A method and device for calculating a wind wheel azimuth deviation value of a wind turbine generator system

Abstract

The embodiment of the specification discloses a wind wheel azimuth deviation value calculation method and device of a wind turbine generator set. The method comprises calculating the blade theoretical load and the blade actual load of the blade at the current wind wheel azimuth deviation value respectively according to the acquired calibration data, determining the target time delay point number based on the maximum cross-correlation between the blade theoretical load and the blade actual load, adjusting the current wind wheel azimuth deviation value according to the average time delay point number when the average time delay point number corresponding to each target time delay point number is greater than the time delay threshold, and obtaining the target current wind wheel azimuth deviation value when the average time delay point number is not greater than the time delay threshold. The wind wheel azimuth deviation value is continuously adjusted through the maximum cross-correlation between the blade theoretical load and the blade actual load, the requirement of automatically calculating the target wind wheel azimuth deviation value is met, the accuracy of the blade load calibration calculation of the wind turbine generator set is improved, and the workload of repeated calibration and repeated calibration on site is reduced.

Description

Technical Field

[0001] This specification relates to the field of wind power generation technology, and in particular to a method for calculating the azimuth deviation of a wind turbine generator set. Background Technology

[0002] In recent years, with the rapid development of wind turbine technology, large-megawatt wind turbines have become mainstream, and the load on the wind turbine rotor is increasing, placing higher demands on the load reduction design of the unit. If the loads on the three blades are unbalanced, the excessive load difference can pose a significant safety hazard to the wind turbine during long-term operation. Furthermore, the blade load magnitude also affects the execution of the unit's pitch control, thus requiring highly accurate measurement of blade loads. Blade loads are measured using fiber optic strain sensors installed at the blade root. After calibration, the load magnitude of the blades can be monitored in real time. The rotor azimuth angle is involved in the theoretical load calculation. Generally, the rotor azimuth angle is calibrated before the load calibration process begins; however, deviations in the rotor azimuth angle can still occur after multiple calibrations, directly affecting the accuracy of the calibration parameters and leading to poor load calibration results, posing certain safety hazards. Summary of the Invention

[0003] This specification provides a method and apparatus for calculating the azimuth deviation of a wind turbine generator set, the technical solution of which is as follows:

[0004] Firstly, embodiments of this specification provide a method for calculating the azimuth deviation of a wind turbine generator set, the method comprising:

[0005] For any blade of a wind turbine generator, the theoretical load and actual load of the blade corresponding to the current rotor azimuth deviation value are calculated based on the obtained calibration data. The calibration data includes the rotor azimuth angle of the calibration blade, the blade pitch angle, the calibration wavelength data, and the blade parameters.

[0006] The target time delay points are determined based on the maximum cross-correlation between the theoretical load and the actual load of the blade.

[0007] In response to the average number of delay points corresponding to each of the target delay points being greater than the delay threshold, the current wind turbine azimuth deviation value is adjusted according to the average delay point value, and the average delay point value is re-determined according to the adjusted current wind turbine azimuth deviation value, until the average delay point value is not greater than the delay threshold, and the target wind turbine azimuth deviation value is obtained.

[0008] Secondly, a device for calculating the azimuth deviation of a wind turbine generator set is provided, the device comprising:

[0009] The calculation module is used to calculate the theoretical load and actual load of any blade of a wind turbine generator set based on the acquired calibration data, according to the current rotor azimuth deviation value of the blade. The calibration data includes the rotor azimuth angle of the calibration blade, the blade pitch angle, the calibration wavelength data, and the blade parameters.

[0010] The time delay module is used to determine the target number of time delay points based on the maximum cross-correlation between the theoretical load and the actual load of the blade.

[0011] The determination module is used to respond to the fact that the average delay point corresponding to each of the target delay points is greater than the delay threshold, adjust the current wind turbine azimuth deviation value according to the average delay point, and redetermine the average delay point according to the adjusted current wind turbine azimuth deviation value, until the average delay point is not greater than the delay threshold, and obtain the target wind turbine azimuth deviation value.

[0012] Thirdly, an electronic device is provided, including a device processor and a memory;

[0013] The device processor is connected to the memory;

[0014] The memory is used to store executable program code;

[0015] The device processor runs a program corresponding to the executable program code stored in the memory to perform the steps of the method provided as in the first aspect or any possible implementation thereof.

[0016] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, the computer-readable storage medium storing instructions that, when executed on a computer or device processor, cause the computer or device processor to perform the method provided as in the first aspect or any possible implementation thereof.

[0017] The beneficial effects of the technical solutions provided in some embodiments of this specification include at least the following:

[0018] In one or more embodiments of this specification, for any blade of a wind turbine generator, the theoretical load and actual load of the blade corresponding to the current azimuth deviation value of the rotor are calculated based on the acquired calibration data. Then, the target time delay points are determined based on the maximum cross-correlation between the theoretical and actual loads. When the average time delay points corresponding to each target time delay point are greater than a time delay threshold, the current azimuth deviation value of the rotor is adjusted based on the average time delay points, and the average time delay points are re-determined based on the adjusted value. This process continues until the average time delay points are no greater than the time delay threshold, at which point the target current azimuth deviation value of the rotor is obtained. By continuously adjusting the rotor azimuth deviation value through the maximum cross-correlation between the theoretical and actual loads of the blade, the requirement for automatically calculating the target rotor azimuth deviation value is met, improving the accuracy of wind turbine generator blade load calibration calculation and reducing the workload of repeated calibration and recalibration on-site. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating a method for calculating the azimuth deviation of a wind turbine rotor, provided in an embodiment of this specification;

[0021] Figure 2 This is a schematic diagram of the structure of a wind turbine rotor azimuth deviation calculation device provided in the embodiments of this specification;

[0022] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this specification. Detailed Implementation

[0023] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0024] The terms "first," "second," "third," etc., in the description, claims, and accompanying drawings are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0025] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this specification. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0026] Please see Figure 1 , Figure 1 This document presents an overall flowchart illustrating a method for calculating the azimuth deviation of a wind turbine generator set, as provided in an embodiment of this specification.

[0027] like Figure 1 As shown, the method for calculating the azimuth deviation of the wind turbine generator set may include at least the following steps:

[0028] Step 101: For any blade of the wind turbine generator set, calculate the theoretical load and actual load of the blade corresponding to the current azimuth deviation value of the wind turbine based on the obtained calibration data.

[0029] The calibration data includes the azimuth angle of the calibrated blade wind turbine, the blade pitch angle, the calibration wavelength data, and the blade parameters.

[0030] In the embodiments of this specification, each wind turbine may include 2, 3, or more blades depending on actual design requirements. To accurately calculate the rotor azimuth deviation value of the wind turbine and ensure that the blade load measured by the sensors is closer to the actual blade load, thereby improving the accuracy of the wind turbine blade load calibration calculation, for any blade of the wind turbine, it is necessary to first calculate the theoretical and actual blade load based on the calibration data obtained through calibration tests, under the current rotor azimuth deviation value. Specifically, when obtaining calibration data, three or four fiber optic strain sensors installed inside the blade root of each blade can be used for measurement to obtain sensor wavelength data. Then, the calibration coefficient matrix is ​​determined using the rotor azimuth, blade pitch angle, calibration wavelength data, and blade parameters obtained during the calibration process, and the sensor measured wavelength data is converted into blade load data. The initial rotor azimuth deviation value can be initially set to... The theoretical load on the blade is calculated by combining the azimuth deviation of the wind turbine, and the actual load on the blade is calculated based on the calibration coefficient matrix and the measured wavelength data of the sensor.

[0031] In one possible implementation, the step of calculating the theoretical load and actual load of the blade corresponding to the current wind turbine azimuth deviation value based on the acquired calibration data includes:

[0032] The theoretical load on the blade is determined by the calculated difference between the calibrated blade azimuth angle and the current azimuth angle deviation.

[0033] The actual load on the blade is determined based on the theoretical load and calibration wavelength data.

[0034] In the embodiments of this specification, when calculating the theoretical load and actual load of the blade corresponding to the current rotor azimuth deviation value based on the acquired calibration data, the initial current rotor azimuth deviation value can be set as follows: If subsequent pre-defined conditions determine that the requirements are not met, the rotor azimuth deviation value needs to be adjusted to determine a new current rotor azimuth deviation value. Then, the theoretical load on the blade is determined based on the calculated difference between the calibrated rotor azimuth deviation value in the calibration data and the adjusted current rotor azimuth deviation value. Specifically, when determining the theoretical load on the blade by calculating the difference, i.e., the compensated rotor azimuth deviation, the calculated difference can be directly substituted into the theoretical load calculation formula for calculation. Alternatively, since the blade's physical dimensions are fixed, a deviation-load mapping database can be pre-set based on historical calculation data. The corresponding theoretical load on the blade can then be obtained by directly querying the deviation value in the database.

[0035] Next, the calibration coefficient matrix and calibration wavelength data are obtained through calibration calculations, and then converted into actual blade loads. Note that the calibration coefficient matrix changes as the azimuth deviation of the wind turbine is adjusted.

[0036] In one possible implementation, determining the theoretical load on the blade based on the calculated difference between the calibrated blade azimuth angle and the current azimuth angle deviation includes:

[0037] The wind turbine azimuth correction angle is determined by the calculated difference between the calibrated blade wind turbine azimuth angle and the current wind turbine azimuth angle deviation value.

[0038] The wind turbine azimuth correction angle, blade pitch angle, and blade parameters are calculated based on the theoretical load calculation formula to obtain the theoretical load of the blade.

[0039] In the embodiments of this specification, the difference between the calibrated blade azimuth angle and the current azimuth angle deviation can be calculated first, and this difference can be used as the azimuth correction angle. As an example, the azimuth correction angle... =calibrated blade rotor azimuth angle q - current rotor azimuth angle deviation value Q. Next, determine the blade pitch angle and blade parameters for this type of blade, which may include the distance from the center of gravity to the blade root, blade mass, rotor tilt angle, and blade cone angle. Further, substitute the rotor azimuth correction angle, blade pitch angle, and blade parameters into the determined theoretical load calculation formula to obtain the theoretical load on the blade. The theoretical load calculation formula is as follows:

[0040]

[0041] Where M1 represents the theoretical load on the blade, r represents the distance from the center of gravity to the blade root, and m represents the blade mass. It is the gravitational constant. Indicates the wind turbine azimuth correction angle. Indicates the wind turbine tilt angle. Indicates the blade cone angle. This indicates the blade pitch angle.

[0042] In one possible implementation, determining the actual load on the blade based on the theoretical load and calibration wavelength data includes:

[0043] The calibration coefficient matrix is ​​obtained by fitting the theoretical load of the blade and the measured wavelength data of the sensor.

[0044] The actual load on the blade is determined based on the calibration coefficient matrix and calibration wavelength data.

[0045] In the embodiments described in this specification, a calibration coefficient matrix can be obtained first through calibration calculation based on the theoretical load of the blade and the measured wavelength data of the sensor. The calibration coefficient matrix includes the k-coefficient and the initial wavelength. As an example, when four fiber optic strain sensors installed inside the blade root of each wind turbine blade are used for measurement, the measured wavelength of the sensor is... The initial wavelengths of each sensor obtained after calibration calculations are: The sensor wavelength variation matrix is ​​obtained by subtracting the corresponding initial wavelength from each actual measured wavelength. Then, the blade root flapping moment and blade root flaring moment are determined based on the calibration coefficient matrix and the sensor wavelength variation matrix; these two are the actual blade loads. The specific formula for calculating the actual blade load is as follows:

[0046]

[0047] Where M2 is the actual load on the blade. For the leaf root oscillation bending moment, For the leaf roots to wield bending moment, The k coefficients are the calibration coefficient matrix. This is the sensor wavelength variation matrix. The initial calibration wavelength for each sensor. The actual measurement wavelength for each sensor.

[0048] Step 102: Determine the target time delay points based on the maximum cross-correlation between the theoretical load and the actual load of the blade.

[0049] In the embodiments of this specification, in order to accurately calculate the azimuth deviation angle of the wind turbine generator set, so that the actual load of the blade calculated by calibration is closer to the theoretical load of the blade, and to improve the accuracy of the wind turbine generator set blade load measurement, it is necessary to use the maximum cross-correlation between the theoretical load and the actual load of the blade to determine the corresponding target time delay points, and determine the time delay between the theoretical load and the actual load of the blade based on the target time delay points, so as to convert it into the azimuth deviation value of the wind turbine generator set to compensate for the azimuth angle of the wind turbine generator set.

[0050] When determining the target number of delay points, the cross-correlation between the two can be calculated first, and then the peak position of the cross-correlation number can be queried to locate the maximum cross-correlation.

[0051] In one possible implementation, determining the target time delay point number based on the maximum cross-correlation between the theoretical load and the actual load of the blade includes:

[0052] Determine the cross-correlation function between the theoretical load and the actual load on the blade;

[0053] The cross-correlation function is subjected to time delay traversal using the extreme value traversal method to determine the target time delay point corresponding to the maximum cross-correlation.

[0054] In the embodiments of this specification, the theoretical load on the blades is first calculated based on the wind turbine azimuth angle after compensation for the azimuth angle deviation and the remaining blade parameters. Next, calibration calculations are performed based on the theoretical load and the wavelength in the calibration data to obtain the calibration parameter matrix. The actual load on the blades is then obtained based on the calibration parameter matrix and the wavelength variation matrix. Finally, cross-correlation calculations are performed based on the cross-correlation between the theoretical load and the actual load on the blades, as follows:

[0055]

[0056] Where, sequence For the actual load sequence, For theoretical load sequences, Let be the cross-correlation value at time shift m.

[0057] Next, the cross-correlation values ​​are determined by performing a time-delay traversal using the maximum / minimum traversal method. The maximum delay point m corresponds to this delay, and this number is determined as the target delay point. .

[0058] In one possible implementation, after determining the target time delay point number based on the maximum cross-correlation between the theoretical load and the actual load of the blade, the method further includes:

[0059] Determine the number of blades in the wind turbine generator set and the target time delay points corresponding to each blade;

[0060] The average number of delay points is determined based on the number of blades and the number of target delay points.

[0061] In the embodiments of this specification, to eliminate interference from accidental measurement errors, after obtaining the target time delay points corresponding to each blade, it is necessary to process the target time delay points using an averaging method to improve robustness. Specifically, the number of blades in the wind turbine generator set and the target time delay points corresponding to each blade can be determined first. Then, the average time delay points can be determined based on the number of blades and the target time delay points. Generally, each wind turbine generator set may include 2, 3, or more blades depending on actual design requirements. As an example, taking 3 blades as an example, the average time delay points are... .

[0062] Step 103: In response to the average delay point number corresponding to each of the target delay points being greater than the delay threshold, adjust the current wind turbine azimuth deviation value according to the average delay point number, and redetermine the average delay point number according to the adjusted current wind turbine azimuth deviation value, until the average delay point number is not greater than the delay threshold, and obtain the target wind turbine azimuth deviation value.

[0063] In the embodiments of this specification, after determining the average time delay points corresponding to each target time delay point, it is necessary to compare the average time delay points with a time delay threshold to determine whether the current wind turbine azimuth deviation value meets the requirements. Specifically, when the average time delay points are greater than the time delay threshold, it indicates that the phase difference between the theoretical load and the actual load of the blade is too large, the accuracy of the wind turbine blade load calibration calculation is low, and further compensation and adjustment of the current wind turbine azimuth angle are required. Specifically, the current wind turbine azimuth deviation value can be adjusted based on the determined average time delay points. Furthermore, based on the current wind turbine azimuth angle after compensation adjustment, the theoretical load and actual load of the blades are calculated similarly. The average time delay points are then recalculated and compared with the time delay threshold. If it is still greater than the time delay threshold, the adjustment process is repeated until the determined average time delay points are no greater than the time delay threshold. The target wind turbine azimuth angle deviation value is then output, thus completing the calculation of the wind turbine azimuth angle deviation value. At the same time, the calibration parameter matrix obtained after calibration after the wind turbine azimuth angle deviation value is corrected is output. Combined with the measured sensor wavelength data, a more accurate measured load of the wind turbine blades can be obtained.

[0064] In one possible implementation, adjusting the current wind turbine azimuth deviation value based on the average time delay points includes:

[0065] The single decrease angle is determined by the product of the decrease coefficient and the average delay point.

[0066] The current wind turbine azimuth deviation value is adjusted based on the angle difference between the current wind turbine azimuth deviation value and the single decreasing angle.

[0067] In the embodiments of this specification, when reducing the current wind turbine azimuth deviation value based on the average delay points, a reduction coefficient can first be determined according to the accuracy requirements. Specifically, the reduction coefficient can be set to 0-0.5; the higher the accuracy requirement, the smaller the corresponding reduction coefficient. Generally, 0.1 can be used. Next, the product of the reduction coefficient and the average delay points is determined as the single reduction angle, i.e., the single reduction angle. Furthermore, the current wind turbine azimuth deviation is reduced based on the angle difference between the current azimuth deviation and the single decreasing angle. Specifically, the adjusted current wind turbine azimuth deviation... = Current wind turbine azimuth deviation value in the previous stage - .

[0068] During the first initial adjustment, Desirable .

[0069] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0070] Please refer to the following. Figure 2 , Figure 2 A schematic diagram of a wind turbine rotor azimuth deviation calculation device provided in an embodiment of this specification is shown. It should be noted that... Figure 2 The wind turbine rotor azimuth deviation calculation device shown is used to perform the functions described in this application. Figure 1 The methods shown in the embodiments are for illustrative purposes only, illustrating the parts relevant to the embodiments of this application. For specific technical details not disclosed, please refer to this application. Figure 1 The example shown.

[0071] like Figure 2As shown, the wind turbine rotor azimuth deviation calculation device may include at least:

[0072] Calculation module 201 is used to calculate the theoretical load and actual load of any blade of a wind turbine generator set based on the acquired calibration data, according to the current rotor azimuth deviation value of the blade. The calibration data includes the rotor azimuth angle of the calibration blade, the blade pitch angle, the calibration wavelength data, and the blade parameters.

[0073] The delay module 202 is used to determine the target number of delay points based on the maximum cross-correlation between the theoretical load and the actual load of the blade.

[0074] The determining module 203 is used to respond to the average delay point number corresponding to each of the target delay points being greater than the delay threshold, adjust the current wind turbine azimuth deviation value according to the average delay point number, and redetermine the average delay point number according to the adjusted current wind turbine azimuth deviation value, until the average delay point number is not greater than the delay threshold, and obtain the target wind turbine azimuth deviation value.

[0075] In one possible implementation, the computing module 201 is specifically used for:

[0076] The theoretical load on the blade is determined by the calculated difference between the calibrated blade azimuth angle and the current azimuth angle deviation.

[0077] The actual load on the blade is determined based on the theoretical load and calibration wavelength data.

[0078] In one possible implementation, the computing module 201 is further configured to:

[0079] The wind turbine azimuth correction angle is determined by the calculated difference between the calibrated blade wind turbine azimuth angle and the current wind turbine azimuth angle deviation value.

[0080] The wind turbine azimuth correction angle, blade pitch angle, and blade parameters are calculated based on the theoretical load calculation formula to obtain the theoretical load of the blade.

[0081] In one possible implementation, the computing module 201 is further configured to:

[0082] The calibration coefficient matrix is ​​obtained by fitting the theoretical load of the blade and the measured wavelength data of the sensor.

[0083] The actual load on the blade is determined based on the calibration coefficient matrix and calibration wavelength data.

[0084] In one possible implementation, the delay module 202 is specifically used for:

[0085] Determine the cross-correlation function between the theoretical load and the actual load on the blade;

[0086] The cross-correlation function is subjected to time delay traversal using the extreme value traversal method to determine the target time delay point corresponding to the maximum cross-correlation.

[0087] In one possible implementation, the delay module 202 is further configured to:

[0088] Determine the number of blades in the wind turbine generator set and the target time delay points corresponding to each blade;

[0089] The average number of delay points is determined based on the number of blades and the number of target delay points.

[0090] In one possible implementation, the determining module 203 is specifically used for:

[0091] The single decrease angle is determined by the product of the decrease coefficient and the average delay point.

[0092] The current wind turbine azimuth deviation value is adjusted based on the angle difference between the current wind turbine azimuth deviation value and the single decreasing angle.

[0093] Those skilled in the art will clearly understand that the technical solutions of the embodiments of this application can be implemented by means of software and / or hardware. In this specification, "unit" and "module" refer to software and / or hardware that can independently complete or cooperate with other components to complete a specific function, wherein the hardware may be, for example, a field-programmable gate array (FPGA), an integrated circuit (IC), etc.

[0094] Each processing unit and / or module in the embodiments of this application can be implemented by an analog circuit that implements the functions described in the embodiments of this application, or by software that executes the functions described in the embodiments of this application.

[0095] Please refer to the following. Figure 3 , Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this specification is shown.

[0096] like Figure 3 As shown, the electronic device 300 may include at least one device processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0097] The communication bus 302 can be used to realize the connection and communication of the above components.

[0098] The user interface 303 may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0099] The network interface 304 may include, but is not limited to, Bluetooth modules, NFC modules, Wi-Fi modules, etc.

[0100] The device processor 301 may include one or more processing cores. The device processor 301 connects to various parts within the electronic device 300 using various interfaces and lines. It executes various functions and processes data of the electronic device 300 by running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling data stored in the memory 305. Optionally, the device processor 301 may be implemented using at least one hardware form of DSP, FPGA, or PLA. The device processor 301 may integrate one or more of the following: CPU, GPU, and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the device processor 301 and may be implemented as a separate chip.

[0101] The memory 305 may include RAM or ROM. Optionally, the memory 305 may include a non-transitory computer-readable medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned device processor 301. Figure 3 As shown, the memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.

[0102] Specifically, the device processor 301 can call the wind turbine rotor azimuth deviation value calculation application stored in the memory 305, and specifically perform the following operations:

[0103] For any blade of a wind turbine generator, the theoretical load and actual load of the blade corresponding to the current rotor azimuth deviation value are calculated based on the obtained calibration data. The calibration data includes the rotor azimuth angle of the calibration blade, the blade pitch angle, the calibration wavelength data, and the blade parameters.

[0104] The target time delay points are determined based on the maximum cross-correlation between the theoretical load and the actual load of the blade.

[0105] In response to the average number of delay points corresponding to each of the target delay points being greater than the delay threshold, the current wind turbine azimuth deviation value is adjusted according to the average delay point value, and the average delay point value is re-determined according to the adjusted current wind turbine azimuth deviation value, until the average delay point value is not greater than the delay threshold, and the target wind turbine azimuth deviation value is obtained.

[0106] As an optional embodiment of this specification, the step of calculating the theoretical load and actual load of the blade corresponding to the current wind turbine azimuth deviation value based on the acquired calibration data includes:

[0107] The theoretical load on the blade is determined by the calculated difference between the calibrated blade azimuth angle and the current azimuth angle deviation.

[0108] The actual load on the blade is determined based on the theoretical load and calibration wavelength data.

[0109] As an optional embodiment of this specification, the step of determining the theoretical load on the blade based on the calculated difference between the calibrated blade azimuth angle and the current blade azimuth angle deviation includes:

[0110] The wind turbine azimuth correction angle is determined by the calculated difference between the calibrated blade wind turbine azimuth angle and the current wind turbine azimuth angle deviation value.

[0111] The wind turbine azimuth correction angle, blade pitch angle, and blade parameters are calculated based on the theoretical load calculation formula to obtain the theoretical load of the blade.

[0112] As an optional embodiment of this specification, determining the actual load on the blade based on the theoretical load and calibration wavelength data includes:

[0113] The calibration coefficient matrix is ​​obtained by fitting the theoretical load of the blade and the measured wavelength data of the sensor.

[0114] The actual load on the blade is determined based on the calibration coefficient matrix and calibration wavelength data.

[0115] As an optional embodiment of this specification, determining the target time delay point number based on the maximum cross-correlation between the theoretical load and the actual load of the blade includes:

[0116] Determine the cross-correlation function between the theoretical load and the actual load on the blade;

[0117] The cross-correlation function is subjected to time delay traversal using the extreme value traversal method to determine the target time delay point corresponding to the maximum cross-correlation.

[0118] As an optional embodiment of this specification, after determining the target time delay point number based on the maximum cross-correlation between the theoretical load and the actual load of the blade, the method further includes:

[0119] Determine the number of blades in the wind turbine generator set and the target time delay points corresponding to each blade;

[0120] The average number of delay points is determined based on the number of blades and the number of target delay points.

[0121] As an optional embodiment of this specification, adjusting the current wind turbine azimuth deviation value based on the average time delay points includes:

[0122] The single decrease angle is determined by the product of the decrease coefficient and the average delay point.

[0123] The current wind turbine azimuth deviation value is adjusted based on the angle difference between the current wind turbine azimuth deviation value and the single decreasing angle.

[0124] This specification also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0125] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0126] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0127] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0128] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0129] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0130] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0131] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0132] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

Claims

1. A method of calculating a yaw error value of a wind wheel of a wind turbine, characterized by, The method comprises: For any blade of a wind turbine generator, the blade theoretical load and the blade actual load corresponding to the current yaw angle deviation value of the blade are calculated respectively according to the obtained calibration data, the calibration data including calibration blade yaw angle, blade pitch angle, calibration wavelength data and blade parameters; The target time delay point number is determined based on the maximum cross-correlation between the blade theoretical load and the blade actual load; In response to the average time delay point number corresponding to each target time delay point number being greater than a time delay threshold value, the current yaw angle deviation value is adjusted according to the average time delay point number, and the average time delay point number is re-determined according to the adjusted current yaw angle deviation value, until the average time delay point number is not greater than the time delay threshold value, and a target yaw angle deviation value is obtained; The blade theoretical load and the blade actual load corresponding to the current yaw angle deviation value of the blade are calculated respectively according to the obtained calibration data, which comprises: The blade theoretical load is determined according to the calculation difference value of the calibration blade yaw angle and the current yaw angle deviation value; The blade actual load is determined based on the blade theoretical load and the calibration wavelength data; The blade theoretical load is determined according to the calculation difference value of the calibration blade yaw angle and the current yaw angle deviation value, which comprises: The yaw correction angle is determined according to the calculation difference value of the calibration blade yaw angle and the current yaw angle deviation value; The yaw correction angle, the blade pitch angle and the blade parameters are calculated based on the theoretical load calculation formula, and the blade theoretical load is obtained; The blade actual load is determined based on the blade theoretical load and the sensor measured wavelength data, which comprises: The calibration coefficient matrix is obtained by fitting calculation according to the blade theoretical load and the sensor measured wavelength data; The blade actual load is determined based on the calibration coefficient matrix and the calibration wavelength data; The current yaw angle deviation value is adjusted according to the average time delay point number, which comprises: The single-time decreasing angle is determined according to the product of the decreasing coefficient and the average time delay point number; The current yaw angle deviation value is adjusted based on the angle difference value between the current yaw angle deviation value and the single-time decreasing angle.

2. The method of claim 1, wherein, The target time delay point number is determined based on the maximum cross-correlation between the blade theoretical load and the blade actual load, which comprises: The cross-correlation function between the blade theoretical load and the blade actual load is determined; The target time delay point number corresponding to the maximum cross-correlation is determined by time delay traversal of the cross-correlation function according to the maximum value traversal method.

3. The method of claim 1, wherein, After the target time delay point number is determined based on the maximum cross-correlation between the blade theoretical load and the blade actual load, the method further comprises: The number of blades of the wind turbine generator and the target time delay point number corresponding to each blade are determined; The average time delay point number is determined based on the number of blades and each target time delay point number.

4. A wind turbine azimuth deviation value calculating device for a wind turbine generator system, characterized by comprising: The device comprises: The computing module is configured to calculate, for any blade of the wind turbine generator set, a blade theoretical load and a blade actual load corresponding to a current yaw angle deviation value of the blade according to acquired calibration data, the calibration data including calibration blade yaw angle, blade pitch angle, calibration wavelength data and blade parameters; The time delay module is configured to determine target time delay point numbers based on maximum cross-correlation between the blade theoretical load and the blade actual load; The determining module is configured to, in response to an average time delay point number corresponding to each of the target time delay point numbers being greater than a time delay threshold, adjust the current yaw angle deviation value according to the average time delay point number, and re-determine the average time delay point number according to the adjusted current yaw angle deviation value, until the average time delay point number is not greater than the time delay threshold, to obtain a target yaw angle deviation value; The computing module is specifically configured to: determine the blade theoretical load according to a calculation difference between the calibration blade yaw angle and the current yaw angle deviation value; determine the blade actual load based on the blade theoretical load and the calibration wavelength data; The computing module is specifically further configured to: determine a yaw correction angle according to a calculation difference between the calibration blade yaw angle and the current yaw angle deviation value; calculate the blade theoretical load based on a theoretical load calculation formula, the yaw correction angle, the blade pitch angle and the blade parameters; The computing module is specifically further configured to: perform fitting calculation according to the blade theoretical load and sensor measured wavelength data to obtain a calibration coefficient matrix; determine the blade actual load based on the calibration coefficient matrix and the calibration wavelength data; The determining module is specifically configured to: determine a single decrement angle according to a product of a decrement coefficient and the average time delay point number; adjust the current yaw angle deviation value based on an angle difference between the current yaw angle deviation value and the single decrement angle.

5. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the steps of the method of any one of claims 1-3 when executing the computer program. 6.A computer readable storage medium having stored thereon a computer program, the computer readable storage medium having stored therein instructions which, when executed on a computer or processor, cause the computer or processor to perform the steps of the method of any one of claims 1-3.

Images