Multi-mode operation switching method of main control system of wind generating set

Abstract

The invention discloses a multi-mode operation switching method of a main control system of a wind generating set, and particularly relates to the field of wind power generation operation switching. Comprising the steps of S1, collecting environment parameters corresponding to all wind generating sets, S2, preprocessing the collected data, S3, obtaining a wind power characteristic rule, S4, setting a dynamic threshold value, S5, dividing mode categories, and S6, generating an operation mode switching strategy. The multi-mode operation switching method of the main control system of the wind generating set is combined with a correction coefficient and a law function, the wind power characteristics are analyzed to obtain a second wind power characteristic group, and the capability of accurately mastering the wind power characteristics under different wind power conditions is improved; the third wind power characteristic group is generated through calculation, so that the problem of poor performance of the wind generating set in a special environment due to fixed threshold setting is reduced; the optimal wind power generation mode is divided by comparing and analyzing the real-time wind power characteristic data with the operation mode characteristics and the dynamic threshold value, and the wind energy capturing efficiency and the unit operation stability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wind power generation operation switching, more particularly, to a multi-mode operation switching method of a wind turbine generator system master control system. BACKGROUND

[0002] With the global demand for clean energy continuing to rise, wind power, as an important part of renewable energy, the number of wind turbine generators is increasing, and in the process of wind power generation, due to the unstable characteristics of wind resources, it is particularly important to ensure that the wind turbine generator can operate efficiently and stably under different wind conditions.

[0003] At present, most wind turbine generator master control systems use traditional operation mode switching schemes, which consist of a sensor module, a central processing unit and an actuator. The sensor module is responsible for real-time collection of wind speed and direction, as well as the operating state data of the unit itself; the central processing unit analyzes and processes the collected data according to the pre-set fixed rules and thresholds, and when the parameters reach a certain threshold, the central processing unit will issue an instruction to control the actuator to switch the operating mode.

[0004] However, in actual use, there are still some shortcomings, such as the fixed switching rules of the existing wind turbine generator master control system, which cannot timely and accurately adjust the operating mode when the wind speed changes rapidly, resulting in low wind energy capture efficiency and waste of energy; the fixed threshold setting cannot fully consider the differences in wind characteristics in different regions and seasons, making it difficult for the wind turbine generator to perform optimally in special environments; the existing master control system has limited real-time monitoring and analysis capabilities for the operating state of the unit, cannot dig deep into the potential information behind the data, and cannot predict possible failures in advance, thereby increasing the maintenance cost and downtime of the unit. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art, the present application provides a multi-mode operation switching method for a wind turbine generator master control system, which solves the problems raised in the background art by the following scheme.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical scheme: The multi-mode operation switching method for the wind turbine generator master control system, characterized in that it comprises: S1: Collecting the environmental parameters corresponding to each wind turbine generator: collecting the wind power generation area to be measured by the wind power collector system to obtain a first wind power feature group; S2: Preprocessing the collected data: preprocessing the first wind power feature group to obtain a first key feature group corresponding to the first wind power feature group; S3: Obtain the wind power characteristic rule: obtain the wind power characteristic analysis model, pass the first key feature group through the wind power characteristic analysis model, and obtain the second wind power feature group; S4: Set the dynamic threshold: based on the second wind power feature group, and combined with the regional characteristics of the to-be-tested wind power generation area, obtain the third wind power feature group, which is the dynamic threshold corresponding to the wind power generation mode switching; S5: Divide the mode category: based on the historical wind power features, generate the wind power generation mode, and combine the third wind power feature group to divide the wind power generation mode corresponding to the to-be-tested wind power generation area; S6: Generate the operation mode switching strategy: based on the division instruction of the wind power generation mode in S5, control the operation of each execution unit in the to-be-tested wind power generation area to obtain the operation mode switching strategy.

[0007] Preferably, the S3, obtaining the second wind power feature group, specifically includes: According to the first wind power feature group, the first key feature group is classified to obtain the characteristic group corresponding to the first wind power feature group. The characteristic group is a target key characteristic corresponding to the first wind power feature group. The target key characteristic includes wind speed characteristics, wind direction characteristics, and environmental characteristics. In the preset system operation database, the wind power characteristic analysis model corresponding to the characteristic group is obtained. The preset system operation database is used to save the corresponding relationship between the characteristic group and the wind power characteristic analysis model.

[0008] Preferably, the S3, obtaining the second wind power feature group, specifically includes: Based on the cut-in wind speed , the rated wind speed , and the cut-out wind speed , the law function of the wind speed characteristics is obtained, including: When the real-time wind speed or , ; When , the law function of the wind speed characteristics is specifically represented as: Wherein, is the average rated power of the wind turbine generator set, is the real-time wind speed, is the correction coefficient of the average wind speed, is the correction coefficient of the wind speed change rate; When , the law function of the wind speed characteristics is specifically represented as: wherein, is the average rated power of the wind turbine, is the correction coefficient of the average wind speed, is the correction coefficient of the wind speed variation rate.

[0009] Preferably, the S3, acquiring the second wind force feature group, specifically comprises: based on the air density , the real-time wind speed , and the power coefficient , acquiring the regular function of the wind direction characteristic , specifically expressed as: , wherein, is the correction coefficient of the dominant wind direction, is the correction coefficient of the wind direction variation frequency, is the rotor swept area; wherein, the value of the rotor swept area is , is the rotor radius.

[0010] Preferably, the S3, acquiring the second wind force feature group, specifically comprises: based on the average wind speed and the rated wind speed in the time interval , setting the correction coefficient of the average wind speed ; when , setting the correction coefficient of the average wind speed ; when , the calculation formula of the correction coefficient of the average wind speed , specifically expressed as: wherein, is the time window length, which is the calculation interval of the average wind speed, is the time corresponding to the real-time wind speed, is the variable representing time in the time interval, is the wind speed at the moment , and is the rated wind speed; based on the wind speed variation value of the wind speed at the moment relative to and the wind speed variation threshold , setting the correction coefficient of the wind speed variation rate Configure; when At that time, set a correction factor for the rate of change of wind speed. ; when Correction factor for average wind speed The calculation formula is specifically expressed as follows: in, This represents the pre-set wind speed change threshold. Representing the current time wind speed, This represents the time corresponding to the real-time wind speed. This represents a time interval.

[0011] Preferably, step S3, obtaining the second wind force feature group, specifically includes: Based on the angle between the prevailing wind direction and the wind turbine's optimal windward direction. The prevailing wind direction is within the time interval. Calculate the correction factor for the prevailing wind direction based on the most frequent wind direction within the area. Specifically, it is expressed as: ; Based on time interval Frequency of inland wind direction change and the preset wind direction change frequency threshold Correction factor for the frequency of wind direction changes Configure; when When this happens, a correction factor is set for the frequency of wind direction changes. ; when Correction factor for the frequency of wind direction change The calculation formula is specifically expressed as follows: in, This is represented as the preset threshold for the frequency of wind direction changes. Represented as time The change in inland wind direction exceeds the prescribed angle Number of times, This is expressed as the length of the time window.

[0012] Preferably, in S4, the third wind force feature group includes a wind speed threshold, a wind direction threshold, and an environment switching threshold.

[0013] Preferably, step S5 involves dividing the wind power generation mode corresponding to the wind power generation area to be measured, specifically including: Acquire historical wind power characteristic data in the system operation database; Classify the wind power characteristic data by a clustering algorithm to form wind power generation mode categories; Define the characteristic description and parameter range corresponding to the wind power generation mode categories; Extract the operation mode characteristics corresponding to each wind power generation mode category in the system operation database; Compare and analyze the real-time wind power characteristic data of the current to-be-tested wind power generation area with the extracted operation mode characteristics and dynamic threshold values; Classify the real-time wind power characteristic data of the to-be-tested wind power generation area and divide the optimal wind power generation mode.

[0014] Technical effects and advantages of the present application: 1. The present application improves the accurate grasp of wind power characteristics under different wind conditions by deeply analyzing the wind power characteristics according to the first key characteristic group, combining the correction coefficient and the law function, reduces the problems of unstable operation and low efficiency of the unit caused by insufficient grasp of wind power characteristics, and reduces the maintenance cost and downtime of the unit; 2. The present application improves the flexibility and adaptability of threshold setting by calculating the third wind power characteristic group and dynamically updating the threshold values, and reduces the problem of poor performance of the wind power generator set in special environments caused by fixed threshold setting; 3. The present application improves the classification and adaptability to different wind conditions by classifying multiple wind power generation mode categories by using a clustering algorithm, comparing and analyzing the real-time wind power characteristic data with the operation mode characteristics and dynamic threshold values, and dividing the optimal wind power generation mode, reduces the problem of low power generation efficiency caused by improper selection of operation mode, and further improves the wind energy capture efficiency and operation stability of the unit. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 The method steps of the present application.

[0016] Figure 2 The system flowchart corresponding to the method of the present application.

[0017] Figure 3 The system structure schematic diagram corresponding to the method of the present application.

[0018] BRIEF DESCRIPTION OF DRAWINGS: 300, a device security analysis system processing structure schematic diagram based on big data; 301, a system central processor; 302, a communication bus; 303, a system database; 304, a user information terminal. DETAILED DESCRIPTION

[0019] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of the present application.

[0020] The terms used in the following embodiments of the present application are only for the purpose of describing the specific embodiments, and are not intended to be limiting on the present application. As used in the specification of the present application, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or" used in the present application, means and includes any or all possible combinations of one or more listed items.

[0021] Hereinafter, the terms "first", "second", and "third" are only for the purpose of description, and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second", and "third" can explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0022] As shown in the multi-mode operation switching method of the wind turbine generator system master control system, Figure 1 The multi-mode operation switching method of the wind turbine generator system master control system includes S1: collecting environmental parameters corresponding to each wind turbine generator, S2: preprocessing the collected data, S3: obtaining wind characteristics, S4: setting dynamic threshold, S5: dividing mode categories, and S6: generating operation mode switching strategy.

[0023] S1: Collecting environmental parameters corresponding to each wind turbine generator: collecting the wind power generation area to be measured by the wind collector system to obtain the first wind characteristic group; Specifically, after the wind turbine generator system master control system is started, the sensors in the wind collector system immediately start working and continuously collect environmental parameter data. The wind collector system includes multiple types of sensors, including but not limited to wind speed sensors, wind direction sensors, temperature sensors, humidity sensors, pressure sensors, etc., and stores them in the system operation database to form the first wind characteristic group. The first wind characteristic group includes rated wind speed, real-time wind speed, cut-in wind speed, rated power of the wind turbine generator, best wind direction of the wind wheel, wind direction, wind wheel radius, air density, power coefficient, gas constant of air, and pressure and temperature data corresponding to multiple seasons.

[0024] In the embodiment, a wind speed sensor with a precision of ±0.1 m / s is installed at the hub height of each wind turbine in the wind power generation area to be measured to measure the actual wind speed acting on the wind wheel at a sampling frequency of 10 times per second; a wind direction sensor with a precision of ±1° is installed at the top of the nacelle to perceive the wind direction at a sampling frequency of 5 times per second; a temperature sensor with a precision of ±0.5°C and a humidity sensor with a precision of ±5% RH are distributed at different heights of the tower and in the surrounding environment, and collect data every 1 minute to obtain temperature and humidity data at different positions; a pressure sensor with a precision of ±0.1 kPa is installed near the wind wheel to monitor the change of air pressure at a sampling frequency of 1 time per second.

[0025] S2: Preprocessing the collected data: preprocessing the first wind feature group to obtain a first key feature group corresponding to the first wind feature group; Specifically, after obtaining the first wind feature group, a plurality of key features corresponding to the first wind feature group, i.e., the first key feature group, can be obtained through preprocessing. The steps of preprocessing are as follows: data classification: classifying the collected data, and the classification includes but is not limited to wind speed data, wind direction data, temperature data, humidity data, etc.; wind speed data filtering: processing the wind speed data by using a low-pass filter, and the cutoff frequency of the low-pass filter is set according to the Butterworth low-pass filter algorithm; wind direction data filtering: processing the wind direction data by using a band-pass filter, and setting the passband range according to the Chebyshev band-pass filter; data denoising: setting a range by calculating the mean and standard deviation of the wind speed data within a unit time; when the deviation of the wind speed data point from the mean exceeds 3 times the standard deviation, the data point is determined to be an abnormal point, and the reasonable value obtained by the interpolation algorithm is used to replace it; data normalization: using a linear normalization method to unify the dimension and range of data in different ranges.

[0026] S3: Obtaining the wind power characteristic law: obtaining a wind power characteristic analysis model, and inputting the first key feature group into the wind power characteristic analysis model to obtain a second wind feature group; Specifically, the wind power characteristic analysis model is a learning model constructed in advance. By inputting the first key feature group into the wind power characteristic analysis model, the wind power characteristic analysis model obtains a second wind feature group according to the first key feature group, and the second wind feature group includes average wind speed, wind speed change value, law function of wind speed characteristic, dominant wind direction, wind direction change frequency, law function of wind direction characteristic, air pressure change function, temperature change function, and law function of environmental characteristic.

[0027] In one possible implementation, obtaining the second wind force feature group includes: classifying the first key feature group according to the first wind force feature group to obtain the characteristic group corresponding to the first wind force feature group, wherein the characteristic group is the target key characteristic corresponding to the first wind force feature group, and the target key characteristic includes wind speed characteristic, wind direction characteristic and environmental characteristic; and obtaining the wind force characteristic analysis model corresponding to the characteristic group in a preset system operation database, wherein the preset system operation database is used to store the correspondence between the characteristic group and the wind force characteristic analysis model.

[0028] Specifically, the first key feature group is classified through the first wind force feature group, and the corresponding characteristic group is obtained. The characteristic group is the target key characteristic involved in the first wind force feature group. That is, by confirming the key characteristic category to which the first wind force feature group belongs, the key characteristic law involved in the wind force feature analysis model is confirmed. The target key characteristic law includes, but is not limited to: wind speed characteristic law, wind direction characteristic law, and environmental characteristic law, etc. After determining the characteristic group of the first wind force feature group, the corresponding wind force feature analysis model is obtained from the preset system operation database through the correspondence between the characteristic group and the wind force feature analysis model. The preset system operation database is a pre-built database used to store multiple characteristic groups, multiple wind force feature analysis models, and the correspondence between multiple characteristic groups and multiple wind force feature analysis models. The characteristic group and the wind force feature analysis model correspond one-to-one, including but not limited to: wind speed analysis model corresponding to wind speed characteristics, wind direction analysis model corresponding to wind direction characteristics, and environmental factor analysis model corresponding to environmental characteristics, etc.

[0029] In one possible implementation, obtaining the second wind force feature set further includes: based on a time interval The corresponding average wind speed and rated wind speed Correction factor for average wind speed Configure it when When this is the case, a correction factor for the average wind speed is set. ;when Correction factor for average wind speed The calculation formula is specifically expressed as follows: in, This is expressed as the length of the time window, which is the calculation interval for the average wind speed. This represents the time corresponding to the real-time wind speed. This represents a variable indicating time within a time interval. Represented as Wind speed at any moment Expressed as rated wind speed; based on wind speed at time... relative to the wind speed change value and the wind speed change threshold , the correction coefficient of the wind speed change rate is set, when , the correction coefficient of the wind speed change rate is set, when , the correction coefficient of the average wind speed is calculated, and the calculation formula is specifically as follows: wherein, is a pre-set wind speed change threshold, is the wind speed at the current time , is the time corresponding to the real-time wind speed, is the time interval; based on the cut-in wind speed , the rated wind speed , and the cut-out wind speed , the regular function of the wind speed characteristic is obtained , specifically including: when the real-time wind speed or , the correction coefficient of the average wind speed is set to 1; when , the correction coefficient of the average wind speed is specifically as follows: wherein, is the rated power of the wind turbine, is the real-time wind speed, is the correction coefficient of the average wind speed, is the correction coefficient of the wind speed change rate; when , the correction coefficient of the average wind speed is specifically as follows: wherein, is the rated power of the wind turbine, is the correction coefficient of the average wind speed, is the correction coefficient of the wind speed change rate.

[0030] Specifically, the correction coefficient of the average wind speed is dynamically adjusted according to the current wind speed level, so as to accurately reflect the actual operation state of the wind turbine; when , the wind speed is at a high level, and the generator is close to or reaches the rated power operation, the correction coefficient of the average wind speed is set; when , the correction coefficient of the average wind speed is dynamically adjusted by calculating the ratio of the average wind speed in the time interval to the rated wind speed; the correction coefficient of the wind speed change rate for considering the influence of short-term fluctuation of wind speed on power generation efficiency, when the wind speed change is within a normal range; when an upper limit of the wind speed change rate is limited to avoid unstable operation or efficiency reduction of the generator due to severe fluctuation of the wind speed; a regular function of wind speed characteristics is used to describe the output power characteristics of the wind turbine at different wind speeds, when the real-time wind speed or the wind turbine set is in a shutdown state; when a correction coefficient is introduced to dynamically describe the output power of the generator in the low wind speed range; when the generator is in a rated power operation state.

[0031] In a possible implementation, the second wind feature group is further obtained based on an included angle between a dominant wind direction and an optimal wind-approaching direction of the wind wheel , the dominant wind direction being a wind direction with the highest occurrence frequency in a time interval , a correction coefficient of the dominant wind direction being calculated , and being specifically represented as: ; based on a wind direction change frequency in a time interval and a preset wind direction change frequency threshold , a correction coefficient of the wind direction change frequency is set, when , the correction coefficient of the wind direction change frequency is set; when , the correction coefficient of the wind direction change frequency is calculated, and is specifically represented as: wherein represents the preset wind direction change frequency threshold, represents a number of times of wind direction change over a predetermined angle in a time window, represents a length of the time window; based on air density , real-time wind speed , and power coefficient , a regular function of wind direction characteristics is obtained, and is specifically represented as: , , wherein represents the correction coefficient of the dominant wind direction, represents the correction coefficient of the wind direction change frequency, This is expressed as the swept area of ​​the wind turbine; where the swept area of ​​the wind turbine is a value of... , This is expressed as the radius of the wind turbine.

[0032] Specifically, the prevailing wind direction correction coefficient To quantify the alignment between the wind turbine and the prevailing wind direction, thereby assessing the wind turbine's energy capture efficiency under current wind conditions; The range of values ​​is When the wind turbine is fully facing the wind, that is , Taking the maximum value of 1 indicates that the wind turbine is perfectly aligned with the wind direction, resulting in the highest energy capture efficiency; when When it increases, A decrease indicates an increased deviation between the wind turbine and the wind direction, resulting in lower energy capture efficiency; the wind direction change frequency correction coefficient. To assess the impact of wind direction changes on the operational stability of wind turbines; when At that time, the wind direction change was within the normal range; when Frequent wind direction changes cause the wind turbine to adjust its direction frequently, reducing operating efficiency. This study quantifies the impact of wind direction changes on energy capture using formulas; the regular function of wind direction characteristics is also discussed. By introducing the prevailing wind direction and wind direction change frequency correction coefficient, the influence of wind direction factors on the output power of wind turbines is comprehensively considered.

[0033] In one possible implementation, obtaining the second wind characteristic set further includes: performing data fitting on air pressure and temperature data corresponding to multiple seasons stored in the system operation database to obtain the air pressure change function corresponding to each season. and temperature change function ,in This is represented as a seasonal identifier; in this embodiment, It indicates springtime; Indicates summer; It indicates autumn; Indicates winter; Gas constant based on air Real-time wind speed and power coefficient Obtain the regular function of environmental characteristics Specifically, it is expressed as: in, Expressed as a function of air pressure change, Represented as a function of temperature change, This is expressed as the swept area of ​​the wind turbine; where the swept area of ​​the wind turbine is a value of... , This is expressed as the radius of the wind turbine.

[0034] Specifically, by fitting the air pressure and temperature data corresponding to multiple seasons stored in the system's operating database, the variation patterns of air pressure and temperature under different seasons are obtained. The changes in air pressure and temperature directly affect air density, which in turn affects the power output of the wind turbine.

[0035] S4: Set dynamic threshold: Based on the second wind feature group and combined with the regional characteristics of the wind power generation area to be tested, obtain the third wind feature group. The third wind feature group is the dynamic threshold corresponding to the wind power generation mode switching. Specifically, based on the regional characteristics of the wind power generation area to be tested, including but not limited to topographic relief and surface roughness, a third wind power feature group is generated by combining the second wind power feature group. The third wind power feature group includes wind speed threshold, wind direction threshold, and environmental switching threshold.

[0036] In one possible implementation, obtaining the third set of wind characteristics includes: a regular function based on wind speed characteristics. Calculate the wind speed threshold Specifically, it is expressed as: in, Indicated as within a time range The maximum value within, Indicated as within a time range Minimum value within, This is represented as a wind speed threshold adjustment coefficient, ranging from 0 to 1, used to adjust the influence of maximum and minimum wind speeds on the threshold according to actual needs; a function based on wind direction characteristics. Calculate the wind direction threshold Specifically, it is expressed as: in, This is expressed as the wind direction threshold adjustment coefficient; Indicated as within a time range Average value within; regular function based on environmental characteristics Calculate the environment switching threshold Specifically, it is expressed as: in, This is expressed as the environment switching threshold adjustment coefficient; Indicated as within a time range The average value within the range.

[0037] Specifically, the pre-set threshold is updated and analyzed every other day, and the threshold is re-evaluated in combination with historical data, and when the corresponding regular function in the second wind force feature group changes, the threshold is immediately recalculated and adjusted.

[0038] S5: dividing mode category: generating wind power generation mode based on historical wind force features, and dividing the wind power generation mode corresponding to the to-be-tested wind power generation area in combination with the third wind force feature group.

[0039] Specifically, the dynamic threshold calculated according to the third wind force feature group is used to extract and identify the features under different operation modes in the system operation database, classify the wind conditions corresponding to the to-be-tested wind power generation area, and divide the best wind power generation mode.

[0040] In a possible implementation, dividing the wind power generation mode corresponding to the to-be-tested wind power generation area includes: Obtaining historical wind force feature data in the system operation database, the historical wind force feature data including data information of wind speed, wind direction, temperature, humidity, and air pressure in different time periods in multiple seasons; classifying the wind force feature data by a clustering algorithm to form multiple wind power generation mode categories, wherein the wind power generation mode categories include a low wind speed stable mode, a low wind speed fluctuation mode, a high wind speed stable mode, a high wind speed fluctuation mode, and the like; defining feature descriptions and parameter ranges corresponding to the multiple wind power generation mode categories; extracting multiple operation mode features corresponding to each wind power generation mode category in the system operation database; the operation mode features include but are not limited to a pitch angle setting of a wind turbine, a generator speed range, a power output characteristic, and the like under each wind power generation mode; comparing and analyzing real-time wind force feature data of the to-be-tested wind power generation area with the extracted operation mode features and the dynamic threshold; classifying the real-time wind force feature data of the to-be-tested wind power generation area, and dividing the best wind power generation mode.

[0041] S6: generating an operation mode switching strategy: based on the division instruction of the wind power generation mode in S5, controlling each execution unit in the to-be-tested wind power generation area to obtain an operation mode switching strategy.

[0042] As shown in the multi-mode operation switching system of the wind turbine main control system, Figure 2 The multi-mode operation switching system of the wind turbine main control system includes a system operation database, a system central processing module, and a user information terminal, and further includes a power generation area acquisition module, a data preprocessing module, a wind force characteristic regularity analysis module, a dynamic threshold setting module, a power generation mode category division module, and an operation mode switching strategy generation module.

[0043] The power generation area acquisition module: acquiring the to-be-tested wind power generation area by a wind force collector system to obtain the first wind force feature group; The data preprocessing module: performs a preprocessing operation on the first wind power feature group, and the preprocessing operation is used to obtain a first key feature group corresponding to the first wind power feature group. The wind power characteristic rule analysis module: obtains a wind power characteristic analysis model, and obtains a second wind power feature group by inputting the first key feature group into the wind power characteristic analysis model. The dynamic threshold setting module: obtains a third wind power feature group based on the second wind power feature group and in combination with the regional characteristics of the to-be-tested wind power generation area, and the third wind power feature group is a dynamic threshold corresponding to the wind power generation mode switching. The power generation mode classification division module: generates a wind power generation mode based on historical wind power features, and divides the wind power generation mode corresponding to the to-be-tested wind power generation area in combination with the third wind power feature group. The operation mode switching strategy generation module: controls each execution unit in the to-be-tested wind power generation area based on the division instruction of the wind power generation mode transmitted by the power generation mode classification division module, so as to obtain an operation mode switching strategy.

[0044] The system operation database is all data texts of the multi-mode operation switching system, and information texts output by each module are collected in real time. The system central processing module is used to control the information text instructions output by each module in the method. The user information terminal is an information output device of the multi-mode operation switching system.

[0045] In this embodiment, a multi-mode operation switching system processing structure is also disclosed. Referring to Figure 3 , the electronic device can include at least one system central processor 301, at least one communication bus 302, a user information terminal 304, and at least one system database 303.

[0046] The system central processor 301 is the core operation and control unit of the entire multi-mode operation switching system. It includes one or more processing cores, connects various parts in the entire system through various interfaces and lines, executes instructions, programs, code sets or instruction sets stored in the system database, and can call data stored therein, so as to execute various functions of the multi-mode operation switching system, including analysis and processing of wind power feature data, setting of dynamic thresholds, division of wind power generation modes, generation of operation mode switching strategies, etc.

[0047] The communication bus 302 is used to realize the connection and communication between components.

[0048] Among them, the system database 303 is used to save a large amount of data related to the multi-mode operation switching system, including historical operation data, wind characteristic parameters, operation strategies in different modes, switching rules, fault records, and a large amount of historical operation data, including power output data, wind speed and direction data, generator temperature data in various modes; when the system central processor executes various functions, it will frequently call these data from the system database to ensure that the system can quickly and accurately make switching decisions of the operation mode according to different wind characteristics and environmental conditions, so as to realize accurate control and efficient management of the multi-mode operation switching system.

[0049] Among them, the user information end 304 connects the display screen and the camera and other external devices through a standard wired interface or a wireless interface to provide an interface for the user to interact with the system.

[0050] Secondly: the drawings in the disclosed embodiments of the application only involve the structures involved in the disclosed embodiments of the application, other structures can refer to the usual design, and in the case of no conflict, the same embodiment and different embodiments of the application can be combined with each other; Finally: the above only describes the preferred embodiments of the application and is not used to limit the application, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method for switching between multiple modes of operation of a wind turbine generator system master control system, characterized by, The method comprises the following steps: S1: Collecting the environmental parameters corresponding to each wind turbine: collecting the wind power generation area to be tested through a wind collector system to obtain a first wind feature group; S2: Preprocessing the collected data: preprocessing the first wind feature group to obtain a first key feature group corresponding to the first wind feature group; S3: Obtaining the wind power characteristic law: obtaining a wind power characteristic analysis model, and obtaining a second wind feature group by inputting the first key feature group into the wind power characteristic analysis model; S4: Setting a dynamic threshold: based on the second wind feature group and in combination with the regional characteristics of the wind power generation area to be tested, a third wind feature group is obtained, which is a dynamic threshold corresponding to the wind power generation mode switching; S5: Dividing the mode category: based on the historical wind feature, a wind power generation mode is generated, and the wind power generation mode corresponding to the wind power generation area to be tested is divided based on the third wind feature group; S6: Generating a running mode switching strategy: based on the division instruction of the wind power generation mode in S5, each execution unit in the wind power generation area to be tested is controlled to obtain a running mode switching strategy.

2. The multi-mode operation switching method of a wind turbine generator system master control system according to claim 1, characterized by: In S3, the second wind feature group is obtained, and specifically comprises: According to the first wind feature group, the first key feature group is classified to obtain a characteristic group corresponding to the first wind feature group, and the characteristic group is a target key characteristic corresponding to the first wind feature group, and the target key characteristic includes wind speed characteristics, wind direction characteristics and environmental characteristics; In the preset system running database, the wind power characteristic analysis model corresponding to the characteristic group is obtained, and the preset system running database is used to save the corresponding relationship between the characteristic group and the wind power characteristic analysis model.

3. The multi-mode operation switching method of a wind turbine generator system master control system according to claim 2, characterized in that: In S3, the second wind feature group is obtained, and specifically comprises: Based on a cut-in wind speed , a rated wind speed , and a cut-out wind speed , obtaining a regular function of wind speed characteristics , comprising: When the real-time wind speed or , ; When the regular function of wind speed characteristics , specifically represented as: wherein, is expressed as an average rated power of the wind turbine, is expressed as a real-time wind speed, is expressed as a correction factor for the average wind speed, is expressed as a correction factor for the wind speed variation rate; When the regular function of wind speed characteristics is specifically represented as: wherein is a correction factor expressed as the average rated power of the wind turbine, is a correction factor expressed as the average wind speed, is a correction factor expressed as the rate of change of wind speed.

4. The multi-mode operation switching method of a wind turbine generator system master control system according to claim 2, characterized by: In S3, the second wind feature group is obtained, and specifically comprises: Based on air density , real-time wind speed , and power coefficient , a regular function of wind direction characteristics is obtained, which is specifically represented as: ， wherein, is a correction factor for the prevailing wind direction, is a correction factor for the frequency of wind direction changes, is the swept area of the wind turbine; wherein the swept area of the wind turbine is in the range of , is the radius of the wind turbine.

5. The method of claim 3, wherein: In S3, the second wind feature group is obtained, and specifically comprises: based on a time interval corresponding to the average wind speed and the rated wind speed a correction factor for the average wind speed is set; When a correction factor for the average wind speed is set ; When the correction coefficient of the average wind speed is calculated, the formula is specifically represented as: wherein, is expressed as a time window length, the time window length being a calculation interval of the average wind speed, is expressed as a time corresponding to the real-time wind speed, is expressed as a variable indicating time within a time interval, is expressed as the wind speed at the time, is expressed as a rated wind speed; based on the wind speed at the time point relative to the wind speed change value and the wind speed change threshold , a correction coefficient for the wind speed change rate is set; When a correction coefficient of the wind speed variation rate is set ; When the correction coefficient of the average wind speed is calculated, the formula is specifically represented as: wherein, is represented as a pre-set wind speed variation threshold value, is represented as a wind speed at a current time point, is represented as a wind speed at a current time point, is represented as a time corresponding to a real-time wind speed, is represented as a time interval.

6. The multi-mode operation switching method of a wind turbine generator system master control system according to claim 4, characterized by: In S3, the second wind feature group is obtained, and specifically comprises: An angle between a dominant wind direction and an optimal wind-approaching direction of a wind wheel The dominant wind direction is a wind direction with the highest occurrence frequency in a time interval A correction coefficient of the dominant wind direction is calculated Specifically represented as: ； Based on a time interval An inner wind direction change frequency And a preset wind direction change frequency threshold A correction coefficient for the wind direction change frequency Is set; When the correction coefficient of the frequency of change of the wind direction is set ; When the correction coefficient of the wind direction change frequency is calculated as follows: wherein, is a predetermined wind direction change frequency threshold, is a time is a number of times the wind direction changes more than a prescribed angle within a time window, is a time window length.

7. The method of multi-mode operation switching of a wind turbine generator system supervisory control system according to claim 1, wherein: In S4, the third wind feature group includes wind speed threshold, wind direction threshold and environmental switching threshold.

8. The method of multi-mode operation switching of a wind turbine generator system master controller system according to claim 1, wherein: In S5, the wind power generation mode corresponding to the wind power generation area to be tested is divided, and specifically comprises: Obtaining the historical wind feature data in the system running database; Classifying the wind feature data by clustering algorithm to form a wind power generation mode category; Defining the feature description and parameter range corresponding to the wind power generation mode category; Extracting the running mode features corresponding to each wind power generation mode category in the system running database; Comparing and analyzing the real-time wind feature data of the current wind power generation area to be tested with the extracted running mode features and dynamic threshold; Classifying the real-time wind feature data of the wind power generation area to be tested, and dividing the best wind power generation mode.

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