Wind turbine generator system and method for adaptive load reduction in complex wind fields

Abstract

The application discloses a wind turbine load adaptive load reduction method and system for complex wind fields, and relates to the technical field of wind turbine control. The method comprises the following steps: acquiring unit operation state data and environment data in real time; estimating equivalent aerodynamic load acting on a wind wheel on line according to wind wheel dynamics relation through a parameter identification algorithm based on the data; calculating generator torque compensation according to the equivalent aerodynamic load and a load reference value, and calculating pitch angle compensation according to the equivalent aerodynamic load and a cut-off frequency; superimposing the two compensation amounts on original control instructions of the wind turbine to generate and execute load reduction instructions. Through the above method, real-time on-line estimation and active feed-forward compensation of random time-varying aerodynamic load are realized, dynamic load fluctuation under complex wind fields can be adaptively reduced, fatigue load of key components can be effectively reduced, and operation safety and service life of the unit are improved.

Description

Technical Field

[0001] This application relates to the field of wind turbine control technology, and in particular to a method and system for adaptive load reduction of wind turbines for complex wind farms. Background Technology

[0002] In the field of wind power generation, complex wind fields are often accompanied by strong turbulence, high shear, and extreme wind conditions, resulting in drastically fluctuating aerodynamic loads acting on wind turbine generators. Existing wind turbine control strategies are mostly based on standardized wind condition designs, employing feedback control principles to respond to structural load changes. This results in significant lag and makes it difficult to effectively suppress random, high-frequency load fluctuations. This not only exacerbates fatigue damage to critical components such as the drivetrain, tower, and blades, affecting the unit's operational lifespan, but also limits the unit's accessibility and power generation efficiency in harsh wind field environments.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this application is to provide a method and system for adaptive load reduction of wind turbine generator sets for complex wind farms, aiming to solve the technical problem of large load fluctuations of wind turbines under complex wind farms in the prior art.

[0005] To achieve the above objectives, this application provides an adaptive load reduction method for wind turbine generators in complex wind farms, the method comprising: Real-time acquisition of wind turbine operating status data and environmental data of the wind farm; Based on the operational status data and the environmental data, the equivalent aerodynamic load acting on the wind turbine is estimated online using a parameter identification algorithm and in accordance with the wind turbine dynamics relationship. The generator torque compensation amount is calculated based on the equivalent aerodynamic load and the load reference value, and the pitch angle compensation amount is calculated based on the equivalent aerodynamic load and the cutoff frequency. The generator torque compensation and the blade pitch angle compensation are superimposed on the original control command of the wind turbine to generate a load reduction execution command, and the load is reduced according to the load reduction execution command.

[0006] In one embodiment, the step of estimating the equivalent aerodynamic load acting on the wind turbine online based on the operating status data and the environmental data, using a parameter identification algorithm and the wind turbine dynamics relationship, includes: Based on the wind speed information in the environmental data, the generator speed in the operating status data is filtered, and the operating status data corresponding to the speed data segment located in the normal operating range of the wind turbine is retained to obtain the filtered operating status data. Extract the generator speed sequence and generator torque sequence from the filtered operating status data; Based on the aforementioned wind turbine dynamics relationship, a wind turbine dynamics equation is established, which relates the wind turbine moment of inertia, the differential value of the generator speed, the measured value of the generator torque, and the equivalent aerodynamic torque acting on the wind turbine. The wind turbine dynamics equations are solved using a parameter identification algorithm based on the generator speed sequence and generator torque sequence to obtain an estimated equivalent aerodynamic torque. The estimated value of the equivalent aerodynamic torque is used as the equivalent aerodynamic load.

[0007] In one embodiment, the step of solving the wind turbine dynamics equations using a parameter identification algorithm on the generator speed sequence and generator torque sequence to obtain an estimated equivalent aerodynamic torque includes: The generator speed differential is calculated based on the generator speed sequence, and the generator speed differential at the current sampling moment is combined with the generator torque measurement value to form an observation scalar according to the generator torque sequence and the wind turbine dynamics equation. The gain coefficient for the current sampling time is calculated based on the covariance matrix estimated from the parameters at the previous sampling time. Based on the gain coefficient, the observed scalar, and the estimated equivalent aerodynamic torque at the previous sampling time, the estimated equivalent aerodynamic torque at the current sampling time is calculated using a recursive least squares update algorithm.

[0008] In one embodiment, the step of calculating the generator torque compensation amount based on the equivalent aerodynamic load and the load reference value includes: The load deviation is calculated based on the equivalent aerodynamic load and the load reference value. The initial torque compensation amount is determined based on the load deviation. The initial torque compensation amount is subjected to rate and amplitude limits to obtain the generator torque compensation amount.

[0009] In one embodiment, the step of applying rate and amplitude limits to the initial torque compensation amount to obtain the generator torque compensation amount includes: The positive and negative amplitude limit thresholds for torque compensation are set according to the instantaneous torque bearing limit value of the wind turbine generator drive chain. The threshold for limiting the rate of change of torque compensation is set based on the dynamic response capability of the wind turbine converter and the vibration suppression requirements of the wind turbine drive train. The initial torque compensation amount is applied to the positive and negative amplitude limit thresholds of the torque compensation amount and the change rate limit threshold of the torque compensation amount to obtain the generator torque compensation amount.

[0010] In one embodiment, the step of calculating the pitch angle compensation amount based on the equivalent aerodynamic load and the cutoff frequency includes: The high-frequency fluctuation component of the load is obtained by separating it from the equivalent aerodynamic load based on the cutoff frequency; Determine the gain coefficient corresponding to the current operating condition of the wind turbine based on the gain scheduling table; The pitch angle compensation amount is obtained based on the high-frequency fluctuation component and the gain coefficient.

[0011] In one embodiment, the step of determining the gain coefficient corresponding to the current operating condition of the wind turbine based on the gain scheduling table includes: Based on the generator speed and generator power in the operating status data, the current operating condition point of the wind turbine is determined; Based on the gain scheduling table, the gain coefficient corresponding to the current operating condition point is obtained by querying.

[0012] In one embodiment, the step of acquiring real-time operating status data of the wind turbine generator and environmental data of the wind farm includes: Real-time acquisition of raw operating status data including generator speed, generator torque, nacelle acceleration, and independent pitch angles of the three blades; Simultaneously collect raw environmental data including wind speed, wind direction, and turbulence intensity; The collected raw operating status data and raw environmental data are time-stamped and validated to remove abnormal data points, thereby obtaining the operating status data of the wind turbine generator and the environmental data of the wind farm.

[0013] In one embodiment, the step of superimposing the generator torque compensation amount and the blade pitch angle compensation amount onto the original control command of the wind turbine to generate a load reduction execution command, and performing load reduction according to the load reduction execution command, includes: The generator torque compensation amount is superimposed on the original generator torque command to generate a generator torque execution command. The pitch angle compensation amount is superimposed on the original pitch angle command to generate a pitch angle execution command. The generator torque execution command and the pitch angle execution command are encoded to generate a load reduction execution command, and the load is reduced according to the load reduction execution command.

[0014] Furthermore, to achieve the above objectives, this application also proposes a wind turbine generator load adaptive unloading system for complex wind farms. The wind turbine generator load adaptive unloading system for complex wind farms includes: The data acquisition module is used to acquire real-time operating status data of the wind turbine generator and environmental data of the wind farm. The online estimation module is used to estimate the equivalent aerodynamic load acting on the wind turbine online based on the operating status data and the environmental data, through a parameter identification algorithm and according to the wind turbine dynamics relationship. The compensation calculation module is used to calculate the generator torque compensation amount based on the equivalent aerodynamic load and the load reference value, and to calculate the pitch angle compensation amount based on the equivalent aerodynamic load and the cutoff frequency. The load reduction module is used to superimpose the generator torque compensation amount and the pitch angle compensation amount onto the original control command of the wind turbine to generate a load reduction execution command, and perform load reduction according to the load reduction execution command.

[0015] In addition, to achieve the above objectives, this application also proposes a wind turbine generator load adaptive load reduction device for complex wind farms. The wind turbine generator load adaptive load reduction device for complex wind farms includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the wind turbine generator load adaptive load reduction method for complex wind farms as described above.

[0016] In addition, to achieve the above objectives, the present invention also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the wind turbine generator load adaptive load reduction method for complex wind farms as described above.

[0017] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the adaptive load reduction method for wind turbine generator sets in complex wind fields as described above.

[0018] This application provides a method for adaptive load reduction of wind turbine generators in complex wind farms. It acquires real-time operating status data and environmental data; based on this data, a parameter identification algorithm estimates the equivalent aerodynamic load acting on the wind turbine online according to the wind turbine dynamics; the generator torque compensation is calculated based on the equivalent aerodynamic load and load reference values, and the pitch angle compensation is calculated based on the equivalent aerodynamic load and cutoff frequency; these two compensations are superimposed on the original control commands of the wind turbine generator to generate and execute load reduction commands. Through this method, real-time online estimation and active feedforward compensation of random time-varying aerodynamic loads are achieved, enabling adaptation to dynamic load fluctuations in complex wind farms, effectively reducing fatigue loads on key components, and improving the operational safety and lifespan of the generator unit. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating an embodiment of the wind turbine generator load adaptive load reduction method for complex wind farms in this application. Figure 2 This is an embodiment of the wind turbine generator load adaptive unloading method for complex wind farms in this application, showing the instantaneous wind speed and wind turbine power-speed curves; Figure 3 This is a schematic diagram of the module structure of the wind turbine generator load adaptive unloading system for complex wind farms according to an embodiment of this application; Figure 4 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the wind turbine generator load adaptive load reduction method for complex wind farms in the embodiments of this application.

[0022] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0024] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0025] The main solution of this application embodiment is: to acquire the operating status data of the wind turbine generator set and the environmental data of the wind farm in real time; Based on the operational status data and the environmental data, the equivalent aerodynamic load acting on the wind turbine is estimated online using a parameter identification algorithm and in accordance with the wind turbine dynamics relationship. The generator torque compensation amount is calculated based on the equivalent aerodynamic load and the load reference value, and the pitch angle compensation amount is calculated based on the equivalent aerodynamic load and the cutoff frequency. The generator torque compensation and the blade pitch angle compensation are superimposed on the original control command of the wind turbine to generate a load reduction execution command, and the load is reduced according to the load reduction execution command.

[0026] Currently, in the field of wind power generation, complex wind fields are often accompanied by strong turbulence, high shear, and extreme wind conditions, resulting in drastically fluctuating aerodynamic loads acting on wind turbine generators. Existing wind turbine control strategies are mostly based on standardized wind condition designs and use feedback control principles to respond to changes in structural loads, exhibiting significant lag and difficulty in effectively suppressing random, high-frequency load fluctuations. This not only exacerbates fatigue damage to critical components such as the drivetrain, tower, and blades, affecting the unit's operational lifespan, but also limits the unit's accessibility and power generation efficiency in harsh wind field environments.

[0027] This application provides a solution that acquires real-time unit operating status data and environmental data; based on the data, a parameter identification algorithm is used to estimate the equivalent aerodynamic load acting on the wind turbine online according to the wind turbine dynamics relationship; the generator torque compensation is calculated based on the equivalent aerodynamic load and load reference value, and the pitch angle compensation is calculated based on the equivalent aerodynamic load and cutoff frequency; the two compensation values ​​are superimposed on the original control command of the wind turbine to generate and execute a load reduction command. Through the above method, this approach achieves real-time online estimation and active feedforward compensation of random time-varying aerodynamic loads, enabling it to adapt to dynamic load fluctuations under complex wind fields, effectively reducing fatigue loads on key components, and improving the operational safety and lifespan of the unit.

[0028] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions, such as a wind turbine generator load adaptive unloading device for complex wind farms. This embodiment does not specifically limit it in this regard. The following uses a wind turbine generator load adaptive unloading device for complex wind farms as an example to describe this embodiment and the following embodiments.

[0029] All actions involving the acquisition of signals, information, or data in this application are carried out in accordance with the relevant data protection laws and policies of the country where the application is located, and with the authorization of the owner of the relevant device.

[0030] This application provides an adaptive load reduction method for wind turbine generators in complex wind farms, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the wind turbine generator load adaptive load reduction method for complex wind farms in this application.

[0031] In this embodiment, the wind turbine generator load adaptive load reduction method for complex wind farms includes steps S10~S40: Step S10: Real-time acquisition of the operating status data of the wind turbine generator set and the environmental data of the wind farm.

[0032] It should be noted that operational status data refers to data reflecting the real-time operating parameters of the wind turbine generator itself, while environmental data refers to real-time external parameter data describing the wind field conditions where the generator is located.

[0033] Understandably, the generator speed, torque and other status signals are read through the unit controller's local area network bus, while information such as wind speed and direction is collected through the weather station installed on the nacelle. All data is time-synchronized and filtered preprocessed by the data acquisition and monitoring system to ensure the accuracy and real-time performance of subsequent estimation and control.

[0034] In one feasible implementation, the step of acquiring the real-time operating status data of the wind turbine generator and the environmental data of the wind farm includes: Real-time acquisition of raw operating status data including generator speed, generator torque, nacelle acceleration, and independent pitch angles of the three blades; Simultaneously collect raw environmental data including wind speed, wind direction, and turbulence intensity; The collected raw operating status data and raw environmental data are time-stamped and validated to remove abnormal data points, thereby obtaining the operating status data of the wind turbine generator and the environmental data of the wind farm.

[0035] It should be noted that generator speed and torque are core parameters reflecting the load and power output of the transmission chain, nacelle acceleration is a key indicator characterizing the intensity of tower front-to-back and left-to-right vibration, independent pitch angle refers to the real-time pitch angle of each of the three wind turbine blades, and wind speed, wind direction and turbulence intensity are basic wind field elements describing the instantaneous characteristics of wind energy resources.

[0036] In practice, data acquisition is accomplished through sensors deployed throughout the unit. For operational status data, the photoelectric encoder on the generator side outputs speed pulse signals, the torque meter measures the drive shaft torque, and the accelerometer installed at the bottom of the nacelle measures vibration. For environmental data, the ultrasonic anemometer located at the top of the nacelle continuously measures the three-dimensional wind speed components, thereby calculating horizontal wind speed, wind direction, and turbulence intensity. All analog or digital signals from the sensors are synchronously sampled via a data acquisition card.

[0037] For timestamp alignment, all channel sampling data are timestamped to millisecond precision based on a unified system clock. Data validity verification employs a strategy combining thresholding and rate of change methods to eliminate outliers that clearly exceed physical limits. A commonly used verification formula can be expressed as:

[0038] in, For valid data, represent The original measured value of a certain parameter (such as rotational speed) at a given time. and These are the preset lower and upper limits of this parameter, used to identify out-of-range anomalies. It is the maximum permissible rate of change threshold for this parameter per unit time, used to identify abrupt changes. This indicates that the data point is invalid and has been removed. These two steps ensure that the data used for subsequent analysis is of high quality in both time and numerical terms.

[0039] Step S20: Based on the operating status data and the environmental data, the equivalent aerodynamic load acting on the wind turbine is estimated online according to the wind turbine dynamics relationship through the parameter identification algorithm.

[0040] It should be noted that parameter identification algorithm is a technique for estimating unknown parameters in a model using measurable input and output data of the system. Wind turbine dynamics relationship refers to the physical equation describing the relationship between the rotational motion of the wind turbine and the aerodynamic torque it is subjected to. Equivalent aerodynamic load refers to combining the distributed aerodynamic pressure acting on the entire wind turbine blade into a concentrated load acting on the center of the hub that can produce the same dynamic effect.

[0041] Understandably, after acquiring high-quality data, a simplified wind turbine rotation dynamics model is established based on the acquired high-quality data. For example, the balance equation between aerodynamic torque and generator torque and speed derivative is used, and online estimation algorithms such as recursive least squares method or Kalman filtering are employed to dynamically identify the aerodynamic torque parameters in the model. These parameters are the estimated values ​​of the equivalent aerodynamic loads.

[0042] In one feasible implementation, the step of estimating the equivalent aerodynamic load acting on the wind turbine online based on the operating status data and the environmental data, using a parameter identification algorithm and the wind turbine dynamics relationship, includes: Based on the wind speed information in the environmental data, the generator speed in the operating status data is filtered, and the operating status data corresponding to the speed data segment located in the normal operating range of the wind turbine is retained to obtain the filtered operating status data. Extract the generator speed sequence and generator torque sequence from the filtered operating status data; Based on the aforementioned wind turbine dynamics relationship, a wind turbine dynamics equation is established, which relates the wind turbine moment of inertia, the differential value of the generator speed, the measured value of the generator torque, and the equivalent aerodynamic torque acting on the wind turbine. The wind turbine dynamics equations are solved using a parameter identification algorithm based on the generator speed sequence and generator torque sequence to obtain an estimated equivalent aerodynamic torque. The estimated value of the equivalent aerodynamic torque is used as the equivalent aerodynamic load.

[0043] It should be noted that the normal operating range of a wind turbine refers to the stable power generation area where the wind turbine generator set maintains the optimal wind energy utilization coefficient below the rated wind speed. The differential value of the generator speed is the angular acceleration obtained by numerically differentiating the speed sequence. The equivalent aerodynamic torque is the driving torque that acts on the wind turbine's rotation axis and is converted from wind energy.

[0044] In the specific implementation, refer to Figure 2 , Figure 2 The instantaneous wind speed and turbine power-speed curves are used. Based on the measured instantaneous wind speed and turbine power-speed curves, a corresponding optimal speed range is set, and data segments where the generator speed falls within this range are selected. This ensures that the data used for identification originates from the turbine's stable power generation condition. Subsequently, time-synchronized generator speed sequences are extracted from these selected data. and generator torque sequence .

[0045] The established wind turbine dynamics equations are based on Newton's second law for rotating systems, and their expression is:

[0046] in, It is the equivalent moment of inertia of the entire transmission chain referred to the wind turbine side, and is a known system parameter. It is the angular acceleration of the wind turbine. Since the gearbox transmission ratio is fixed, it is related to the angular acceleration of the generator. The proportional relationship can be derived from the generator speed sequence through numerical differentiation (such as the central difference method). The estimate was obtained. The equivalent aerodynamic torque to be determined is... It is the measured generator torque.

[0047] When solving this equation, it is rearranged into the standard form for parameter identification. .in, , Parameters to be identified That is, equivalent aerodynamic torque The equation is solved using online algorithms such as the recursive least squares method. The equivalent aerodynamic torque is output in real time through recursive calculation of the sequence data. The optimal estimate is the equivalent aerodynamic load used for load characterization.

[0048] In one feasible implementation, the step of solving the wind turbine dynamics equations using a parameter identification algorithm on the generator speed sequence and generator torque sequence to obtain an estimated equivalent aerodynamic torque includes: The generator speed differential is calculated based on the generator speed sequence, and the generator speed differential at the current sampling moment is combined with the generator torque measurement value to form an observation scalar according to the generator torque sequence and the wind turbine dynamics equation. The gain coefficient for the current sampling time is calculated based on the covariance matrix estimated from the parameters at the previous sampling time. Based on the gain coefficient, the observed scalar, and the estimated equivalent aerodynamic torque at the previous sampling time, the estimated equivalent aerodynamic torque at the current sampling time is calculated using a recursive least squares update algorithm.

[0049] It should be noted that the observed scalar refers to the auxiliary computational quantity composed of known measurements that has a linear relationship with the parameter to be estimated. The gain coefficient is a weighting factor used in the parameter identification algorithm to weigh the reliability of new measurement data and historical estimates. The recursive least squares update algorithm is a mathematical method that updates the parameter estimate and its error covariance online recursively without storing all historical data.

[0050] In practical implementation, firstly, the wind turbine dynamics equations are... Rewritten in standard identification model form. The parameter to be estimated is defined as the equivalent aerodynamic torque. The system outputs the observed scalar. System regression quantity .in, Indicates the current sampling time. This is achieved by numerically differentiating the generator speed sequence (e.g., using the central difference method). The calculated angular acceleration, This is the current generator torque measurement value. It is the sampling period.

[0051] Gain coefficient And parameter estimation covariance matrix The update of is the core of the algorithm. Its update formula is:

[0052]

[0053] in, It is the estimation error covariance matrix of the previous moment (initial values ​​need to be set), and it is a scalar. It is the forgetting factor (usually a value slightly less than 1, such as 0.99 to 0.999), which gives new data greater weight, enabling the algorithm to track time-varying parameters. It is the identity matrix, which is globally set to 1 in this application.

[0054] Finally, based on the gain coefficients calculated above, the estimated equivalent aerodynamic torque at the current moment is updated:

[0055] in, These are the parameter estimates from the previous moment (initial values ​​need to be set). Known as innovation or prediction error, it reflects the difference between current observations and predictions based on historical estimates. Gain coefficient This determines the magnitude of the correction that the new information makes to the current estimate. The new information refers to the difference between the current observation and the best prediction made based on historical parameter estimates.

[0056] Step S30: Calculate the generator torque compensation amount based on the equivalent aerodynamic load and the load reference value, and calculate the pitch angle compensation amount based on the equivalent aerodynamic load and the cutoff frequency.

[0057] It should be noted that the load reference value is the target load level of the transmission chain set for the generator torque control circuit. The generator torque compensation amount is the dynamic adjustment amount of the generator torque reference command to make the actual transmission chain load track the reference value. The pitch angle compensation amount is the dynamic adjustment amount of the pitch angle reference command to limit excessive wind turbine aerodynamic load. The cutoff frequency is a characteristic parameter of the low-pass filter, used to extract the slow-varying components below a specific frequency from the equivalent aerodynamic load signal.

[0058] Understandably, in practical applications, two independent compensators can be designed: a torque compensator compares the estimated equivalent aerodynamic load with the load reference value, and the deviation is used to generate a torque compensation amount through a proportional-integral controller, which is then superimposed on the generator torque command to achieve active damping control of the transmission chain load; the pitch angle compensator passes the estimated equivalent aerodynamic load through a low-pass filter to filter out high-frequency fluctuations and obtain its quasi-steady-state component, which is then used to generate a pitch angle compensation amount through a proportional controller and superimposed on the pitch angle command to smooth power output and reduce structural load when the wind speed is higher than the rated value.

[0059] In one feasible implementation, the step of calculating the generator torque compensation amount based on the equivalent aerodynamic load and the load reference value includes: The load deviation is calculated based on the equivalent aerodynamic load and the load reference value. The initial torque compensation amount is determined based on the load deviation. The initial torque compensation amount is subjected to rate and amplitude limits to obtain the generator torque compensation amount.

[0060] It should be noted that load deviation refers to the difference between the actual estimated value of the equivalent aerodynamic load and the preset load reference value. The initial torque compensation amount is the original compensation value calculated by the control algorithm based on this load deviation. The rate limit and amplitude limit are constraints imposed on the rate of change and maximum / minimum value of the control command to protect the fan drive system.

[0061] In the actual implementation, the load deviation is first calculated using a simple subtraction operation. The load reference value is set as follows: The currently estimated equivalent aerodynamic torque is Then the load deviation The calculation formula is:

[0062] in, This is the load deviation. Subsequently, this deviation signal is fed into a controller (usually a PI controller) to generate an initial torque compensation. The calculation formula is as follows:

[0063] in, It is a proportional gain, used for rapid response to load deviation; It is the integral gain, used to eliminate steady-state error; It is the sampling period of the controller; This is the current sampling time. The proportional term provides immediate compensation, while the integral term accumulates historical deviations for precise adjustment.

[0064] Finally, to ensure the safe operation of the wind turbine and prevent sudden or excessive torque commands from impacting the generator and frequency converter, the initial compensation amount needs to be limited. The rate limit constrains the variation between adjacent sampling cycles to not exceed a set threshold. The amplitude limit constrains its final value to the upper and lower limits. Within this range. After these two limitations, a safe and smooth generator torque compensation is achieved. .

[0065] In one feasible implementation, the step of applying rate and amplitude limits to the initial torque compensation amount to obtain the generator torque compensation amount includes: The positive and negative amplitude limit thresholds for torque compensation are set according to the instantaneous torque bearing limit value of the wind turbine generator drive chain. The threshold for limiting the rate of change of torque compensation is set based on the dynamic response capability of the wind turbine converter and the vibration suppression requirements of the wind turbine drive train. The initial torque compensation amount is applied to the positive and negative amplitude limit thresholds of the torque compensation amount and the change rate limit threshold of the torque compensation amount to obtain the generator torque compensation amount.

[0066] It should be noted that the instantaneous torque withstand limit refers to the maximum and minimum torque boundaries that each component in the wind turbine generator drivetrain (such as the main shaft, gearbox, coupling, etc.) can safely withstand in a short period of time. The converter's dynamic response capability refers to the maximum rate of change of the converter that can accurately track the torque command. Vibration suppression requirements refer to the smoothness requirements of the torque change rate to avoid exciting the natural frequency of the drivetrain. The positive and negative amplitude limit thresholds are the upper and lower limits of the compensation amount set based on the instantaneous torque withstand limit. The rate of change limit threshold is the maximum change of the compensation amount per unit time set by combining the converter's dynamic response capability and vibration suppression requirements.

[0067] In the specific implementation, the amplitude limit threshold is first set. Let the maximum instantaneous torque that the transmission chain can withstand be... The rated torque of the generator is The positive amplitude limit threshold for torque compensation is... Usually set to Negative amplitude limit threshold Usually set to (That is, minimum compensation to zero torque). Among them, Determined by the mechanical design strength of the transmission chain, It is the steady-state torque of the generator at its rated power.

[0068] Then set a threshold for the rate of change. This threshold... (Unit: N·m / s) Two factors need to be considered simultaneously: first, the torque step response time or maximum slope achievable by the converter; and second, the frequency cutoff characteristics required to avoid the main natural frequencies of the excitation drive train (such as 1P, 2P, 3P frequencies). Its settings must meet the following requirements: ,in These are vibration frequencies that need to be avoided. This is the allowable torque fluctuation amplitude.

[0069] Finally, the initial torque compensation amount Rate limiting and amplitude limiting are performed sequentially. The discretized calculation formula for rate limiting is:

[0070] in, It is the value after the rate limit was applied at the previous moment. This is the control cycle. This formula ensures that the change in the output value of the current cycle relative to the value at the previous moment does not exceed [a certain threshold]. .

[0071] Next, amplitude limiting is applied, calculated using the following formula:

[0072] in, This is the final output generator torque compensation. This formula further constrains the value after the rate limit to... Within the specified range, ensure that the compensation command is within the safe tolerance range of the transmission chain.

[0073] In one feasible implementation, the step of calculating the pitch angle compensation amount based on the equivalent aerodynamic load and the cutoff frequency includes: The high-frequency fluctuation component of the load is obtained by separating it from the equivalent aerodynamic load based on the cutoff frequency; Determine the gain coefficient corresponding to the current operating condition of the wind turbine based on the gain scheduling table; The pitch angle compensation amount is obtained based on the high-frequency fluctuation component and the gain coefficient.

[0074] It should be noted that the high-frequency fluctuation component refers to the rapidly changing part of the equivalent aerodynamic load, which is usually caused by wind speed turbulence or periodic disturbances in the rotation of the wind turbine. The gain scheduling table is a control parameter configuration table, the contents of which are preset according to the main operating conditions of the wind turbine (such as different pitch angles or generator speeds). The gain coefficient is a scaling factor used to convert physical quantities into pitch angle commands, which is obtained from this table. The current operating condition of the wind turbine refers to the real-time working state of the unit determined by key parameters such as generator speed, output power, or pitch angle.

[0075] In practical implementation, a high-frequency fluctuation component is extracted from the equivalent aerodynamic load signal using a high-pass filter or a band-stop filter. A first-order high-pass filter is typically used, and its recursive calculation formula in the discrete domain is as follows:

[0076] in, It is the equivalent aerodynamic load at the current moment. It is the high-frequency fluctuation component output at the current moment. These are filter coefficients, determined by the cutoff frequency. and sampling period The decision is made, and the calculation formula is as follows: This filter allows frequencies higher than [previous frequencies]. The signal components pass through, thereby separating high-frequency fluctuations.

[0077] Subsequently, the gain coefficient is determined by querying the gain dispatch table based on the current unit operating conditions. The gain factor is usually the pitch angle. or generator speed The function, i.e. or For example, the optimal gain can be pre-tuned at different pitch angles through simulation or experimentation, and a lookup table can be constructed. The control system can then obtain the current gain based on the real-time measured pitch angle through linear interpolation. This scheduling mechanism is designed to adapt to the nonlinear changes in the aerodynamic characteristics of the wind turbine under different angles of attack.

[0078] Finally, pitch angle compensation The calculation formula is obtained by multiplying the high-frequency fluctuation component by the gain coefficient:

[0079] in, It is the gain coefficient under the current operating conditions. It is the high-frequency load fluctuation component obtained after filtering. This compensation amount will be directly superimposed on the pitch angle reference command, and the high-frequency torsional vibration of the transmission chain will be suppressed by actively adjusting the blade angle.

[0080] In one feasible implementation, the step of determining the gain coefficient corresponding to the current operating condition of the wind turbine based on the gain scheduling table includes: Based on the generator speed and generator power in the operating status data, the current operating condition point of the wind turbine is determined; Based on the gain scheduling table, the gain coefficient corresponding to the current operating condition point is obtained by querying.

[0081] It should be noted that operating status data refers to the set of physical quantities that the wind turbine control system monitors and collects in real time, reflecting the current operating status of the unit. These mainly include generator speed, generator power, and pitch angle. The current operating condition point is a working state that represents a specific load and performance, jointly determined by the two key parameters of generator speed and generator power on the wind turbine operating characteristic curve. The gain scheduling table is a pre-set two-dimensional or multi-dimensional data table that establishes the mapping relationship between different operating conditions and the optimal control gain coefficient.

[0082] In practical implementation, determining the current operating condition point typically involves determining the generator speed. and generator power Standardization or regional division is performed. A common method is to calculate the equivalent speed. This value integrates speed and power information, providing a more accurate characterization of aerodynamic properties. Its calculation formula is as follows: ,when >0.

[0083] in, It is the actual measured generator speed. This is the actual measured generator power. This is the rated power of the fan. Parameters This eliminates the influence of power variations on operating condition judgment, making the operating point primarily related to speed, which facilitates table lookup. Another, simpler method is to directly use... The operating point is defined using two-dimensional coordinates.

[0084] Subsequently, the gain coefficient is queried based on the gain scheduling table. The gain scheduling table is essentially a two-dimensional lookup table, where the row and column indices correspond to discretized generator speed and power values, respectively. The lookup process employs a bilinear interpolation algorithm to improve accuracy. Let the current measured value be... Find the four grid points enclosed in the table. and their corresponding gain values The interpolation formula is:

[0085] in, It is the normalized interpolation factor in the direction of rotational speed. It is the normalized interpolation factor in the power direction, where, This represents the discretized power value corresponding to the j-th column. This represents the discretized generator speed value corresponding to the i-th row. Through this calculation, a gain coefficient that precisely matches the current operating conditions can be smoothly obtained.

[0086] Step S40: The generator torque compensation amount and the blade pitch angle compensation amount are superimposed on the original control command of the wind turbine to generate a load reduction execution command, and the load is reduced according to the load reduction execution command.

[0087] It should be noted that the original control command refers to the generator torque command and pitch angle command calculated by the wind turbine main controller according to the standard power tracking or constant power operation strategy, without considering the active load reduction requirement. The generator torque compensation is the torque increment calculated by load observation and torque control loop to suppress transmission chain vibration. The pitch angle compensation is the pitch angle increment calculated by aerodynamic load separation and pitch control loop to suppress blade and tower vibration at specific frequencies. The load reduction execution command is the control signal obtained by superimposing the compensation amount onto the original command and finally sending it to the converter actuator and pitch actuator.

[0088] It is understandable that, in each control cycle, the calculated generator torque compensation amount will be... The original generator torque command output by the main control Algebraic addition yields the load reduction torque command. At the same time, the pitch angle compensation amount Compared with the raw pitch angle command output by the main control Algebraic addition yields the load reduction pitch angle command. These two load reduction commands are then sent to the converter and the pitch system, respectively. By rapidly adjusting the electromagnetic torque of the generator and the pitch angle of the blades, the fluctuations of external aerodynamic loads are offset in real time, thereby effectively suppressing the dynamic loads on key components.

[0089] In one feasible implementation, the step of superimposing the generator torque compensation amount and the blade pitch angle compensation amount onto the original control command of the wind turbine to generate a load reduction execution command, and performing load reduction according to the load reduction execution command, includes: The generator torque compensation amount is superimposed on the original generator torque command to generate a generator torque execution command. The pitch angle compensation amount is superimposed on the original pitch angle command to generate a pitch angle execution command. The generator torque execution command and the pitch angle execution command are encoded to generate a load reduction execution command, and the load is reduced according to the load reduction execution command.

[0090] In the actual implementation, instruction superposition is accomplished through simple algebraic operations. For the torque loop, the generator torque execution instruction is generated. The formula is:

[0091] in, The original generator torque command is the reference torque required to maintain the wind turbine at the target speed or power. The generator torque compensation is a dynamic torque correction value estimated by an observer and calculated by a control law to counteract torsional vibration in the drive train. Similarly, for the pitch circuit, the pitch angle execution command is generated. The formula is:

[0092] In this formula, Represents the original pitch angle command, typically used for steady-state control of power or speed; The pitch angle compensation is a dynamic pitch angle correction value obtained by extracting high-frequency components from the equivalent aerodynamic load and adjusting the gain. It is used to suppress tower front-to-back vibration or blade sway.

[0093] Subsequently, instruction encoding is required to ensure reliable signal transmission and execution. The encoding process typically includes range normalization, data type conversion, and protocol encapsulation. For example, consecutive floating-point instructions are first encoded... and Normalization to a specific range (such as the digital quantity corresponding to 0-100% or 4-20mA) can be achieved using the following formula:

[0094]

[0095] in, and These are the lower and upper limits allowed for torque commands. and These are the lower and upper limits allowed for the pitch angle command. The target signal range is specified (e.g., 100 or 16). These normalized values ​​are then converted into digital signals conforming to fieldbus protocols (e.g., CANopen, Profinet) or analog standards, and packaged into a load reduction execution command frame. This command frame is sent to the converter and pitch servo drive via a communication network, driving the actuators to actively suppress mechanical loads.

[0096] This embodiment provides a method for adaptive load reduction of wind turbine generators in complex wind farms. It acquires real-time operating status data and environmental data; based on this data, a parameter identification algorithm estimates the equivalent aerodynamic load acting on the wind turbine online according to the wind turbine dynamics; the generator torque compensation is calculated based on the equivalent aerodynamic load and load reference values, and the pitch angle compensation is calculated based on the equivalent aerodynamic load and cutoff frequency; these two compensations are superimposed on the original control commands of the wind turbine generator to generate and execute load reduction commands. Through this method, real-time online estimation and active feedforward compensation of random time-varying aerodynamic loads are achieved, enabling adaptation to dynamic load fluctuations in complex wind farms, effectively reducing fatigue loads on key components, and improving the operational safety and lifespan of the generator unit.

[0097] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the adaptive load reduction method for wind turbine generators in complex wind farms. Any simple modifications based on this technical concept are within the scope of protection of this application.

[0098] This application also provides a wind turbine generator load adaptive unloading system for complex wind farms; please refer to [reference needed]. Figure 3 The wind turbine generator load adaptive unloading system for complex wind farms includes: Data acquisition module 10 is used to acquire real-time operating status data of wind turbine generators and environmental data of the wind farm where they are located; The online estimation module 20 is used to estimate the equivalent aerodynamic load acting on the wind turbine online based on the operating status data and the environmental data, through a parameter identification algorithm and according to the wind turbine dynamics relationship. The compensation calculation module 30 is used to calculate the generator torque compensation amount based on the equivalent aerodynamic load and the load reference value, and to calculate the pitch angle compensation amount based on the equivalent aerodynamic load and the cutoff frequency. The load reduction module 40 is used to superimpose the generator torque compensation amount and the pitch angle compensation amount onto the original control command of the wind turbine to generate a load reduction execution command, and perform load reduction according to the load reduction execution command.

[0099] In one feasible implementation, the online estimation module 20 is further configured to filter the generator speed in the operating status data based on the wind speed information in the environmental data, retain the operating status data corresponding to the speed data segment located in the normal operating range of the wind turbine, and obtain the filtered operating status data. Extract the generator speed sequence and generator torque sequence from the filtered operating status data; Based on the aforementioned wind turbine dynamics relationship, a wind turbine dynamics equation is established, which relates the wind turbine moment of inertia, the differential value of the generator speed, the measured value of the generator torque, and the equivalent aerodynamic torque acting on the wind turbine. The wind turbine dynamics equations are solved using a parameter identification algorithm based on the generator speed sequence and generator torque sequence to obtain an estimated equivalent aerodynamic torque. The estimated value of the equivalent aerodynamic torque is used as the equivalent aerodynamic load.

[0100] In one feasible implementation, the online estimation module 20 is further configured to calculate the generator speed differential based on the generator speed sequence, and combine the generator speed differential at the current sampling moment with the generator torque measurement value into an observation scalar according to the generator torque sequence and the wind turbine dynamics equation; The gain coefficient for the current sampling time is calculated based on the covariance matrix estimated from the parameters at the previous sampling time. Based on the gain coefficient, the observed scalar, and the estimated equivalent aerodynamic torque at the previous sampling time, the estimated equivalent aerodynamic torque at the current sampling time is calculated using a recursive least squares update algorithm.

[0101] In one feasible implementation, the compensation calculation module 30 is further configured to calculate the load deviation based on the equivalent aerodynamic load and the load reference value; The initial torque compensation amount is determined based on the load deviation. The initial torque compensation amount is subjected to rate and amplitude limits to obtain the generator torque compensation amount.

[0102] In one feasible implementation, the compensation calculation module 30 is further configured to set positive and negative amplitude limit thresholds for torque compensation based on the instantaneous torque bearing limit value of the wind turbine generator drive train. The threshold for limiting the rate of change of torque compensation is set based on the dynamic response capability of the wind turbine converter and the vibration suppression requirements of the wind turbine drive train. The initial torque compensation amount is applied to the positive and negative amplitude limit thresholds of the torque compensation amount and the change rate limit threshold of the torque compensation amount to obtain the generator torque compensation amount.

[0103] In one feasible implementation, the compensation calculation module 30 is further configured to separate the high-frequency fluctuation component of the load from the equivalent aerodynamic load based on the cutoff frequency. Determine the gain coefficient corresponding to the current operating condition of the wind turbine based on the gain scheduling table; The pitch angle compensation amount is obtained based on the high-frequency fluctuation component and the gain coefficient.

[0104] In one feasible implementation, the compensation calculation module 30 is further configured to determine the current operating condition point of the wind turbine based on the generator speed and generator power in the operating status data. Based on the gain scheduling table, the gain coefficient corresponding to the current operating condition point is obtained by querying.

[0105] In one feasible implementation, the data acquisition module 10 is also used to acquire raw operating status data in real time, including generator speed, generator torque, nacelle acceleration, and independent pitch angles of the three blades. Simultaneously collect raw environmental data including wind speed, wind direction, and turbulence intensity; The collected raw operating status data and raw environmental data are time-stamped and validated to remove abnormal data points, thereby obtaining the operating status data of the wind turbine generator and the environmental data of the wind farm.

[0106] In one feasible implementation, the load reduction module 40 is further configured to superimpose the generator torque compensation amount onto the original generator torque command to generate a generator torque execution command. The pitch angle compensation amount is superimposed on the original pitch angle command to generate a pitch angle execution command. The generator torque execution command and the pitch angle execution command are encoded to generate a load reduction execution command, and the load is reduced according to the load reduction execution command.

[0107] The wind turbine load adaptive load reduction system for complex wind farms provided in this application adopts the wind turbine load adaptive load reduction method for complex wind farms in the above embodiments, which can solve the technical problem of large load fluctuations in wind turbines under complex wind farms. Compared with the prior art, the beneficial effects of the wind turbine load adaptive load reduction system for complex wind farms provided in this application are the same as the beneficial effects of the wind turbine load adaptive load reduction method for complex wind farms provided in the above embodiments, and other technical features of the wind turbine load adaptive load reduction system for complex wind farms are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0108] This application provides a wind turbine generator load adaptive load reduction device for complex wind farms. The wind turbine generator load adaptive load reduction device for complex wind farms includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the wind turbine generator load adaptive load reduction method for complex wind farms in the above embodiment 1.

[0109] The following is for reference. Figure 4 This document illustrates a structural schematic diagram of a wind turbine generator load adaptive unloading device suitable for implementing embodiments of this application for complex wind farms. The wind turbine generator load adaptive unloading device for complex wind farms in embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle terminals (e.g., vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The wind turbine load adaptive unloading device shown for complex wind farms is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0110] like Figure 4As shown, the wind turbine load adaptive descent device for complex wind farms may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the wind turbine load adaptive descent device for complex wind farms. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, LCDs (Liquid Crystal Displays), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the wind turbine load adaptive descent device for complex wind farms to exchange data with other devices wirelessly or via wired communication. Although the figure shows a wind turbine load adaptive descent device for complex wind farms with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0111] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0112] The wind turbine load adaptive unloading device for complex wind farms provided in this application adopts the wind turbine load adaptive unloading method for complex wind farms in the above embodiments, and can solve the technical problem of wind turbine load adaptive unloading for complex wind farms. Compared with the prior art, the beneficial effects of the wind turbine load adaptive unloading device for complex wind farms provided in this application are the same as the beneficial effects of the wind turbine load adaptive unloading method for complex wind farms provided in the above embodiments, and other technical features in the wind turbine load adaptive unloading device for complex wind farms are the same as the features disclosed in the previous embodiment method, and will not be repeated here.

[0113] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0114] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0115] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the wind turbine generator load adaptive load reduction method for complex wind farms in the above embodiments.

[0116] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory or Flash Memory), optical fibers, CD-ROM (CD-Read Only Memory), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0117] The aforementioned computer-readable storage medium may be included in a wind turbine generator load adaptive unloading device for complex wind farms; or it may exist independently and not be assembled into a wind turbine generator load adaptive unloading device for complex wind farms.

[0118] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the wind turbine generator load adaptive unloading device for complex wind farms, enable the wind turbine generator load adaptive unloading device for complex wind farms to: acquire real-time operating status data of the wind turbine generator and environmental data of the wind farm. Based on the operational status data and the environmental data, the equivalent aerodynamic load acting on the wind turbine is estimated online using a parameter identification algorithm and in accordance with the wind turbine dynamics relationship. The generator torque compensation amount is calculated based on the equivalent aerodynamic load and the load reference value, and the pitch angle compensation amount is calculated based on the equivalent aerodynamic load and the cutoff frequency. The generator torque compensation and the blade pitch angle compensation are superimposed on the original control command of the wind turbine to generate a load reduction execution command, and the load is reduced according to the load reduction execution command.

[0119] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including LAN (Local Area Network) or WAN (Wide Area Network)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0120] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0121] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0122] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described adaptive load reduction method for wind turbine generators in complex wind farms. This method can solve the technical problem of adaptive load reduction for wind turbine generators in complex wind farms. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the adaptive load reduction method for wind turbine generators in complex wind farms provided in the above embodiments, and will not be repeated here.

[0123] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for adaptive load reduction of wind turbine generator sets for complex wind farms.

[0124] The computer program product provided in this application can solve the technical problem of large load fluctuations in wind turbines under complex wind farm conditions. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the adaptive load reduction method for wind turbine generators in complex wind farms provided in the above embodiments, and will not be repeated here.

[0125] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for adaptive load reduction of wind turbine generator sets for complex wind farms, characterized in that, The adaptive load reduction method for wind turbine generators in complex wind farms includes: Real-time acquisition of wind turbine operating status data and environmental data of the wind farm; Based on the operational status data and the environmental data, the equivalent aerodynamic load acting on the wind turbine is estimated online using a parameter identification algorithm and in accordance with the wind turbine dynamics relationship. The generator torque compensation amount is calculated based on the equivalent aerodynamic load and the load reference value, and the pitch angle compensation amount is calculated based on the equivalent aerodynamic load and the cutoff frequency. The generator torque compensation amount and the blade pitch angle compensation amount are superimposed on the original control command of the wind turbine to generate a load reduction execution command, and the load is reduced according to the load reduction execution command. The step of estimating the equivalent aerodynamic load acting on the wind turbine online based on the operating status data and the environmental data, using a parameter identification algorithm and the wind turbine dynamics relationship, includes: Based on the wind speed information in the environmental data, the generator speed in the operating status data is filtered, and the operating status data corresponding to the speed data segment located in the normal operating range of the wind turbine is retained to obtain the filtered operating status data. Extract the generator speed sequence and generator torque sequence from the filtered operating status data; Based on the aforementioned wind turbine dynamics relationship, a wind turbine dynamics equation is established, which relates the wind turbine moment of inertia, the differential value of the generator speed, the measured value of the generator torque, and the equivalent aerodynamic torque acting on the wind turbine. The wind turbine dynamics equations are solved using a parameter identification algorithm based on the generator speed sequence and generator torque sequence to obtain an estimated equivalent aerodynamic torque. The estimated value of the equivalent aerodynamic torque is used as the equivalent aerodynamic load; The step of solving the wind turbine dynamics equations using a parameter identification algorithm on the generator speed sequence and generator torque sequence to obtain the equivalent aerodynamic torque estimate includes: The generator speed differential is calculated based on the generator speed sequence, and the generator speed differential at the current sampling moment is combined with the generator torque measurement value to form an observation scalar according to the generator torque sequence and the wind turbine dynamics equation. The gain coefficient for the current sampling time is calculated based on the covariance matrix estimated from the parameters at the previous sampling time. Based on the gain coefficient, the observed scalar, and the estimated equivalent aerodynamic torque at the previous sampling time, the estimated equivalent aerodynamic torque at the current sampling time is calculated using a recursive least squares update algorithm.

2. The method as described in claim 1, characterized in that, The steps for calculating the generator torque compensation based on the equivalent aerodynamic load and load reference value include: The load deviation is calculated based on the equivalent aerodynamic load and the load reference value. The initial torque compensation amount is determined based on the load deviation. The initial torque compensation amount is subjected to rate and amplitude limits to obtain the generator torque compensation amount.

3. The method as described in claim 2, characterized in that, The steps of applying rate and amplitude limits to the initial torque compensation amount to obtain the generator torque compensation amount include: The positive and negative amplitude limit thresholds for torque compensation are set according to the instantaneous torque bearing limit value of the wind turbine generator drive chain. The threshold for limiting the rate of change of torque compensation is set based on the dynamic response capability of the wind turbine converter and the vibration suppression requirements of the wind turbine drive train. The initial torque compensation amount is applied to the positive and negative amplitude limit thresholds of the torque compensation amount and the change rate limit threshold of the torque compensation amount to obtain the generator torque compensation amount.

4. The method as described in claim 1, characterized in that, The steps for calculating the pitch angle compensation based on the equivalent aerodynamic load and cutoff frequency include: The high-frequency fluctuation component of the load is obtained by separating it from the equivalent aerodynamic load based on the cutoff frequency; Determine the gain coefficient corresponding to the current operating condition of the wind turbine based on the gain scheduling table; The pitch angle compensation amount is obtained based on the high-frequency fluctuation component and the gain coefficient.

5. The method as described in claim 4, characterized in that, The step of determining the gain coefficient corresponding to the current operating condition of the wind turbine based on the gain scheduling table includes: Based on the generator speed and generator power in the operating status data, the current operating condition point of the wind turbine is determined; Based on the gain scheduling table, the gain coefficient corresponding to the current operating condition point is obtained by querying.

6. The method as described in claim 1, characterized in that, The steps for acquiring real-time operating status data of wind turbine generators and environmental data of the wind farm include: Real-time acquisition of raw operating status data including generator speed, generator torque, nacelle acceleration, and independent pitch angles of the three blades; Simultaneously collect raw environmental data including wind speed, wind direction, and turbulence intensity; The collected raw operating status data and raw environmental data are time-stamped and validated to remove abnormal data points, thereby obtaining the operating status data of the wind turbine generator and the environmental data of the wind farm.

7. The method as described in claim 1, characterized in that, The step of superimposing the generator torque compensation amount and the blade pitch angle compensation amount onto the original control command of the wind turbine to generate a load reduction execution command, and performing load reduction according to the load reduction execution command, includes: The generator torque compensation amount is superimposed on the original generator torque command to generate a generator torque execution command. The pitch angle compensation amount is superimposed on the original pitch angle command to generate a pitch angle execution command. The generator torque execution command and the pitch angle execution command are encoded to generate a load reduction execution command, and the load is reduced according to the load reduction execution command.

8. A wind turbine generator load adaptive unloading system for complex wind farms, characterized in that, The wind turbine generator load adaptive unloading system for complex wind farms includes: The data acquisition module is used to acquire real-time operating status data of the wind turbine generator and environmental data of the wind farm. The online estimation module is used to estimate the equivalent aerodynamic load acting on the wind turbine online based on the operating status data and the environmental data, through a parameter identification algorithm and according to the wind turbine dynamics relationship. The compensation calculation module is used to calculate the generator torque compensation amount based on the equivalent aerodynamic load and the load reference value, and to calculate the pitch angle compensation amount based on the equivalent aerodynamic load and the cutoff frequency. The load reduction module is used to superimpose the generator torque compensation amount and the blade pitch angle compensation amount onto the original control command of the wind turbine to generate a load reduction execution command, and perform load reduction according to the load reduction execution command. The step of estimating the equivalent aerodynamic load acting on the wind turbine online based on the operating status data and the environmental data, using a parameter identification algorithm and the wind turbine dynamics relationship, includes: Based on the wind speed information in the environmental data, the generator speed in the operating status data is filtered, and the operating status data corresponding to the speed data segment located in the normal operating range of the wind turbine is retained to obtain the filtered operating status data. Extract the generator speed sequence and generator torque sequence from the filtered operating status data; Based on the aforementioned wind turbine dynamics relationship, a wind turbine dynamics equation is established, which relates the wind turbine moment of inertia, the differential value of the generator speed, the measured value of the generator torque, and the equivalent aerodynamic torque acting on the wind turbine. The wind turbine dynamics equations are solved using a parameter identification algorithm based on the generator speed sequence and generator torque sequence to obtain an estimated equivalent aerodynamic torque. The estimated value of the equivalent aerodynamic torque is used as the equivalent aerodynamic load; The step of solving the wind turbine dynamics equations using a parameter identification algorithm on the generator speed sequence and generator torque sequence to obtain the equivalent aerodynamic torque estimate includes: The generator speed differential is calculated based on the generator speed sequence, and the generator speed differential at the current sampling moment is combined with the generator torque measurement value to form an observation scalar according to the generator torque sequence and the wind turbine dynamics equation. The gain coefficient for the current sampling time is calculated based on the covariance matrix estimated from the parameters at the previous sampling time. Based on the gain coefficient, the observed scalar, and the estimated equivalent aerodynamic torque at the previous sampling time, the estimated equivalent aerodynamic torque at the current sampling time is calculated using a recursive least squares update algorithm.

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