Wind speed calibration method and system of wind generating set, medium and equipment

Abstract

The invention provides a wind speed calibration method for a wind generating set. The wind speed calibration method comprises the steps that the real-time standard wind speed at the current moment is obtained; determining a wind speed standard interval corresponding to the real-time standard wind speed, and calculating calibration parameters of a transfer function model according to the wind speed standard interval; and performing wind speed calibration on a wind speed sensor based on the calibration parameters, the real-time standard wind speed and the transfer function model to obtain a calibrated wind speed. According to the method, measurement errors caused by wind speed changes can be reduced, it is ensured that the wind speed sensor can keep stable performance under different wind speed conditions, the method adapts to various complex and changeable environments, the calibration process is more efficient and reliable, and therefore the control strategy of the wind generating set is further optimized, and the power generation efficiency is improved. The invention further provides a wind speed calibration system of the wind generating set, a computer readable storage medium and electronic equipment, which have the above beneficial effects.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wind power generation, in particular to a wind speed calibration method, system, medium and equipment for a wind turbine generator system. BACKGROUND

[0002] With the rapid development of the wind power industry, the performance evaluation and optimization of wind turbine generators have become increasingly important. The power curve, as a key indicator of wind turbine generator power generation performance, directly affects the evaluation of wind farm power generation efficiency, equipment operation state monitoring, and subsequent intelligent operation and maintenance management. However, in actual operation, the power curve of the wind turbine generator is often affected by various factors, causing it to deviate from the design value or theoretical model, and thus affecting the overall operation benefit of the wind farm.

[0003] Among them, the blade wake effect and complex environmental factors are one of the important reasons for the deviation of the wind measurement data. The blade wake is a low-speed, high-turbulence area formed behind the blade during the rotation of the wind turbine generator blade. When the anemometer or wind measurement equipment is located in the wake area, the wind speed data collected is often lower than the actual free flow wind speed, and the turbulence intensity increases significantly. This deviation not only leads to inaccurate wind speed measurement, but also further affects the fitting accuracy of the power curve of the wind turbine generator, causing distortion in the evaluation of power generation performance.

[0004] In addition, wind farms are usually built in areas with complex terrain and variable climate, and environmental factors such as terrain undulations, obstacle shielding, temperature changes, humidity fluctuations, etc. can also significantly affect the accuracy of the wind measurement equipment. For example, in mountainous or hilly areas, the direction and speed of the wind flow will change significantly, causing systematic deviation in the wind measurement data; while in coastal or high-humidity areas, changes in the water vapor content in the air can also affect the measurement accuracy of ultrasonic wind measurement equipment.

[0005] Traditional wind measurement data processing methods usually use simple filtering or averaging algorithms, which are difficult to effectively identify and correct systematic deviations caused by wake and environmental factors. This leads to the phenomenon of "drift" or "distortion" in the power curve of the wind turbine generator in actual application, which further affects the performance evaluation, fault diagnosis and intelligent control strategy formulation of the wind farm. SUMMARY

[0006] The purpose of the present application is to provide a wind speed calibration method, system, computer readable storage medium and electronic device for a wind turbine generator, which can effectively calibrate the wind power of the wind turbine generator.

[0007] To solve the above technical problems, the present application provides a wind speed calibration method for a wind turbine generator, and the specific technical solutions are as follows:

[0008] obtaining a real-time standard wind speed at the current time;

[0009] determine a wind speed standard interval corresponding to the real-time standard wind speed, and calculate a calibration parameter of a transfer function model according to the wind speed standard interval;

[0010] calibrate the wind speed sensor based on the calibration parameter, the real-time standard wind speed and the transfer function model to obtain a calibrated wind speed.

[0011] Optionally, the obtaining of the real-time standard wind speed at the current time comprises:

[0012] obtaining an environmental parameter of an environment in which the wind turbine generator is located;

[0013] obtaining a measured wind speed at the current time;

[0014] performing standard wind speed conversion based on the environmental parameter and the measured wind speed to obtain the real-time standard wind speed.

[0015] Optionally, before the determining of the wind speed standard interval corresponding to the real-time standard wind speed, the method further comprises:

[0016] judging whether a difference between the real-time standard wind speed and a set standard wind speed interval satisfies an allowable deviation threshold value;

[0017] if not, performing wind speed correction on the real-time standard wind speed, and determining the corresponding wind speed standard interval with reference to a corrected wind speed after the correction.

[0018] Optionally, the obtaining of the measured wind speed at the current time comprises:

[0019] calling a laser radar wind measuring instrument to obtain measured wind speeds of the wind turbine generator at different heights and different wind directions;

[0020] calculating an equivalent wind speed of a wind wheel based on the measured wind speeds.

[0021] Optionally, the calculating of the calibration parameter of the transfer function model according to the wind speed standard interval comprises:

[0022] if the wind speed standard interval belongs to a first wind speed interval, calling a low wind speed correction model to output a wind speed adjustment parameter;

[0023] if the wind speed standard interval belongs to a second wind speed interval, calling a wind speed correction model to output a wind speed correction parameter;

[0024] if the wind speed standard interval belongs to a third wind speed interval, calling a wind speed calibration model to output a wind speed calibration parameter with reference to a current load of the wind turbine generator.

[0025] Optionally, the calibrating of the wind speed sensor based on the calibration parameter, the real-time standard wind speed and the transfer function model to obtain the calibrated wind speed comprises:

[0026] substituting the calibration parameter and the real-time standard wind speed into a transfer function model, to output a calibrated wind speed.

[0027] Optionally, the transfer function model is:

[0028]

[0029] wherein, is the calibrated wind speed, is the real-time standard wind speed, T is temperature, H is humidity, and P is air pressure, , , , are regression coefficients fitted, is a fitting error term.

[0030] The application also provides a wind speed calibration system for a wind turbine generator, comprising:

[0031] a wind speed acquisition module configured to acquire a real-time standard wind speed at a current time;

[0032] a calibration parameter calculation module configured to determine a wind speed standard interval corresponding to the real-time standard wind speed, and calculate a calibration parameter of a transfer function model according to the wind speed standard interval;

[0033] a wind speed calibration module configured to calibrate a wind speed sensor based on the calibration parameter, the real-time standard wind speed, and the transfer function model, to obtain a calibrated wind speed.

[0034] The application also provides a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the wind speed calibration method as described above.

[0035] The application also provides an electronic device comprising a memory and a processor, wherein the memory has a computer program stored therein, and the processor, when invoking the computer program in the memory, implements the steps of the wind speed calibration method as described above.

[0036] The application provides a wind speed calibration method for a wind turbine generator, comprising: acquiring a real-time standard wind speed at a current time; determining a wind speed standard interval corresponding to the real-time standard wind speed, and calculating a calibration parameter of a transfer function model according to the wind speed standard interval; and calibrating a wind speed sensor based on the calibration parameter, the real-time standard wind speed, and the transfer function model, to obtain a calibrated wind speed.

[0037] ​The application can dynamically determine the calibration parameter of the transfer function model most suitable for the current wind speed condition by acquiring the real-time standard wind speed and matching it with the wind speed standard interval. This helps to reduce the measurement error caused by changes in wind speed, thereby improving the accuracy of the wind speed sensor measurement results. At the same time, the calibration parameter of the transfer function model can be adaptively adjusted according to the changes in real-time wind speed, ensuring that the wind speed sensor can maintain stable performance under different wind speed conditions and adapt to various complex and variable environments such as meteorological observation, wind power plant, etc. Using the transfer function model to calibrate the wind speed sensor can more accurately describe the input-output relationship of the sensor, better compensate for the non-linear error and lag error of the sensor, and make the calibration process more efficient and reliable, thereby further optimizing the control strategy of the wind turbine generator and improving the power generation efficiency.

[0038] The application also provides a wind speed calibration system for a wind turbine generator, a computer readable storage medium and an electronic device, which have the above beneficial effects, which will not be described here. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to the provided drawings without creative labor.

[0040] Figure 1 A flowchart of a wind speed calibration method for a wind turbine generator provided by an embodiment of the present application;

[0041] Figure 2 A transfer function application process flowchart provided by an embodiment of the present application;

[0042] Figure 3 A wind speed calibration system structure schematic diagram for a wind turbine generator provided by an embodiment of the present application;

[0043] Figure 4 A structure diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0045] The object information involved in the present application includes but is not limited to object device information, object personal information, etc., and the data includes but is not limited to data for analysis, stored data, displayed data, etc., which are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of related data need to comply with relevant national and regional laws, regulations and standards.

[0046] Referring to Figure 1 , Figure 1 A flowchart of a wind speed calibration method of a wind turbine generator set provided by an embodiment of the present application, the method comprising:

[0047] S101: obtaining a real-time standard wind speed at the current time;

[0048] S102: determining a wind speed standard interval corresponding to the real-time standard wind speed, and calculating a calibration parameter of a transfer function model according to the wind speed standard interval;

[0049] S103: calibrating a wind speed sensor based on the calibration parameter, the real-time standard wind speed and the transfer function model to obtain a calibrated wind speed.

[0050] S101 aims to obtain a real-time standard wind speed, and it needs to be noted that the real-time standard wind speed is not equal to the measured wind speed. After the wind turbine generator set is started, the system automatically inputs and processes the basic information of the environment in the area, including parameters such as temperature, humidity and air pressure. These parameters are crucial for subsequent wind speed measurement and calibration process, ensuring that all measured values are under standard reference conditions. Therefore, the real-time standard wind speed in S101 refers to the wind speed obtained after standardizing the measured wind speed.

[0051] In a feasible implementation, the following steps can be included:

[0052] S1011: obtaining an environmental parameter of the environment where the wind turbine generator set is located;

[0053] S1012: obtaining a measured wind speed at the current time;

[0054] S1013: performing standard wind speed conversion based on the environmental parameter and the measured wind speed to obtain a real-time standard wind speed.

[0055] Environmental factors such as temperature and air pressure have a significant impact on wind speed measurement. In order to improve the accuracy of wind speed calculation, the measured wind speed can be standardized using the following formula:

[0056] ;

[0057] wherein, is the standard conversion wind speed, is the original measured wind speed (m / s), is the current ambient temperature (in Celsius), is the standard temperature (in Celsius), P is the current air pressure (Pa), is the standard air pressure (Pa).

[0058] Herein, no limitation is imposed on how to obtain the original measured wind speed. In one possible implementation, a laser radar wind measuring instrument can be invoked to obtain the measured wind speed of the wind turbine at different heights and in different wind directions, and the equivalent wind speed of the wind wheel is calculated based on a plurality of the measured wind speeds. The laser radar wind measuring instrument is used to perform non-contact wind speed monitoring on a target region, including wind speed measurement at different heights and in different directions, and real-time feedback of data to the control system of the wind turbine. Specifically, the laser radar wind measuring instrument can be installed on the top of the nacelle of the wind turbine, to ensure that the radar can cover the area in front of the wind wheel, so as to obtain the wind speed and wind direction information in front of the wind wheel. According to the actual situation of the wind turbine, the measurement height range and the number of distance gates of the laser radar wind measuring instrument are set. For example, the measurement height can be set to a certain range from the ground to above the top of the wind wheel, and the number of distance gates can be set to several to tens according to actual application needs. The equivalent wind speed data of the wind wheel obtained by the laser radar wind measuring instrument are used as the original measured wind speed, so that the wind resources of the wind farm can be more accurately evaluated. By analyzing the equivalent wind speed distribution at different positions in the wind farm, the layout of the wind turbine can be optimized, and the best installation position of the wind turbine can be selected, so as to improve the power generation efficiency and economic benefits of the wind farm where the wind turbine is located.

[0059] Thereafter, it is necessary to further determine the wind speed standard interval corresponding to the real-time standard wind speed, and to calculate the calibration parameters of the transfer function model according to the wind speed standard interval.

[0060] Herein, no limitation is imposed on how to divide the wind speed standard interval. The division rule of the wind speed range can be determined by the person skilled in the art in advance, to provide a basis for real-time wind speed matching. According to the application scenario (such as meteorological monitoring, wind power generation, etc.) or the industry standard (such as the Beaufort wind scale, engineering specifications), the wind speed range can be divided into a plurality of continuous standard intervals.

[0061] One exemplary division can be as follows:

[0062] Interval 1: 0.0~3.0 m / s;

[0063] Interval 2: 3.0~6.0 m / s;

[0064] Interval 3: 6.0~10.0 m / s;

[0065] Interval 4: Greater than 10.0 m / s;

[0066] The calculated calibration parameters have different uses for different wind speed standard intervals.

[0067] In a feasible implementation, the following execution mode can be adopted:

[0068] If the wind speed standard interval belongs to the first wind speed interval, a low wind speed correction model is called to output a wind speed adjustment parameter;

[0069] If the wind speed standard interval belongs to the second wind speed interval, a wind speed correction model is called to output a wind speed correction parameter;

[0070] If the wind speed standard interval belongs to the third wind speed interval, a wind speed calibration model is called to output a wind speed calibration parameter with reference to the current load of the wind turbine generator.

[0071] If it belongs to the first wind speed interval, the low wind speed correction model is called, and the real-time wind speed value is input, which can optimize the system sensitivity at low wind speed and avoid misoperation caused by wind speed fluctuation.

[0072] If it belongs to the second wind speed interval, the wind speed correction model is called, the real-time wind speed value is input, and the wind speed correction parameter is output, which adopts step-by-step calibration to correct the wind speed error caused by environmental factors (such as temperature, humidity), and can correct the system response in the medium wind speed range, balance stability and efficiency.

[0073] If it belongs to the third wind speed interval, the wind speed calibration model is called, the real-time wind speed value and the current load value of the wind turbine generator are input, and the wind speed calibration parameter is output, which can calibrate the parameter in combination with the load state at high wind speed, consider the response characteristics of the wind turbine generator under different loads, ensure accurate calibration at high wind speed, and prevent overload or system out of control.

[0074] According to the real-time standard wind speed and the calibration feedback mechanism, the system dynamically adjusts the wind speed sensor to gradually approach the real wind speed. This process is realized based on an automatic algorithm, and a transfer function model of each interval is established. By introducing a multi-interval mapping function model, the wind speed reconstruction is realized by fitting the following multivariate nonlinear regression equation. The calibration wind speed can be obtained by substituting the calibration parameter and the real-time standard wind speed into the transfer function model.

[0075] In a feasible implementation, the transfer function model is:

[0076] ;

[0077] wherein, is the calibrated wind speed, is the real-time standard wind speed, T is the temperature, H is the humidity, and P is the air pressure, , , , are regression coefficients obtained by fitting, is a fitting error term.

[0078] In addition, the embedded error detection mechanism can also be used to continuously monitor abnormal situations during the calibration process. If an error occurs during the calibration process (such as data mutation, sensor failure, etc.), the parameters of the wind speed sensor will be automatically identified and adjusted to eliminate potential errors and maintain high accuracy of the sensor.

[0079] When the wind speed calibration is completed, the corrected calibrated wind speed will be transmitted to the control system of the wind turbine in real time. Through an efficient data communication link, real-time updating of wind speed information is ensured to support the optimization scheduling and load adjustment of the wind turbine by the wind farm management system.

[0080] The embodiment of the present application can dynamically determine the transfer function model calibration parameters most suitable for the current wind speed conditions by obtaining the real-time standard wind speed and matching it with the wind speed standard interval. This helps to reduce measurement errors caused by changes in wind speed, thereby improving the accuracy of the wind speed sensor measurement results. At the same time, it can adaptively adjust the calibration parameters of the transfer function model according to the changes in real-time wind speed, ensuring that the wind speed sensor can maintain stable performance under different wind speed conditions and adapt to various complex and variable environments such as meteorological observation, wind farms, etc. Using the transfer function model to calibrate the wind speed sensor can more accurately describe the input-output relationship of the sensor and better compensate for the nonlinear error and lag error of the sensor, making the calibration process more efficient and reliable, thereby further optimizing the control strategy of the wind turbine and improving the power generation efficiency.

[0081] In an executable manner of the present application, the wind speed sensor can also be dynamically calibrated, for example, using the Kalman filter algorithm to dynamically correct the measured real-time standard wind speed, real-time feedback data and automatically update the calibration parameters to ensure long-term accuracy of wind speed measurement. The specific process can be as follows:

[0082] The wind speed is regarded as the system state, and its change is assumed to conform to a linear dynamic model. The process noise is set to represent the uncertainty of the wind speed itself. The measurement noise is used to represent the statistical characteristics of the sensor measurement error. The error covariance matrix is used to reflect the uncertainty of the initial wind speed prediction value, which can be the actual measured wind speed.

[0083] First, the current wind speed is predicted according to the wind speed estimate value of the last time, and the error covariance matrix and the process noise are updated.

[0084] The wind speed measurement value of the wind speed sensor is acquired again, and the data validity of the wind speed measurement value is detected to eliminate obvious abnormal values. The Kalman gain is calculated again, the reliability between the wind speed measurement value and the wind speed prediction value is calculated, and the error covariance matrix used to reflect the corrected confidence is updated.

[0085] The measurement residual is then counted, which is the difference between the wind speed measurement value and the wind speed prediction value. If the residual significantly increases, it indicates that the measurement noise is insufficient, and the measurement noise is further increased. If the wind speed frequently changes and the filter tracks, the process noise is increased.

[0086] Finally, after adjusting the measurement noise and the process noise, the Kalman filter output is taken as the corrected wind speed and is used to replace the wind speed measurement value to participate in the calibration process of the above-embodiment.

[0087] It should be noted that the filter performance can be periodically detected, and the process noise and the measurement noise can be optimized.

[0088] Referring to Figure 2 , Figure 2 A process flow chart for applying the transfer function provided by the embodiments of the present application is provided, and the process includes:

[0089] Step one: input the impeller diameter and blade basic information, as well as temperature, humidity, air pressure and other information.

[0090] Step two: determine whether the laser radar is normal; if the laser radar is normal, continue to execute step three. If the laser radar is not normal, display a fan fault warning and end the process.

[0091] Step three: use the laser radar to obtain the equivalent wind speed of the wind wheel.

[0092] Step four: calibrate the wind speed of the wind turbine generator and determine the transfer function of the wind speed measuring instrument of the unit.

[0093] Step five: check whether the wind speed of the wind turbine generator and the equivalent wind speed of the wind wheel are less than a threshold value: if yes, continue to execute step six. If no, return to step four.

[0094] Check whether the power curve is normal: if the power curve is normal, continue to execute step six. If the power curve is not normal, return to step four.

[0095] Step six: complete the calibration and replace the transfer function.

[0096] As can be seen, by using the laser radar to obtain the equivalent wind speed of the wind wheel, the wind speed can be measured more accurately, and the calibration process ensures the accuracy of the transfer function of the wind turbine anemometer, thereby improving the overall accuracy of wind speed measurement. Step two checks whether the laser radar is working properly, which can timely discover and handle sensor failures, avoiding measurement errors caused by sensor problems. If the laser radar is not working properly, the system will display a fault warning, which helps maintenance personnel respond quickly and repair problems, reducing downtime. By calibrating and adjusting the transfer function, it can ensure that the wind turbine runs efficiently under different wind speed conditions, thereby optimizing power generation efficiency. Checking whether the power curve is normal can help identify and solve problems affecting the performance of the wind turbine, such as mechanical failure or improper control strategy. Through continuous monitoring and calibration, the integrity and consistency of wind speed data are ensured. In addition, the entire process is automatically executed, reducing the need for manual intervention and improving the convenience and efficiency of operation.

[0097] Referring to Figure 3 , Figure 3 A wind speed calibration system for a wind turbine provided by an embodiment of the present application has a structural schematic diagram, and the system comprises:

[0098] A wind speed acquisition module is configured to acquire a real-time standard wind speed at the current time.

[0099] A calibration parameter calculation module is configured to determine a wind speed standard interval corresponding to the real-time standard wind speed, and calculate calibration parameters of a transfer function model according to the wind speed standard interval.

[0100] A wind speed calibration module is configured to calibrate the wind speed of a wind speed sensor based on the calibration parameters, the real-time standard wind speed, and the transfer function model, to obtain a calibrated wind speed.

[0101] Based on the above embodiment, as a preferred embodiment, the wind speed acquisition module comprises:

[0102] A parameter acquisition unit is configured to acquire environmental parameters of an environment in which the wind turbine is located.

[0103] A measured wind speed acquisition unit is configured to acquire a measured wind speed at the current time.

[0104] A wind speed conversion unit is configured to convert a standard wind speed based on the environmental parameters and the measured wind speed, to obtain a real-time standard wind speed.

[0105] Based on the above embodiment, as a preferred embodiment, it further comprises:

[0106] The wind speed calibration module is configured to determine whether a difference between the real-time standard wind speed and a set standard wind speed interval satisfies an allowable deviation threshold; if not, to correct the real-time standard wind speed, and to determine a corresponding wind speed standard interval based on the corrected wind speed.

[0107] Based on the above embodiments, as a preferred embodiment, the measurement wind speed acquisition unit is a unit configured to perform the following steps:

[0108] The laser radar anemometer is called to acquire measurement wind speeds of the wind turbine generator set at different heights and different wind directions; and the equivalent wind speed of the wind wheel is calculated based on the measurement wind speeds.

[0109] Based on the above embodiments, as a preferred embodiment, the calibration parameter calculation module comprises:

[0110] The first calibration parameter determination unit is configured to, if the wind speed standard interval belongs to the first wind speed interval, call a low wind speed correction model to output a wind speed adjustment parameter.

[0111] The second calibration parameter determination unit is configured to, if the wind speed standard interval belongs to the second wind speed interval, call a wind speed correction model to output a wind speed correction parameter.

[0112] The third calibration parameter determination unit is configured to, if the wind speed standard interval belongs to the third wind speed interval, call a wind speed calibration model to output a wind speed calibration parameter based on a current load of the wind turbine generator set.

[0113] Based on the above embodiments, as a preferred embodiment, the wind speed calibration module is a module configured to substitute the calibration parameter and the real-time standard wind speed into a transfer function model to output a calibrated wind speed.

[0114] The present application also provides an embodiment corresponding to a computer readable storage medium. The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the method described in the above method embodiment.

[0115] It can be understood that if the method in the above embodiment is implemented in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and performs all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0116] The computer readable storage medium provided in the embodiment includes the method mentioned above, and the effects are the same as above.

[0117] The present application also provides an electronic device, referring to Figure 4 , the structural diagram of an electronic device provided by the embodiment of the present application, as Figure 4 shown, can include a processor 1410 and a memory 1420.

[0118] The processor 1410 can include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1410 can be implemented in at least one hardware form of a DSP (Digital Signal Processing), a FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 1410 can also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a CPU (Central Processing Unit). The coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 1410 can be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing the content to be displayed by the display screen. In some embodiments, the processor 1410 can also include an AI (Artificial Intelligence) processor for processing machine learning-related computing operations.

[0119] The memory 1420 can include one or more computer-readable storage media. The computer-readable storage media can be non-transitory. The memory 1420 can also include high-speed random access memory and can include nonvolatile memory, such as one or more magnetic disk storage devices, optical storage devices, flash memory devices, or other nonvolatile solid-state storage devices. In this embodiment, the memory 1420 is at least used to store the following computer programs 1421, wherein the computer programs are loaded and executed by the processor 1410, and can realize the related steps in the method executed by the electronic device side disclosed in any of the preceding embodiments. In addition, the resources stored in the memory 1420 can also include an operating system 1422, data 1423, and the like, and the storage mode can be temporary storage or permanent storage. The operating system 1422 can include Windows, Linux, Android, and the like.

[0120] In some embodiments, the electronic device can further include a display screen 1430, an input / output interface 1440, a communication interface 1450, a sensor 1460, a power supply 1470, and a communication bus 1480.

[0121] Of course, Figure 4 The structure of the electronic device shown does not constitute a limitation on the electronic device in the embodiments of the present application. In actual applications, the electronic device can include more or fewer components than those shown, or some components can be combined. Figure 4 The structure of the electronic device shown does not constitute a limitation on the electronic device in the embodiments of the present application. In actual applications, the electronic device can include more or fewer components than those shown, or some components can be combined.

[0122] The embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system provided by the embodiments, since it corresponds to the method provided by the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0123] The principles and implementation manners of the present application are described by using specific examples in this paper. The above description of the embodiments is only used to help understand the method and its core idea of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, some improvements and modifications can be made to the present application, and these improvements and modifications also fall within the protection scope of the present application.

[0124] It also needs to be explained that in the present specification, the relational terms such as first and second and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

Claims

1. A wind speed calibration method for a wind turbine generator set, characterized in that: include: Get the current real-time standard wind speed; Determining a wind speed standard interval corresponding to the real-time standard wind speed, and calculating calibration parameters of a transfer function model according to the wind speed standard interval; The wind speed sensor is calibrated based on the calibration parameters, the real-time standard wind speed, and the transfer function model to obtain a calibrated wind speed.

2. The wind speed calibration method according to claim 1, characterized in that: The obtaining of the real-time standard wind speed at the current moment includes: Obtaining environmental parameters of the environment in which the wind turbine generator set is located; Get the measured wind speed at the current moment; A standard wind speed conversion is performed based on the environmental parameters and the measured wind speed to obtain a real-time standard wind speed.

3. The wind speed calibration method according to claim 1, characterized in that: Before determining the wind speed standard interval corresponding to the real-time standard wind speed, the method further includes: Determine whether the difference between the real-time standard wind speed and the set standard wind speed range meets the allowable deviation threshold; If not, the real-time standard wind speed is calibrated, and the corresponding wind speed standard range is determined with reference to the calibrated wind speed.

4. The wind speed calibration method according to claim 2, characterized in that: Obtaining the measured wind speed at the current moment includes: Calling a laser radar anemometer to obtain the measured wind speed of the wind turbine at different heights and different wind directions; The rotor equivalent wind speed is calculated based on the plurality of measured wind speeds.

5. The wind speed calibration method according to claim 1, characterized in that: The calibration parameters of the transfer function model calculated according to the wind speed standard interval include: If the wind speed standard interval belongs to the first wind speed interval, calling the low wind speed correction model to output the wind speed adjustment parameter; If the wind speed standard interval belongs to the second wind speed interval, calling the wind speed correction model to output the wind speed correction parameter; If the wind speed standard interval belongs to the third wind speed interval, the wind speed calibration model is called to output wind speed calibration parameters with reference to the current load of the wind turbine generator set.

6. The wind speed calibration method according to claim 1, characterized in that: The wind speed sensor is calibrated based on the calibration parameter, the real-time standard wind speed, and the transfer function model to obtain the calibrated wind speed, which includes: Substitute the calibration parameters and the real-time standard wind speed into a transfer function model, and output the calibrated wind speed.

7. The wind speed calibration method according to claim 6, characterized in that: The transfer function model is: ； in, is the calibrated wind speed, is the real-time standard wind speed, T is the temperature, H is the humidity, and P is the air pressure. 、 、 、 are the regression coefficients obtained by fitting, is the fitting error term.

8. A wind speed calibration system for a wind turbine generator set, characterized in that: include: Wind speed acquisition module, used to obtain the real-time standard wind speed at the current moment; a calibration parameter calculation module, configured to determine a wind speed standard interval corresponding to the real-time standard wind speed, and calculate calibration parameters of a transfer function model according to the wind speed standard interval; The wind speed calibration module is used to calibrate the wind speed sensor based on the calibration parameters, the real-time standard wind speed and the transfer function model to obtain the calibrated wind speed.

9. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which implements the steps of the method according to any one of claims 1 to 7 when executed.

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