting in real time. A method and a non-transitory medium are also disclosed.

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 "hydraulic rotating machinery" ("HRM") system provides optimal energy efficiency over a very wide conditions of service ("COS") range by configuring a plurality of variable speed HRMs in a "cluster." The HRMs are interconnected by one or more valves that can be actuated by a controller to configure and vary a flow path through which a process fluid flows from an inlet to an outlet. By actively selecting which of the HRMs are included in the flow path, the interconnections therebetween, and the operating speeds thereof, the controller ensures that the HRM cluster continues to operate at optimal efficiency as the COS fluctuates over a very wide range. The HRMs can be identical to each other, or can vary in design. The HRM system can be implemented for storage and retrieval of green energy. The controller can also monitor the health of the cluster and / or of the associated process.

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 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.

To provide a method for controlling a wind turbine having a plurality of actuators.SOLUTION: A method comprises receiving operating data (366) of a wind turbine and determining an operating state of the wind turbine. Further, the method includes an intensity calculation module (372) for calculating secondary load parameters (374) from loads (375). The method comprises optimizing a cost function over a finite optimization time period, subject to constraints, to determine an optimal trajectory (391) including commands for actuators. Finally, the method includes controlling the actuators using the first commands of the determined optimal trajectory. The present disclosure relates to a wind turbine controller (360) configured to implement such a method.SELECTED DRAWING: Figure 5

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.

Wind turbine comprising a tower (2) bearing a nacelle (5) and a rotor (3) with 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 produce an output signal corresponding to a turbulent flow condition during operation of the rotor blade (4), at least one noise sensor (10) adapted to produce an output signal corresponding to a noise generated by the rotor blade (4) at the location of the noise sensor (10), and a control unit (11), 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) in dependence of the output signals of the unsteady pressure sensor (9) and the noise sensor (10) to emit an anti-noise signal at least partly reducing the noise generated by the rotor blade (4).

According to the variable pitch control method of the wind turbine generator, a dynamic decision-making mechanism is constructed by fusing a physical model and an LSTM prediction algorithm, vibration suppression and a safety grading execution strategy are integrated, all-working-condition optimization control of the wind turbine generator is achieved, the load peak value is accurately predicted based on the real-time wind speed, thrust and vibration data, and the control accuracy is improved. A cost function with thrust fluctuation and variable pitch gentle double targets is adopted to optimize a pitch angle sequence, hub axial load fluctuation is reduced, vibration energy is effectively reduced by detecting a tower vibration amplitude dynamic superposition anti-phase compensation angle, the control precision error is reduced, and the power generation efficiency is improved.

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.