Wind turbine generator extreme wind condition load reduction optimization method and system

Abstract

The invention provides a wind turbine generator extreme wind condition load reduction optimization method and system, and the method comprises the steps: calculating a normal turbulent wind working condition, an extreme turbulent wind working condition and an extreme gust working condition of a wind turbine generator according to a load calculation standard of the wind turbine generator, and obtaining blade root limit load distribution results under different working conditions; according to a blade root limit load distribution result, a wind speed-blade root limit load threshold table is formulated, namely blade root limit load threshold conditions corresponding to different wind speeds are formulated, so that normal turbulent wind conditions and extreme wind conditions at specific wind speeds are distinguished; the control logic of the wind turbine generator under the extreme wind condition is optimized, that is, when the wind turbine generator is under the extreme wind condition, the actual measurement load value of the blade root is reduced by adding extra variable pitch actions; compared with the prior art, the blade root limit load under the extreme wind condition can be greatly reduced, and the safety of the wind turbine generator is improved.

Description

Technical Field

[0001] The present invention relates to the field of wind power control technology, and in particular to a method and system for optimizing load reduction of a wind turbine under extreme wind conditions. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] As the capacity of a single wind turbine continues to increase, the length, weight and swept area of ​​the turbine's impeller are also increasing. The load on the blades not only tests the safety and economy of the turbine, but also limits the development of large-scale turbines. At the same time, as the main load-bearing component of a wind turbine, the blades are connected to the pitch bearing and the hub through the blade roots. During the operation of the wind turbine, the blades are both the most complex parts to bear stress and the parts with the largest loads. Therefore, the blade root load is one of the important bases for the design of wind turbine loads. Under extreme wind conditions, the rapid changes in wind speed and direction will cause the force generated by the incoming flow to change irregularly and drastically, which will have an adverse effect on the aerodynamic characteristics, structural strength and fatigue load of the wind turbine. In particular, when the wind turbine is operating in the rated wind speed range, the blade root load surges. If it exceeds the bearing capacity of the blades, it will cause adverse consequences such as blade breakage.

[0004] The relevant patents disclosed in the prior art are as follows:

[0005] Patent CN 202010597652.3 discloses a prediction method, device and equipment for extreme wind conditions of a wind turbine, including processing wind data from a wind tower to obtain a wind data segment; predicting wind parameters of a predetermined recurrence period based on the joint probability distribution of wind speed and wind parameters in the wind data segment; and outputting the predicted wind parameters of the predetermined recurrence period; wherein the predicted wind parameters of the predetermined recurrence period specifically include: determining a reliability index of the predetermined recurrence period based on a Gaussian probability function, wherein the reliability index is associated with a first standard normal variable for wind speed values ​​and a second standard normal variable for wind parameters. The square sum of the wind parameters is calculated; the function of the wind parameters relative to the wind speed is calculated through the joint probability distribution of the first standard normal variable and the second standard normal variable; and the wind parameters of the predetermined recurrence period are predicted based on the calculated function; however, only the prediction is achieved, and the safety hazard caused by the change of blade root load under extreme wind conditions of the wind turbine cannot be solved;

[0006] Patent CN202410435754.3 discloses a method and system for optimizing load reduction during emergency shutdown of a wind turbine; a converter torque short-time support control strategy is obtained, and when the wind turbine is shut down in an emergency, the converter provides support torque for the wind turbine according to the torque short-time support control strategy to reduce the load of the wind turbine during emergency shutdown; wherein the converter torque short-time support control strategy is to increase the converter torque value to a set percentage of the rated torque, maintain it for a second set time, and then reduce it to zero according to a set descending slope. However, this patent involves an optimization method for load reduction during emergency shutdown, and cannot solve the safety hazard caused by changes in blade root loads under extreme wind conditions of wind turbines.

[0007] Patent CN204253288U discloses a wind turbine blade structure that can effectively resist extreme wind conditions such as typhoons. This patent effectively avoids damage to the blades and the unit caused by extreme wind conditions such as typhoons by changing the blade structure of the wind turbine. However, this method is costly and requires changing the existing blade structure to solve the problem.

[0008] In summary, there is no feasible method in the prior art to solve the potential safety hazard caused by the change of blade root load of wind turbines under extreme wind conditions. Summary of the invention

[0009] In order to solve the above problems, the present invention proposes a method and system for optimizing load reduction in extreme wind conditions for wind turbines. The present invention intends to solve the problem of excessive blade root load when a wind turbine encounters extreme gust conditions or extreme turbulent winds. By installing a blade root load sensor (or other sensors that can directly or indirectly obtain the blade root load), real-time monitoring of the blade root load of the wind turbine is performed. By performing data processing and analysis on the measured load, additional blade retraction instructions and protection actions are applied to achieve load reduction of the wind turbine blades, thereby improving the reliability and service life of the wind turbine.

[0010] According to some embodiments, in a first aspect, a solution of the present invention provides a method for optimizing load reduction of a wind turbine in extreme wind conditions, which adopts the following technical solution:

[0011] Step 1: According to the current wind resource parameters of the unit and related standards, obtain the wind speed and three-blade root limit load distribution results of normal turbulent wind conditions and extreme wind conditions;

[0012] Step 2: determining the relationship between wind speed and blade root limit load threshold according to the distribution result;

[0013] Step 3, obtain the real-time wind speed signal and the measured signal of the blade root load, and obtain the corresponding blade root limit load threshold according to the relationship between the wind speed and the blade root limit load threshold; compare the measured signal of the blade root load with the set multiple of the blade root limit load threshold. If the measured signal of the blade root load is greater than the set multiple of the blade root limit load threshold, solve the corresponding additional pitch angle compensation value. If the set conditions are met, the compensation value is superimposed on the original pitch setting value. If the set conditions are not met, the pitch setting value remains unchanged. If the measured signal of the blade root load is less than or equal to the set multiple of the blade root limit load threshold, the pitch setting value remains unchanged.

[0014] As a further technical solution, the extreme wind conditions include extreme turbulent wind conditions and extreme gust conditions.

[0015] As a further technical solution, the set multiple is greater than 0 and less than or equal to 1.

[0016] As a further technical solution, the setting conditions are:

[0017] Determine the relationship between the pitch angle setting threshold, the power setting threshold, the actual pitch angle value, and the average power value; if the actual pitch angle value > the pitch angle setting threshold and the average power value > the power setting threshold, correct the corresponding variable pitch setting value; otherwise, the variable pitch setting value remains unchanged.

[0018] In a second aspect, the present invention further provides a wind turbine generator set load reduction optimization system under extreme wind conditions, as follows:

[0019] Module 1 is configured to obtain wind speed and three-blade root limit load distribution results of normal turbulent wind conditions and extreme wind conditions according to the current wind resource parameters of the unit and related standards;

[0020] Module 2 is configured to determine the relationship between wind speed and blade root limit load threshold according to the distribution result;

[0021] Module three is configured to obtain real-time wind speed signals and measured signals of blade root load, and obtain the corresponding blade root limit load threshold according to the relationship between wind speed and blade root limit load threshold; compare the measured signal of blade root load with the set multiple of blade root limit load threshold, if the measured signal of blade root load is greater than the set multiple of blade root limit load threshold, solve the corresponding additional pitch angle compensation value, if the set conditions are met, then the compensation value is superimposed on the original variable pitch setting value, if the set conditions are not met, then the variable pitch setting value remains unchanged; if the measured signal of blade root load is less than or equal to the set multiple of blade root limit load threshold, then the variable pitch setting value remains unchanged.

[0022] As a further technical solution, the extreme wind conditions include extreme turbulent wind conditions and extreme gust conditions.

[0023] As a further technical solution, the set multiple is greater than 0 and less than or equal to 1.

[0024] As a further technical solution, the setting conditions are:

[0025] Determine the relationship between the pitch angle setting threshold, the power setting threshold, the actual pitch angle value, and the average power value; if the actual pitch angle value > the pitch angle setting threshold and the average power value > the power setting threshold, correct the corresponding variable pitch setting value; otherwise, the variable pitch setting value remains unchanged.

[0026] In a third aspect, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the method for optimizing load reduction in extreme wind conditions for a wind turbine.

[0027] In a fourth aspect, the present invention further provides a computer-readable storage medium, characterized in that it is used to store computer instructions, and when the computer instructions are executed by a processor, the steps of the wind turbine generator set extreme wind condition load reduction optimization method are completed.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. In a method for optimizing load reduction under extreme wind conditions for a wind turbine set proposed in the present invention, firstly, according to the load calculation standard of the wind turbine set, the normal turbulent wind condition, the extreme turbulent wind condition and the extreme gust condition of the computer group are calculated to obtain the distribution results of the blade root limit load under different conditions; the normal turbulent wind condition, the extreme turbulent wind condition and the extreme gust condition of the computer group are calculated to obtain the distribution results of the blade root limit load under different conditions; according to the blade root limit load distribution results, a wind speed-blade root limit load threshold table is formulated, that is, the blade root limit load threshold conditions corresponding to different wind speeds, so as to distinguish between normal turbulent wind conditions and extreme wind conditions under specific wind speeds. Conditions; Optimize the control logic of wind turbines under extreme wind conditions, that is, when the wind turbine is in extreme wind conditions, add additional pitch action to reduce the measured load value of the blade root; This method does not require the replacement of the blade structure, but optimizes the control logic of wind turbines under extreme wind conditions through the change of blade root load, that is, when the wind turbine is in extreme wind conditions, add additional pitch action to reduce the measured load value of the blade root; By monitoring the change of blade root load, timely discover and handle faults caused by excessive load or imbalance, reduce the failure rate of wind turbines, avoid the occurrence of serious accidents, and ensure the long-term stable operation of wind turbines. The blade root limit load under extreme wind conditions can be greatly reduced, thereby improving the safety of wind turbines.

[0030] 2. The method described in the present invention is simple to operate and easy to implement, and can improve the reliability of the unit.

[0031] 3. The method described in the present invention can reduce the weight of wind turbine blades, assist in the lightweight design of the unit, and meet the development needs of the industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0033] Figure 1 It is a flow chart of a method for optimizing load reduction of a wind turbine set under extreme wind conditions as described in Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0034] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0035] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0036] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0037] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0038] This embodiment provides a method for optimizing load reduction of a wind turbine in extreme wind conditions, which adopts the following technical solutions:

[0039] Step 1: According to the current wind resource parameters of the wind turbine and related standards, obtain the blade root limit load distribution results of the wind turbine under normal turbulent wind conditions and extreme wind conditions;

[0040] Step 2: Determine the relationship between wind speed and blade root limit load threshold value according to the blade root limit load distribution result;

[0041] Step 3, obtain the real-time wind speed signal and the measured signal of the blade root load, and obtain the corresponding blade root limit load threshold according to the relationship between the wind speed and the blade root limit load threshold; compare the measured signal of the blade root load with the set multiple of the blade root limit load threshold. If the measured signal of the blade root load is greater than the set multiple of the blade root limit load threshold, solve the corresponding additional pitch angle compensation value. If the set conditions are met, the compensation value is superimposed on the original pitch setting value. If the set conditions are not met, the pitch setting value remains unchanged. If the measured signal of the blade root load is less than or equal to the set multiple of the blade root limit load threshold, the pitch setting value remains unchanged.

[0042] The above-mentioned wind turbine load reduction optimization method for extreme wind conditions does not require the replacement of the blade structure, but optimizes the control logic of the wind turbine under extreme wind conditions through the change of the blade root load, that is, when the wind turbine is in extreme wind conditions, additional pitch change actions are added to reduce the measured load value of the blade root; by monitoring the change of the blade root load, faults caused by excessive or unbalanced loads can be discovered and handled in time, the failure rate of the wind turbine can be reduced, the occurrence of serious accidents can be avoided, and the long-term stable operation of the wind turbine can be ensured. The blade root limit load under extreme wind conditions can be greatly reduced, thereby improving the safety of the wind turbine.

[0043] Embodiment 1

[0044] This embodiment provides a method for optimizing load reduction under extreme wind conditions for a wind turbine. When a wind turbine encounters extreme wind conditions, the blade root limit load Mx and the blade root limit load My (where x and y refer to the directions defined in the blade coordinate system in the IEC61400 standard) appear at extreme values, and the blade root limit load Mxy formed by the two also appears at extreme values. Mxy is directly related to the bearing capacity of the blade under extreme conditions and is an important parameter that reflects whether the wind turbine can operate safely under complex working conditions. Therefore, this implementation case takes the blade root limit load Mxy as an example for explanation, including:

[0045] According to the current wind resource parameters of the unit and the IEC 61400-1-2019 standard, calculate the normal turbulent wind condition dlc1.2, the extreme turbulent wind condition dlc1.3 and the extreme gust condition dlc1.5;

[0046] According to the load calculation results, the wind speed and the three-blade root limit load Mxy distribution results of the normal turbulent wind condition dlc1.2, the extreme turbulent wind condition dlc1.3 and the extreme gust condition dlc1.5 are statistically analyzed;

[0047] According to the wind speed and the load distribution results of the three-blade root limit load Mxy, a blade root limit load threshold table T under different wind speeds is formulated;

[0048] The real-time wind speed signal v obtained (specifically, it can be obtained by wind measuring radar or estimated wind speed) and the three-blade root load measured signal Mxy i(Specifically, it can be indirectly obtained by a blade root load sensor or other sensors, where i=0, 1, 2, representing three blades of the wind turbine generator set);

[0049] The real-time wind speed signal v is obtained by looking up the table T to obtain the corresponding blade root limit load threshold Mxy_Thres;

[0050] The measured value of the three-blade root load Mxy i The value is filtered to obtain the filtered blade root limit load Mxy_Filt i ;

[0051] Compare with Mxy_Filt i and K times the blade root limit load threshold, i.e. K×Mxy_Thtes, where 0<K≤1;

[0052] If Mxy_Filt i If it is greater than K×Mxy_Thres, the corresponding additional pitch angle compensation value is solved;

[0053] If the measured pitch angle and power at this time meet the set start-up conditions, the compensation value is added to the original variable pitch setting value; if the measured pitch angle and power at this time do not meet the start-up conditions, the variable pitch setting value remains unchanged;

[0054] If Mxy_Filt i If it is not greater than K*Mxy_Thres, the pitch setting value remains unchanged.

[0055] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Figure 1 As shown, it mainly includes the following steps:

[0056] S1: According to the current wind resource parameters of the unit and the IEC 61400-1-2019 standard, calculate the normal turbulent wind condition dlc1.2, the extreme turbulent wind condition dlc1.3 and the extreme gust condition dlc1.5.

[0057] S2: Based on the load calculation results in S1, the wind speed and blade root limit load Mxy distribution results of the normal turbulent wind condition dlc1.2, the extreme turbulent wind condition dlc1.3 and the extreme gust condition dlc1.5 are statistically analyzed.

[0058] S3: According to the wind speed-blade root load distribution results in S2, a blade root limit load threshold table T under different wind speeds is formulated, as shown in Table 1, in which a linear interpolation method is used between two consecutive wind speeds.

[0059] Table 1. Threshold values ​​of blade root limit load Mxy at different wind speeds

[0060]

[0061] S4: The real-time wind speed signal v (obtained by wind radar or estimated wind speed) and the measured signal Mxy of the three-blade root load i (Indirectly acquired by blade root load sensor or other sensors);

[0062] S5: Obtain the corresponding blade root limit load threshold Mxy_Thres by looking up the table T for the real-time wind speed signal v;

[0063] S6: The measured value of blade root load Mxy i The value is filtered to obtain the filtered blade root limit load Mxy_Filt i ;

[0064] S7: Comparison with Mxy_Filt i and K times the blade root limit load threshold, that is, K*Mxy_Thres, if Mxy_Filt i >K*Mxy_Thres (where 0<K≤1), then

[0065] (a) Calculation of Mxy_Filt i The difference between K*Mxy_Thres and K*Mxy_Thres is used to obtain the three-blade root load deviation value Mxy_error i ;

[0066] (b) The three-blade root load deviation value Mxy_error i Enter the PID controller (or other controller);

[0067] (c) The PID controller obtains the corresponding three pitch compensation signals β i ;

[0068] (d) setting a pitch angle setting threshold β_Thres and a power setting threshold P_Thres;

[0069] (e) Obtain the measured value β of the pitch angle and the 30-second average power value P (in order to prevent frequent pitch changes of the unit, it is recommended to use the average power, and the 30-second average power is taken as an example here);

[0070] (f) If β>β_Thres and P>P_Thres, then correct the corresponding pitch setting value β demand , that is, β demand =β demand +β i ;

[0071] (g) If the condition in (f) is not met, the pitch setting value remains unchanged, that is, β demand =β demand ;

[0072] S8: Comparison with Mxy_Filti and K times the blade root limit load threshold, that is, K*Mxy_Thres, if Mxy_Filt i ≤K*Mxy_Thres (where 0<K≤1), the pitch setting value remains unchanged, that is, β demand =β demand .

[0073] In the above-mentioned wind turbine load reduction optimization method under extreme wind conditions, according to the wind turbine load calculation standard, such as the IEC-1-61400 standard, the normal turbulent wind condition dlc1.2, the extreme turbulent wind condition dlc1.3 and the extreme gust condition dlc1.5 of the computer group are calculated to obtain the blade root limit load distribution results under different conditions; according to the blade root limit load distribution results, a wind speed-blade root limit load threshold table is formulated, that is, the blade root limit load threshold conditions corresponding to different wind speeds, so as to distinguish normal turbulent wind conditions and extreme wind conditions under specific wind speeds; optimize the wind turbine load reduction optimization method under extreme wind conditions. The control logic under extreme wind conditions is optimized by adding additional pitch-changing actions to reduce the measured load value of the blade root when the wind turbine is in extreme wind conditions. This method does not require the replacement of the blade structure, but optimizes the control logic of the wind turbine under extreme wind conditions through the change of the blade root load. That is, when the wind turbine is in extreme wind conditions, additional pitch-changing actions are added to reduce the measured load value of the blade root. By monitoring the change of the blade root load, faults caused by excessive load or imbalance can be discovered and handled in time, the failure rate of the wind turbine can be reduced, the occurrence of serious accidents can be avoided, and the long-term stable operation of the wind turbine can be ensured. The blade root limit load under extreme wind conditions can be greatly reduced, thereby improving the safety of the wind turbine.

[0074] Embodiment 2

[0075] Furthermore, this embodiment also provides another wind turbine load reduction optimization system under extreme wind conditions, which is as follows: comprising module one, module two and module three;

[0076] Module 1 is configured to obtain the blade root limit load distribution results of the wind turbine under normal turbulent wind conditions and extreme wind conditions according to the current wind resource parameters of the turbine and related standards;

[0077] Module 2, configured to determine the relationship between the wind speed and the blade root limit load threshold according to the blade root limit load distribution result;

[0078] Module three is configured to obtain real-time wind speed signals and blade root load measured signals, and obtain the corresponding blade root load threshold according to the relationship between wind speed and blade root load threshold; compare the blade root load measured signal with the set multiple of the blade root load threshold, if the blade root load measured signal is greater than the set multiple of the blade root load threshold, solve the corresponding additional pitch angle compensation value, and add the compensation value to the original pitch setting value; if the blade root load measured signal is less than or equal to the set multiple of the blade root load threshold, the pitch setting value remains unchanged.

[0079] As a further technical solution, the extreme wind conditions include extreme turbulent wind conditions dlc1.3 and extreme gust conditions dlc1.5;

[0080] As a further technical solution, the set multiple is greater than 0 and less than or equal to 1, that is, corresponding to the above-mentioned K, where 0<K≤1;

[0081] As a further technical solution, the setting conditions are:

[0082] Determine the relationship between the pitch angle setting threshold, the power setting threshold, the actual pitch angle value, and the average power value; if the actual pitch angle value is greater than the pitch angle setting threshold and the 30s average power value is greater than the power setting threshold, correct the corresponding variable pitch setting value; otherwise, the variable pitch setting value remains unchanged.

[0083] The specific implementation method of the wind turbine extreme wind condition load reduction optimization system provided in this embodiment can be found in the wind turbine extreme wind condition load reduction optimization method provided in the embodiment of the present disclosure, and will not be repeated here.

[0084] Embodiment 3

[0085] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the method for optimizing load reduction of a wind turbine under extreme wind conditions described in the first embodiment.

[0086] Among them, the memory and the processor are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and memories together. The bus can also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are all well known in the art, and therefore, this embodiment will not be further described. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor is transmitted on a wireless medium through an antenna, and further, the antenna also receives data and transmits the data to the processor.

[0087] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory can be used to store data used by the processor when performing operations.

[0088] For details, please refer to the optimization method for load reduction of wind turbines under extreme wind conditions provided in Example 1, which will not be described in detail here.

[0089] Embodiment 4

[0090] This embodiment also provides a computer-readable storage medium for storing computer instructions, and when the computer instructions are executed by the processor, the steps of the wind turbine extreme wind condition load reduction optimization method are completed. That is, those skilled in the art can understand that all or part of the steps in the method described in the above-mentioned embodiment can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including a number of instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0091] For details, please refer to the optimization method for load reduction of wind turbines under extreme wind conditions provided in Example 1, which will not be described in detail here.

[0092] Embodiment 5

[0093] In a fourth aspect, the present invention further provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the method for optimizing load reduction of a wind turbine under extreme wind conditions described in Example 1; these steps will not be described in detail here.

[0094] Although the above describes the specific implementation methods of the present disclosure in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present disclosure. Technical personnel in the relevant field should understand that on the basis of the technical solution of the present disclosure, various modifications or variations that can be made by those skilled in the art without creative work are still within the scope of protection of the present disclosure.

Claims

1. A method for optimizing load reduction of a wind turbine in extreme wind conditions, characterized in that: as follows: Step 1: According to the current wind resource parameters of the unit and related standards, obtain the wind speed and three-blade root limit load distribution results of normal turbulent wind conditions and extreme wind conditions; Step 2: determining the relationship between wind speed and blade root limit load threshold according to the distribution result; Step 3, obtain the real-time wind speed signal and the measured signal of the blade root load, and obtain the corresponding blade root limit load threshold according to the relationship between the wind speed and the blade root limit load threshold; compare the measured signal of the blade root load with the set multiple of the blade root limit load threshold. If the measured signal of the blade root load is greater than the set multiple of the blade root limit load threshold, solve the corresponding additional pitch angle compensation value. If the set conditions are met, the compensation value is superimposed on the original pitch setting value. If the set conditions are not met, the pitch setting value remains unchanged. If the measured signal of the blade root load is less than or equal to the set multiple of the blade root limit load threshold, the pitch setting value remains unchanged.

2. The method for optimizing load reduction of a wind turbine in extreme wind conditions according to claim 1, characterized in that: The extreme wind conditions include extreme turbulent wind conditions and extreme gust conditions.

3. The method for optimizing load reduction of a wind turbine in extreme wind conditions according to claim 1, characterized in that: The setting multiple is greater than 0 and less than or equal to 1.

4. The method for optimizing load reduction of a wind turbine in extreme wind conditions according to claim 1, characterized in that: The setting conditions are: Determine the relationship between the pitch angle setting threshold, the power setting threshold, the actual pitch angle value, and the average power value; if the actual pitch angle value > the pitch angle setting threshold and the average power value > the power setting threshold, correct the corresponding variable pitch setting value; otherwise, the variable pitch setting value remains unchanged.

5. A wind turbine load reduction optimization system for extreme wind conditions, characterized in that: as follows: Module 1 is configured to obtain wind speed and three-blade root limit load distribution results of normal turbulent wind conditions and extreme wind conditions according to the current wind resource parameters of the unit and related standards; Module 2 is configured to determine the relationship between wind speed and blade root limit load threshold according to the distribution result; Module three is configured to obtain real-time wind speed signals and measured signals of blade root load, and obtain the corresponding blade root limit load threshold according to the relationship between wind speed and blade root limit load threshold; compare the measured signal of blade root load with the set multiple of blade root limit load threshold, if the measured signal of blade root load is greater than the set multiple of blade root limit load threshold, solve the corresponding additional pitch angle compensation value, if the set conditions are met, then the compensation value is superimposed on the original variable pitch setting value, if the set conditions are not met, then the variable pitch setting value remains unchanged; if the measured signal of blade root load is less than or equal to the set multiple of blade root limit load threshold, then the variable pitch setting value remains unchanged.

6. The wind turbine load reduction optimization system for extreme wind conditions according to claim 5, characterized in that: The extreme wind conditions include extreme turbulent wind conditions and extreme gust conditions.

7. The wind turbine load reduction optimization system for extreme wind conditions according to claim 5, characterized in that: The setting multiple is greater than 0 and less than or equal to 1.

8. The wind turbine load reduction optimization system for extreme wind conditions according to claim 5, characterized in that: The setting conditions are: Determine the relationship between the pitch angle setting threshold, the power setting threshold, the actual pitch angle value, and the average power value; if the actual pitch angle value > the pitch angle setting threshold and the average power value > the power setting threshold, correct the corresponding variable pitch setting value; otherwise, the variable pitch setting value remains unchanged.

9. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of the method according to any one of claims 1 to 4.

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