An anemometry correction system for a wind turbine

Abstract

This application relates to the technical field of wind turbines, and in particular to a wind measurement correction system for wind turbines. It includes: a deviation correction unit for obtaining the wind measurement sub-module parameters of each wind turbine and establishing a wind measurement sub-module sequence A, A = (a1, a2…an), where ai is the wind measurement sub-module on the i-th wind turbine and n is the number of wind measurement sub-modules; an anchoring unit for generating anchoring data; a central control unit for selecting a target wind measurement sub-module, setting the synchronous correction data acquisition parameters for the target wind measurement sub-module and the anchoring unit, and generating a synchronous correction data packet; the central control unit is also used to generate a wind speed correction model for the target wind measurement sub-module. A multi-variable coupling model is established based on the difference relationship between the collected data and the anchoring data to correct the data collected by the wind measurement sub-module of the wind turbine, improve the wind measurement accuracy, reduce the wind measurement error, and thus enhance the power generation efficiency and safety performance of the generator set.

Description

Technical Field

[0001] This application relates to the technical field of wind turbines, and particularly to an anemometry correction system for wind turbines. Background Art

[0002] At present, the power adjustment of wind turbines in operation mainly depends on the anemometry data of the anemometry devices of the wind turbines. However, due to the relatively simple structure of the anemometry devices and the influence of various working conditions on the sensor accuracy, the anemometry accuracy is insufficient, which is likely to cause the following impacts: inaccurate power control: the MPPT efficiency decreases: inaccurate wind speed measurement means that it is impossible to accurately judge the optimal tip speed ratio (TSR) corresponding to the current wind condition, resulting in a weakened effect of the maximum power point tracking (MPPT) algorithm and a reduced power generation efficiency.

[0003] Deviation in performance evaluation and inaccurate power curve analysis: The wind speed measurement error will cause the actually recorded wind speed data to not match the actual wind condition, making the power curve calculated based on these data unable to truly reflect the performance of the unit. This not only affects the unit performance evaluation but also hinders the correct diagnosis of the health status and potential faults of the wind turbines. Economic benefit loss, reduced power generation and increased operation and maintenance costs: Inaccurate wind speed measurement directly leads to a decrease in power generation efficiency, a reduction in power generation, and failure to meet the power generation requirements of the grid side, resulting in assessment and thus affecting the project revenue. At the same time, due to possible misoperations, fault shutdowns, premature maintenance or component replacements, etc., the operation and maintenance costs will also increase accordingly. Summary of the Invention

[0004] The objective of this application is: To solve the above technical problems, this application provides an anemometry correction system for wind turbines, aiming to reduce the anemometry error of the anemometry device, improve the power generation efficiency and safety performance of the wind turbines, and increase the project revenue.

[0005] In some embodiments of this application, by adding an anchoring unit, synchronous anemometry is performed using the anchoring unit and the anemometry sub-module on the wind turbine at typical positions in the wind farm, and by establishing a sequence of working condition categories, the parameter differences between the two under different working conditions are monitored. According to the difference relationship between the collected data and the anchored data, a multi-variable coupling model is established to correct the data collected by the anemometry sub-module of the wind turbine, improve the anemometry accuracy, reduce the anemometry error, and thus improve the power generation efficiency and safety performance of the generator set.

[0006] In some embodiments of this application, by adding a first correction module and a second correction module, the improvement of the power generation of the corrected anemometry sub-module is judged, and a suitable overall correction plan is formulated. While improving the power generation efficiency, the correction cost is minimized as much as possible, and the working condition categories are continuously refined to update the wind speed correction model, thereby improving the correction accuracy.

[0007] In some embodiments of the present application, a wind measurement correction system for a wind turbine is provided, including:

[0008] A deviation correction unit, configured to obtain the wind measurement sub-module parameters of each wind turbine and establish a wind measurement sub-module sequence A, A = (a1, a2... an), where ai is the wind measurement sub-module on the i-th wind turbine and n is the number of wind measurement sub-modules;

[0009] An anchoring unit, configured to generate anchoring data;

[0010] A central control unit, configured to select a target wind measurement sub-module, set the synchronous correction data acquisition parameters for the target wind measurement sub-module and the anchoring unit, and generate a synchronous correction data packet;

[0011] The central control unit is further configured to generate a wind speed correction model for the target wind measurement sub-module according to the synchronous correction data packet.

[0012] In some embodiments of the present application, the central control unit includes:

[0013] A first evaluation module, configured to generate the operation evaluation values of each wind measurement sub-module and establish an operation evaluation value sequence B, B = (b1, b2... bn), where bi is the operation evaluation value of the i-th wind measurement sub-module;

[0014] The first evaluation module is further configured to set the wind measurement sub-module corresponding to the minimum value in the operation evaluation value sequence B as the target wind measurement sub-module.

[0015] In some embodiments of the present application, when generating the operation evaluation values of each wind measurement sub-module, it includes:

[0016] Sequentially set ai as the wind measurement sub-module to be evaluated;

[0017] Obtain the historical maintenance frequency of the wind measurement sub-module to be evaluated and the operation efficiency of the corresponding wind turbine;

[0018] Generate a first reference evaluation value H1 of the wind measurement sub-module to be evaluated according to the historical maintenance frequency;

[0019] Generate a second reference evaluation value H2 of the sub-module to be evaluated according to the operation efficiency of the wind turbine, and generate the operation evaluation value b of the wind measurement sub-module to be evaluated;

[0020] b = e1 * H1 + e2 * H2.

[0021] In some embodiments of the present application, the central control unit further includes:

[0022] A first processing module, configured to set a working condition category sequence C, C = (c1, c2... c m )), where c iis the i-th type of working condition, and m is the number of working condition categories;

[0023] A second processing module, configured to obtain a first wind speed curve collected by an anchoring unit and a second wind speed curve collected by a target anemometry sub-module;

[0024] A third processing module, configured to establish a time axis and align the first wind speed curve and the second wind speed curve based on time scales;

[0025] The third processing module is further configured to establish a plurality of time intervals according to the working condition category sequence C and establish a time interval - working condition category mapping table;

[0026] The third processing module is further configured to generate wind speed differences for each time interval and establish a wind speed difference sequence F, F = (f1, f2... f α ); f i is the wind speed difference for the i-th time interval, and α is the number of time intervals;

[0027] A fourth processing module, configured to establish a time interval - working condition category mapping table and generate a synchronization correction data packet according to the time interval - working condition category mapping table and the wind speed difference sequence F;

[0028] The fourth processing module is further configured to establish a wind speed correction model for the target anemometry sub-module.

[0029] In some embodiments of the present application, the fourth processing module is further configured to:

[0030] Establish a plurality of sub-correction models according to the synchronization correction data packet;

[0031] Establish a sub-correction model sequence D, D = (d1, d2... d m ), where d i is the sub-correction model corresponding to the i-th working condition category;

[0032] Establish a judgment model, and the judgment model determines the sub-correction model to be retrieved according to the real-time working condition parameters of the target anemometry sub-module;

[0033] Correct the wind speed parameters collected by the target anemometry sub-module according to the retrieved sub-correction model;

[0034] Construct a wind speed correction model for the target anemometry sub-module according to the judgment model and all sub-correction models.

[0035] In some embodiments of the present application, when determining the sub-correction model to be retrieved, it includes:

[0036] The judgment model establishes a working condition evaluation index sequence J according to the real-time working condition parameters of the target anemometry sub-module, J = (j1, j2... j m1 ), where m1 is the number of working condition evaluation indexes, ji is the real-time reference value of the i-th working condition evaluation index of the target wind measurement sub-module;

[0037] Set ci as the target working condition category in sequence according to the working condition category sequence C;

[0038] Generate the similarity evaluation value k of the real-time working condition parameters and the target working condition category of the target wind measurement sub-module

[0039]

[0040] where j i ' is the reference value of the i-th working condition evaluation index of the target working condition category, βi is the influence factor of the i-th working condition evaluation index; Q is a fixed coefficient;

[0041] Establish a similarity evaluation value sequence K, K=(k1, k2…k m ), where k i is the similarity evaluation value of the real-time working condition parameters of the target wind measurement sub-region and the i-th working condition category;

[0042] Preset a similarity evaluation value threshold K1;

[0043] If k i > K1, call the i-th sub-correction model.

[0044] In some embodiments of the present application, the central control unit further includes:

[0045] A first correction module, which obtains the gain percentage g of the wind turbine corresponding to the target wind measurement sub-module according to the preset feedback time node;

[0046] The first correction module is further used to preset a first gain percentage threshold G1 and a second gain percentage threshold G2, and G1 < G2;

[0047] If g < G1, the first correction module generates a first-level correction instruction;

[0048] If G1 ≤ g ≤ G2, the first correction module generates a second-level correction instruction;

[0049] If g > G2, the first correction module generates a third-level correction instruction, and the central control unit constructs a wind speed correction model for all wind measurement sub-modules according to the third-level correction instruction.

[0050] In some embodiments of the present application, the first correction module is further used for:

[0051] Correct the working condition category sequence C according to the first-level correction instruction;

[0052] Update the wind speed correction model of the target wind measurement sub-module according to the correction result, obtain the gain percentage g1 of the wind turbine, and generate a correction instruction.

[0053] In some embodiments of the present application, the central control unit further includes:

[0054] A second correction module, configured to select the wind measurement sub-module to be corrected according to the secondary correction instruction and the operation evaluation value sequence B, B=(b1, b2…bn), and establish a wind speed correction model for all the wind measurement sub-modules to be corrected;

[0055] The second correction module is further configured to set a first operation evaluation value threshold B1 according to the gain percentage g;

[0056] If bi < B1, the second correction module sets the i-th wind measurement sub-module as the wind measurement sub-module to be corrected.

[0057] Compared with the prior art, the wind measurement correction system for a wind turbine in the embodiments of the present application has the beneficial effects that:

[0058] By adding an anchoring unit, synchronous wind measurement is performed between the anchoring unit and the wind measurement sub-module on the wind turbine at typical positions in the wind farm, and by establishing a working condition category sequence, the parameter differences between the two under different working conditions are monitored. According to the difference relationship between the collected data and the anchored data, a multi-variable coupling model is established to correct the data collected by the wind measurement sub-module of the wind turbine, improve the wind measurement accuracy, reduce the wind measurement error, and thus improve the power generation efficiency and safety performance of the generator set.

[0059] By adding a first correction module and a second correction module, the improvement of the power generation of the corrected wind measurement sub-module is judged, and a suitable overall correction plan is formulated. While improving the power generation efficiency, the correction cost is minimized as much as possible, and the working condition category is continuously refined to update the wind speed correction model, thereby improving the correction accuracy. Description of the Drawings

[0060] Figure 1 is a schematic structural diagram of a wind measurement correction system for a wind turbine in a preferred embodiment of the embodiments of the present application. Detailed Embodiments

[0061] The following further describes in detail the specific embodiments of the present application with reference to the drawings and embodiments. The following embodiments are used to illustrate the present application, but are not used to limit the scope of the present application.

[0062] In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present application.

[0063] The terms "first" and "second" are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0064] In the description of the present application, it should be noted that unless otherwise clearly specified and limited, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0065] As Figure 1 shown, a wind measurement correction system for a wind turbine in a preferred embodiment of the present application includes:

[0066] A deviation correction unit, configured to obtain the parameters of the wind measurement sub-modules of each wind turbine and establish a wind measurement sub-module sequence A, A = (a1, a2... an), where ai is the wind measurement sub-module on the i-th wind turbine and n is the number of wind measurement sub-modules;

[0067] An anchoring unit, configured to generate anchoring data;

[0068] A central control unit, configured to select a target wind measurement sub-module, set the synchronous correction data acquisition parameters for the target wind measurement sub-module and the anchoring unit, and generate a synchronous correction data packet;

[0069] The central control unit is further configured to generate a wind speed correction model for the target wind measurement sub-module according to the synchronous correction data packet.

[0070] Specifically, the wind measurement sub-module is a wind measurement device installed on the wind turbine.

[0071] Specifically, the anchoring unit is a lidar. The data of the lidar is synchronized with reference to the anemometer tower in the wind field, and then synchronized wind measurement is carried out with the target anemometer sub-module in each typical area in the wind field. The anchoring data is generated according to the wind speed data collected by the lidar, and a multi-variable coupling model is established based on the difference relationship between the data collected by the target anemometer sub-module and the anchoring data.

[0072] Specifically, the central control unit includes:

[0073] The first evaluation module is used to generate the operation evaluation values of each anemometer sub-module and establish an operation evaluation value sequence B, B = (b1, b2... bn), where bi is the operation evaluation value of the i-th anemometer sub-module;

[0074] The first evaluation module is also used to set the anemometer sub-module corresponding to the minimum value in the operation evaluation value sequence B as the target anemometer sub-module.

[0075] Specifically, when generating the operation evaluation values of each anemometer sub-module, it includes:

[0076] Set ai as the to-be-evaluated anemometer sub-module in sequence;

[0077] Obtain the historical maintenance frequency of the to-be-evaluated anemometer sub-module and the operation efficiency of the corresponding wind turbine;

[0078] Generate the first reference evaluation value H1 of the to-be-evaluated anemometer sub-module according to the historical maintenance frequency;

[0079] Generate the second reference evaluation value H2 of the to-be-evaluated sub-module according to the operation efficiency of the wind turbine, and generate the operation evaluation value b of the to-be-evaluated anemometer sub-module;

[0080] b = e1 * H1 + e2 * H2.

[0081] Specifically, the value ranges of the first reference evaluation value and the second reference evaluation value are the same. The smaller the historical maintenance frequency, the larger the corresponding first reference evaluation value. The greater the operation efficiency of the wind turbine, the larger the corresponding second reference evaluation value. The lower the operation evaluation value of the anemometer sub-module, the lower the accuracy of the wind speed data collected by the current anemometer sub-module, and the worse the operation efficiency of the corresponding wind turbine.

[0082] In the preferred embodiment of this application, the central control unit further includes:

[0083] The first processing module is used to set a working condition category sequence C, C = (c1, c2... c m ), where c i is the i-th type of working condition, and m is the number of working condition categories;

[0084] A second processing module, configured to obtain a first wind speed curve collected by an anchoring unit and a second wind speed curve collected by a target wind measurement sub-module;

[0085] A third processing module, configured to establish a time axis and align the first wind speed curve and the second wind speed curve based on time scales;

[0086] The third processing module is further configured to establish a plurality of time intervals according to the working condition category sequence C and establish a time interval - working condition category mapping table;

[0087] The third processing module is further configured to generate wind speed differences for each time interval and establish a wind speed difference sequence F, F = (f1, f2... f α ); f i is the wind speed difference for the i-th time interval, and α is the number of time intervals;

[0088] A fourth processing module, configured to establish a time interval - working condition category mapping table and generate a synchronization correction data packet according to the time interval - working condition category mapping table and the wind speed difference sequence F;

[0089] The fourth processing module is further configured to establish a wind speed correction model for the target wind measurement sub-module.

[0090] Specifically, the fourth processing module is further configured to:

[0091] Establish a plurality of sub-correction models according to the synchronization correction data packet;

[0092] Establish a sub-correction model sequence D, D = (d1, d2... d m ), where di is the sub-correction model corresponding to the i-th working condition category;

[0093] Establish a judgment model, and the judgment model determines the sub-correction model to be retrieved according to the real-time working condition parameters of the target wind measurement sub-module;

[0094] Correct the wind speed parameters collected by the target wind measurement sub-module according to the retrieved sub-correction model;

[0095] Construct a wind speed correction model for the target wind measurement sub-module according to the judgment model and all sub-correction models.

[0096] Specifically, the number of its time intervals is much larger than the number of working condition categories. By establishing a time interval - working condition category mapping table, setting the working condition category corresponding to each time interval, and summarizing the data of the same working condition category, the difference relationship between the collected data and the anchored data under each working condition category is obtained. Thus, a multi-variable coupling model under each working condition category is constructed, and then a wind speed correction model for the target wind measurement sub-module is constructed to correct the real-time measured wind speed of the target wind measurement sub-module and improve the wind measurement accuracy.

[0097] Specifically, when determining the sub-calibration model to be retrieved, it includes:

[0098] The judgment model establishes a working condition evaluation index sequence J according to the real-time working condition parameters of the target wind measurement sub-module, J = (j1, j2…j m1 ), where m1 is the number of working condition evaluation indexes, and j i is the real-time reference value of the i-th working condition evaluation index of the target wind measurement sub-module;

[0099] According to the working condition category sequence C, ci is set as the target working condition category in turn;

[0100] Generate a similarity evaluation value k for the real-time working condition parameters and the target working condition category of the target wind measurement sub-module

[0101]

[0102] where, j i ' is the reference value of the i-th working condition evaluation index of the target working condition category, βi is the influence factor of the i-th working condition evaluation index; Q is a fixed coefficient;

[0103] Establish a similarity evaluation value sequence K, K = (k1, k2…k m ), where ki is the similarity evaluation value of the real-time working condition parameters of the target wind measurement sub-region and the i-th working condition category;

[0104] Preset a similarity evaluation value threshold K1;

[0105] If k i > K1, call the i-th sub-calibration model.

[0106] Specifically, through the judgment model, based on the real-time working condition parameters of the wind measurement sub-module, judge the sub-calibration model to be called, and generate the real-time wind speed according to the average value of the output values of each sub-calibration model, so as to improve the wind measurement accuracy.

[0107] Specifically, the working condition evaluation indexes include but are not limited to operating temperature, operating load, environmental impact factors, and the connection state between each sub-structure, etc., and each working condition evaluation index is quantitatively processed, so that the reference values of each working condition evaluation index are within the same value range.

[0108] In the preferred embodiment of the present application, the central control unit further includes:

[0109] The first correction module obtains the gain percentage g of the wind turbine corresponding to the target wind measurement sub-module according to the preset feedback time node;

[0110] The first correction module is also used to preset a first gain percentage threshold G1 and a second gain percentage threshold G2, and G1 < G2;

[0111] If g < G1, the first correction module generates a first-level correction instruction;

[0112] If G1 ≤ g ≤ G2, the first correction module generates a second-level correction instruction;

[0113] If g > G2, the first correction module generates a third-level correction instruction, and the central control unit constructs a wind speed correction model for all the wind measurement sub-modules according to the third-level correction instruction.

[0114] Specifically, the first gain percentage threshold and the second gain percentage threshold can be set according to the historical operation parameters of the wind turbine.

[0115] Specifically, the first correction module is further configured to:

[0116] Correct the working condition category sequence C according to the first-level correction instruction;

[0117] Update the wind speed correction model of the target wind measurement sub-module according to the correction result, obtain the gain percentage g1 of the wind turbine, and generate a correction instruction.

[0118] Specifically, the central control unit further includes:

[0119] A second correction module, configured to select the wind measurement sub-modules to be corrected according to the second-level correction instruction and the operation evaluation value sequence B, B = (b1, b2... bn), and establish a wind speed correction model for all the wind measurement sub-modules to be corrected;

[0120] The second correction module is further configured to set a first operation evaluation value threshold B1 according to the gain percentage g;

[0121] If bi < B1, the second correction module sets the i-th wind measurement sub-module as the wind measurement sub-module to be corrected.

[0122] It can be understood that in the above embodiments, by judging the improvement of the power generation of the corrected wind measurement sub-modules and formulating a suitable overall correction plan, while improving the power generation efficiency, the correction cost is minimized as much as possible, and the working condition categories are continuously refined and the wind speed correction model is updated, thereby improving the correction accuracy.

[0123] According to the first concept of the present application, by adding an anchoring unit, synchronous wind measurement is performed on the typical positions of the wind farm using the anchoring unit and the wind measurement sub-modules on the wind turbine, and by establishing a working condition category sequence, monitoring the parameter differences between the two under different working conditions, and establishing a multi-source coupling model according to the difference relationship between the collected data and the anchored data, the data collected by the wind measurement sub-modules of the wind turbine is corrected, the wind measurement accuracy is improved, the wind measurement error is reduced, and thus the power generation efficiency and safety performance of the generator set are improved.

[0124] According to the second concept of the present application, by adding a first correction module and a second correction module, the improvement of the power generation of the corrected wind measurement sub-module is judged, and a suitable overall correction plan is formulated. While improving the power generation efficiency, the correction cost is minimized as much as possible, and the working condition categories are continuously refined to update the wind speed correction model, thereby improving the correction accuracy.

[0125] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present application, several improvements and replacements can be made, and these improvements and replacements should also be regarded as the protection scope of the present application.

Claims

1. A wind measurement and correction system for a wind turbine, characterized in that, Including: A rectification unit, which is used to obtain the wind measurement sub-module parameters of each wind turbine and establish a wind measurement sub-module sequence A, A = (a1, a2... an), where ai is the wind measurement sub-module on the i-th wind turbine and n is the number of wind measurement sub-modules; An anchoring unit, which is used to generate anchoring data, and the anchoring unit is a lidar; When generating the anchoring data, it includes: Synchronizing the data of the lidar based on the wind measurement tower in the wind farm, and generating anchoring data according to the wind speed data collected by the lidar; A central control unit, which is used to select a target wind measurement sub-module, set the synchronous calibration data acquisition parameters of the target wind measurement sub-module and the anchoring unit, and generate a synchronous calibration data packet; The central control unit is also used to generate a wind speed correction model for the target wind measurement sub-module according to the synchronous calibration data packet; The central control unit also includes: A first processing module, which is used to set a working condition category sequence C, C = (c1, c2... cm), where ci is the i-th type of working condition and m is the number of working condition categories; A second processing module, which is used to obtain the first wind speed curve collected by the anchoring unit and the second wind speed curve collected by the target wind measurement sub-module; A third processing module, which is used to establish a time axis and align the first wind speed curve and the second wind speed curve based on the time scale; The third processing module is also used to establish multiple time intervals according to the working condition category sequence C and establish a time interval - working condition category mapping table; The third processing module is also used to generate the wind speed difference of each time interval and establish a wind speed difference sequence F, F = (f1, f2... fα); fi is the wind speed difference of the i-th time interval and α is the number of time intervals; A fourth processing module, which is used to establish a time interval - working condition category mapping table and generate a synchronous calibration data packet according to the time interval - working condition category mapping table and the wind speed difference sequence F; The fourth processing module is also used to establish a wind speed correction model for the target wind measurement sub-module; The fourth processing module is also used for: Establishing multiple sub-correction models according to the synchronous calibration data packet; Establishing a sub-correction model sequence D, D = (d1, d2... dm), where di is the sub-correction model corresponding to the i-th working condition category; Establishing a judgment model, which judges the sub-correction model to be called according to the real-time working condition parameters of the target wind measurement sub-module; Correcting the wind speed parameters collected by the target wind measurement sub-module according to the called sub-correction model; Constructing a wind speed correction model for the target wind measurement sub-module according to the judgment model and all sub-correction models.

2. The wind measurement and calibration system for a wind turbine according to claim 1, wherein The central control unit includes: A first evaluation module, which is used to generate the operation evaluation value of each wind measurement sub-module and establish an operation evaluation value sequence B, B = (b1, b2... bn), where bi is the operation evaluation value of the i-th wind measurement sub-module; The first evaluation module is also used to set the wind measurement sub-module corresponding to the minimum value in the operation evaluation value sequence B as the target wind measurement sub-module.

3. The wind measurement and calibration system for a wind turbine according to claim 2, characterized in that, When generating the operation evaluation value of each wind measurement sub-module, it includes: Sequentially setting ai as the wind measurement sub-module to be evaluated; Obtaining the historical maintenance frequency of the wind measurement sub-module to be evaluated and the operation efficiency of the corresponding wind turbine; Generating a first reference evaluation value H1 of the wind measurement sub-module to be evaluated according to the historical maintenance frequency; Generate the second reference evaluation value H2 of the sub-module to be evaluated according to the operating efficiency of the wind turbine unit; Generate the operating evaluation value b of the anemometry sub-module to be evaluated; b = e1*H1 + e2*H2.

4. The wind measurement and correction system for a wind turbine according to claim 3, wherein When judging the sub-calibration model to be retrieved, it includes: The judgment model establishes a working condition evaluation index sequence J according to the real-time working condition parameters of the target wind measurement sub-module, J = (j1, j2…j m1 ), where m1 is the number of working condition evaluation indexes, and j i is the real-time reference value of the i-th working condition evaluation index of the target wind measurement sub-module; Set c in sequence according to the working condition category sequence C i as the target working condition category; Generate the similarity evaluation value k of the real-time operating condition parameters and the target operating condition category of the target anemometry sub-module k = Q / {1 - βi * (j i -j i ') 2}; where j i ' is the reference value of the i-th working condition evaluation index for the target working condition category, and β i is the influence factor of the i-th working condition evaluation index; Q is a fixed coefficient; Establish a similarity evaluation value sequence K, K = (k1, k2…k m ), where k i is the similarity evaluation value between the real-time working condition parameters of the target wind measurement sub-region and the i-th working condition category; Preset the similarity evaluation value threshold K1; If k i > K1, call the i-th sub-calibration model.

5. The anemometry correction system for a wind turbine as claimed in claim 4, wherein The central control unit further includes: The first correction module obtains the gain percentage g of the wind turbine unit corresponding to the target anemometry sub-module according to the preset feedback time node; The first correction module is further used to preset the first gain percentage threshold G1 and the second gain percentage threshold G2, and G1 < G2; If g < G1, the first correction module generates a first-level correction instruction; If G1 ≤ g ≤ G2, the first correction module generates a second-level correction instruction; If g > G2, the first correction module generates a third-level correction instruction, and the central control unit constructs the wind speed correction model of all anemometry sub-modules according to the third-level correction instruction.

6. The anemometry calibration system for a wind turbine according to claim 5, characterized in that, The first correction module is further used for: Correct the operating condition category sequence C according to the first-level correction instruction; Update the wind speed correction model of the target anemometry sub-module according to the correction result, obtain the gain percentage g1 of the wind turbine unit, and generate a correction instruction.

7. The wind measurement and calibration system for a wind turbine according to claim 6, characterized in that, The central control unit further includes: The second correction module is used to select the anemometry sub-module to be corrected according to the second-level correction instruction and the operating evaluation value sequence B, B = (b1, b2…bn), and establish the wind speed correction model of all anemometry sub-modules to be corrected; The second correction module is further used to set the first operating evaluation value threshold B1 according to the gain percentage g; If bi < B1, the second correction module sets the i-th anemometry sub-module as the anemometry sub-module to be corrected.

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