Control method and system for vibration suppression of wind generating set

Abstract

The invention provides a control method and system for vibration suppression of a wind generating set, and relates to the technical field of wind power generation control, and the control method comprises the following steps: collecting wind power information data in an environment where the current wind generating set is located in real time, and dynamically adjusting a running state information collection time interval of the wind generating set; the operation state of the wind generating set is monitored in real time according to the operation state information collection time interval corresponding to the current moment, and operation state information of the wind generating set is obtained; whether vortex-induced vibration happens to the wind generating set or not is judged in combination with a vortex-induced vibration prediction model; and when vortex-induced vibration occurs in the wind generating set, height adjustment is conducted on the liquid level in a TLD damper of the wind generating set according to the vibration information of the current vortex-induced vibration. The system comprises modules corresponding to the steps of the method, intelligent monitoring and regulation of the wind generating set are achieved, and the operation efficiency and stability of the wind generating set are improved.

Description

Technical Field

[0001] The present invention provides a control method and system for vibration suppression of a wind generator set. The present invention relates to the technical field of wind power generation control, and in particular to the technical field of vibration suppression control of a wind generator set. Background Art

[0002] With the rapid development of renewable energy, wind power generation has been widely used as a clean and renewable energy form. However, during the operation of wind turbines, due to the influence of the complex and changeable wind environment, their operating state is often in an unstable state, especially the emergence of problems such as vortex-induced vibration, which poses a serious threat to the stable operation of wind turbines. Traditional wind turbine monitoring methods mainly rely on regular inspections and manual judgment, which is not only inefficient, but also difficult to accurately grasp the operating status of the unit in real time. In addition, for the prediction and suppression of complex problems such as vortex-induced vibration, traditional methods often rely on empirical formulas and the adjustment of fixed parameters, which lack flexibility and accuracy. Summary of the invention

[0003] The present invention provides a control method and system for vibration suppression of a wind turbine generator set to solve the above problems:

[0004] The present invention provides a control method and system for vibration suppression of a wind turbine generator set. The control method for vibration suppression of a wind turbine generator set includes:

[0005] Collect wind information data in the current environment of the wind turbine generator set in real time, and dynamically adjust the time interval for collecting operating status information of the wind turbine generator set according to the wind information data;

[0006] Monitor the operating status of the wind turbine generator set in real time according to the operating status information collection time interval corresponding to the current moment, and obtain the operating status information of the wind turbine generator set;

[0007] Determining whether vortex-induced vibration occurs in the wind turbine generator set based on the operating status information of the wind turbine generator set and a vortex-induced vibration prediction model;

[0008] When vortex-induced vibration occurs in the wind turbine generator set, the liquid level in the TLD damper of the wind turbine generator set is height-adjusted according to vibration information of the current vortex-induced vibration.

[0009] Furthermore, real-time collection of wind information data in the environment where the current wind turbine generator set is located, and dynamic adjustment of the time interval for collecting the operating status information of the wind turbine generator set according to the wind information data, include:

[0010] Real-time collection of wind information data in the environment where the current wind turbine generator set is located, wherein the wind information data includes wind speed information and wind direction change information;

[0011] Obtaining a wind state stability evaluation parameter in the current environment of the wind turbine generator set according to the wind speed information and wind direction change information;

[0012] When the wind state stability evaluation parameter is lower than a preset stability threshold, calling the current wind turbine generator set operation state information collection time interval;

[0013] The operation status information collection time interval is adjusted using a collection time interval adjustment model to obtain an adjusted operation status information collection time interval; wherein the adjusted operation status information collection time interval is obtained by the formula:

[0014]

[0015] Where T represents the adjusted operation status information collection time interval; F y represents the preset stability threshold; F represents the wind state stability evaluation parameter; T d Indicates the time interval for collecting the operating status information of the current wind turbine generator set; T c Indicates the preset initial running status information collection time interval.

[0016] Furthermore, the wind state stability evaluation parameters in the current environment of the wind turbine generator set are obtained according to the wind speed information and the wind direction change information, including:

[0017] Extracting the wind speed information, wherein the wind speed information includes a wind speed value and a wind speed change rate per a first unit time, and the value range of the first unit time is 3 min-5 min;

[0018] The wind speed stability parameter is obtained by using the wind speed value per first unit time and the wind speed change rate; wherein the wind speed stability parameter is obtained by the following formula:

[0019]

[0020] Where S represents the wind speed stability parameter; n represents the total number of complete first unit time experienced by wind information data collection; V pi V represents the average wind speed value corresponding to the i-th first unit time; maxi represents the maximum wind speed value corresponding to the i-th first unit time; T maxi represents the duration of the maximum wind speed in the i-th first unit time; T wrepresents the corresponding duration of the first unit time; λ represents the wind speed stability compensation coefficient, and the wind speed stability compensation coefficient is obtained by the following formula:

[0021]

[0022] Among them, P z Indicates the comprehensive wind speed change rate from wind information data collection to the current moment; P i represents the wind speed change rate in the i-th first unit time;

[0023] Extracting the wind direction change information, wherein the wind direction change information includes the number of wind direction changes within a first unit time, the wind direction deviation angle, and the wind speed value within a preset initial time period of the wind direction change, and the value range of the preset initial time period is 1min-2min;

[0024] The wind direction stability parameter is obtained by using the number of wind direction changes in the first unit time, the wind direction deviation angle, and the wind speed value in the preset initial time period of the wind direction change; wherein the wind direction stability parameter is obtained by the following formula:

[0025]

[0026] Where X represents the wind direction stability parameter; m represents the number of wind direction changes in the first unit time; α ij represents the wind direction deviation angle corresponding to the j-th wind direction change within the i-th first unit time; P ci V represents the wind direction change rate in the first i-th unit time; hij and V xij They respectively represent the wind speed values ​​corresponding to the start time and the end time of the preset initial time period when the j-th wind direction changes within the i-th first unit time; ξ represents the wind direction stability compensation coefficient, and the wind direction stability compensation coefficient is obtained by the following formula:

[0027]

[0028] Among them, P J represents the standard deviation of the wind direction change rate corresponding to n first unit times;

[0029] The wind speed stability parameter and wind direction change information are used to obtain a wind state stability evaluation parameter; wherein the wind state stability evaluation parameter is obtained by the following formula:

[0030] F=logS+logX

[0031] Wherein, F represents the wind state stability evaluation parameter.

[0032] Further, judging whether vortex-induced vibration occurs in the wind turbine generator set according to the operation status information of the wind turbine generator set in combination with a vortex-induced vibration prediction model includes:

[0033] Extracting the operating status information of the wind turbine generator set; wherein the operating status information includes wind speed information, wind direction information, unit speed data and vibration signal;

[0034] Performing data preprocessing on the operating status information to obtain the preprocessed operating status information, wherein the data preprocessing includes data cleaning processing, data noise reduction processing and standardization processing;

[0035] Retrieving a vortex-induced vibration prediction model for vortex-induced vibration prediction from a database; wherein the vortex-induced vibration prediction model adopts a neural network prediction model structure;

[0036] The preprocessed operating status information is input into a vortex-induced vibration prediction model, and the vortex-induced vibration prediction model is used to determine whether vortex-induced vibration occurs in the wind turbine generator set.

[0037] Further, when the wind turbine generator set generates vortex-induced vibration, the liquid level in the TLD damper of the wind turbine generator set is adjusted according to the vibration information of the current vortex-induced vibration, including:

[0038] When vortex-induced vibration occurs in the wind turbine generator set, the vibration amplitude and vibration frequency generated within a preset monitoring time period at the start time of the vortex-induced vibration are extracted;

[0039] Obtaining a target height of the liquid level in the TLD damper according to the vibration amplitude and vibration frequency generated by the vortex-induced vibration within a preset monitoring time period;

[0040] The fluid level in the TLD damper is adjusted according to the target height.

[0041] Furthermore, the control system for vibration suppression of the wind turbine generator set includes:

[0042] A collection interval adjustment module is used to collect wind information data in the environment where the wind turbine generator set is currently located in real time, and dynamically adjust the time interval for collecting the operating status information of the wind turbine generator set according to the wind information data;

[0043] An operation status monitoring module is used to monitor the operation status of the wind turbine generator set in real time according to the operation status information collection time interval corresponding to the current moment, and obtain the operation status information of the wind turbine generator set;

[0044] A vortex-induced vibration judgment module, used to judge whether vortex-induced vibration occurs in the wind turbine generator set according to the operating status information of the wind turbine generator set in combination with a vortex-induced vibration prediction model;

[0045] The vibration adjustment module is used to adjust the height of the liquid level in the TLD damper of the wind turbine generator set according to the vibration information of the current vortex-induced vibration when the wind turbine generator set has vortex-induced vibration.

[0046] Furthermore, the collection interval adjustment module includes:

[0047] A data acquisition module is used to collect wind information data in the environment where the current wind turbine generator set is located in real time, wherein the wind information data includes wind speed information and wind direction change information;

[0048] A parameter acquisition module, used to acquire a wind state stability evaluation parameter in the current environment of the wind turbine generator set according to the wind speed information and wind direction change information;

[0049] An interval retrieving module, used for retrieving the time interval for collecting the operating status information of the current wind turbine generator set when the wind state stability evaluation parameter is lower than a preset stability threshold;

[0050] The time interval calculation module is used to adjust the operation status information collection time interval by using the collection time interval adjustment model to obtain the adjusted operation status information collection time interval; wherein the adjusted operation status information collection time interval is obtained by the formula:

[0051]

[0052] Where T represents the adjusted operation status information collection time interval; F y represents the preset stability threshold; F represents the wind state stability evaluation parameter; T d Indicates the time interval for collecting the operating status information of the current wind turbine generator set; T c Indicates the preset initial running status information collection time interval.

[0053] Furthermore, the wind state stability evaluation parameters in the current environment of the wind turbine generator set are obtained according to the wind speed information and the wind direction change information, including:

[0054] A wind speed extraction module, used to extract the wind speed information, wherein the wind speed information includes a wind speed value and a wind speed change rate per a first unit time, and the value range of the first unit time is 3 min-5 min;

[0055] A wind speed parameter calculation module is used to obtain a wind speed stability parameter using the wind speed value per first unit time and the wind speed change rate; wherein the wind speed stability parameter is obtained by the following formula:

[0056]

[0057] Where S represents the wind speed stability parameter; n represents the total number of complete first unit time experienced by wind information data collection; V pi V represents the average wind speed value corresponding to the i-th first unit time; maxi represents the maximum wind speed value corresponding to the i-th first unit time; T maxi represents the duration of the maximum wind speed in the i-th first unit time; T w represents the corresponding duration of the first unit time; λ represents the wind speed stability compensation coefficient, and the wind speed stability compensation coefficient is obtained by the following formula:

[0058]

[0059] Among them, P z Indicates the comprehensive wind speed change rate from wind information data collection to the current moment; P i represents the wind speed change rate in the i-th first unit time;

[0060] A wind direction extraction module, used to extract the wind direction change information, wherein the wind direction change information includes the number of wind direction changes within a first unit time, the wind direction deviation angle, and the wind speed value within a preset initial time period of the wind direction change, and the value range of the preset initial time period is 1min-2min;

[0061] The wind direction parameter calculation module is used to obtain the wind direction stability parameter by using the number of wind direction changes in the first unit time, the wind direction deviation angle and the wind speed value in the preset initial time period of the wind direction change; wherein the wind direction stability parameter is obtained by the following formula:

[0062]

[0063] Where X represents the wind direction stability parameter; m represents the number of wind direction changes in the first unit time; α ij represents the wind direction deviation angle corresponding to the j-th wind direction change within the i-th first unit time; P ci V represents the wind direction change rate in the first i-th unit time; hij and V xijThey respectively represent the wind speed values ​​corresponding to the start time and the end time of the preset initial time period when the j-th wind direction changes within the i-th first unit time; ξ represents the wind direction stability compensation coefficient, and the wind direction stability compensation coefficient is obtained by the following formula:

[0064]

[0065] Among them, P J represents the standard deviation of the wind direction change rate corresponding to n first unit times;

[0066] The wind power evaluation parameter calculation module is used to obtain the wind power state stability evaluation parameter by using the wind speed stability parameter and the wind direction change information; wherein the wind power state stability evaluation parameter is obtained by the following formula:

[0067] F=logS+logX

[0068] Wherein, F represents the wind state stability evaluation parameter.

[0069] Furthermore, the vortex-induced vibration judgment module includes:

[0070] An operation information extraction module, used to extract the operation status information of the wind turbine generator set; wherein the operation status information includes wind speed information, wind direction information, unit speed data and vibration signal;

[0071] A preprocessing module, used to perform data preprocessing on the operating status information to obtain the preprocessed operating status information, wherein the data preprocessing includes data cleaning processing, data noise reduction processing and standardization processing;

[0072] A model retrieval module is used to retrieve a vortex-induced vibration prediction model for vortex-induced vibration prediction from a database; wherein the vortex-induced vibration prediction model adopts a neural network prediction model structure;

[0073] The model judgment module is used to input the preprocessed operating status information into the vortex-induced vibration prediction model, and judge whether the wind turbine generator set has vortex-induced vibration through the vortex-induced vibration prediction model.

[0074] Furthermore, the vibration adjustment module includes:

[0075] A vibration information extraction module, used for extracting the vibration amplitude and vibration frequency generated within a preset monitoring time period from the start time of the vortex-induced vibration when the wind turbine generator set generates vortex-induced vibration;

[0076] A height information acquisition module, used to acquire a target height of a liquid level in a TLD damper according to a vibration amplitude and a vibration frequency generated by the vortex-induced vibration within a preset monitoring time period;

[0077] The liquid level adjustment module is used to adjust the liquid level in the TLD damper according to the target height.

[0078] Beneficial effects of the present invention: By dynamically adjusting the time interval for collecting operating status information, the system can utilize resources more efficiently while ensuring timely monitoring of the key states of the wind turbine. Using the vortex-induced vibration prediction model, the system can more accurately determine whether vortex-induced vibration occurs in the wind turbine. By adjusting the liquid level in the TLD damper, the system can respond to changes in vortex-induced vibration in real time, effectively suppress vibration, and protect the stable operation of the wind turbine. The entire system realizes intelligent monitoring and regulation of wind turbines, improves the automation and intelligence level of the system, and reduces the need for manual intervention. By collecting wind information data in real time, dynamically adjusting the collection time interval, monitoring the operating status in real time, predicting vortex-induced vibration, and adjusting the liquid level of the TLD damper, intelligent monitoring and regulation of wind turbines are realized, and the operating efficiency and stability of the unit are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 A schematic diagram of a control method for vibration suppression of a wind turbine generator set;

[0080] Figure 2 The figure is a schematic diagram of a control system module for vibration suppression of a wind turbine generator set. DETAILED DESCRIPTION

[0081] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0082] In one embodiment of the present invention, a control method and system for vibration suppression of a wind turbine generator set is provided. The control method for vibration suppression of a wind turbine generator set comprises:

[0083] Collect wind information data in the current environment of the wind turbine generator set in real time, and dynamically adjust the time interval for collecting operating status information of the wind turbine generator set according to the wind information data;

[0084] Monitor the operating status of the wind turbine generator set in real time according to the operating status information collection time interval corresponding to the current moment, and obtain the operating status information of the wind turbine generator set;

[0085] Determining whether vortex-induced vibration occurs in the wind turbine generator set based on the operating status information of the wind turbine generator set and a vortex-induced vibration prediction model;

[0086] When vortex-induced vibration occurs in the wind turbine generator set, the liquid level in the TLD damper of the wind turbine generator set is height-adjusted according to vibration information of the current vortex-induced vibration.

[0087] The working principle of the above technical solution is: real-time collection of wind information data in the environment where the current wind turbine generator set is located, including key parameters such as wind speed and wind direction. The above data is collected through a sensor network and transmitted to the central processing unit for analysis. According to the collected wind information data, the time interval for collecting the operating status information of the wind turbine generator set will be dynamically adjusted. In periods when the wind is strong or changes rapidly, the collection time interval will be shortened so that possible abnormal conditions can be monitored more timely. In periods when the wind is stable or weak, the collection time interval can be appropriately extended to save resources and improve system efficiency. According to the time interval for collecting the operating status information corresponding to the current moment, the system monitors the operating status of the wind turbine generator set in real time. The monitoring content includes key indicators such as the speed, power generation, temperature, and vibration of the unit. Combined with the vortex-induced vibration prediction model, the system determines whether the unit has vortex-induced vibration based on the operating status information of the wind turbine generator set. The vortex-induced vibration prediction model is built based on a large amount of historical data and machine learning algorithms, and can accurately predict and judge the occurrence of vortex-induced vibration. When the system determines that vortex-induced vibration occurs in the wind turbine, the liquid level in the TLD damper in the unit will be adjusted according to the vibration information of the current vortex-induced vibration. The TLD damper is a tuned liquid damper. By adjusting the height of the liquid inside it, its damping characteristics can be changed, thereby effectively suppressing vortex-induced vibration.

[0088] The technical effect of the above technical solution is: by dynamically adjusting the collection time interval of the operating status information, the system can use resources more efficiently and ensure timely monitoring of the key status of the wind turbine. Using the vortex-induced vibration prediction model, the system can more accurately determine whether the wind turbine has vortex-induced vibration. By adjusting the liquid level in the TLD damper, the system can respond to the changes in vortex-induced vibration in real time, effectively suppress vibration, and protect the stable operation of the wind turbine. The entire system realizes the intelligent monitoring and control of the wind turbine, improves the automation and intelligence level of the system, and reduces the need for manual intervention. By collecting wind information data in real time, dynamically adjusting the collection time interval, monitoring the operating status in real time, predicting vortex-induced vibration, and adjusting the liquid level of the TLD damper, the intelligent monitoring and control of the wind turbine is realized, and the operating efficiency and stability of the unit are improved.

[0089] In one embodiment of the present invention, wind information data in the current environment of the wind turbine generator set is collected in real time, and the time interval for collecting the operating status information of the wind turbine generator set is dynamically adjusted according to the wind information data, including:

[0090] Real-time collection of wind information data in the environment where the current wind turbine generator set is located, wherein the wind information data includes wind speed information and wind direction change information;

[0091] Obtaining a wind state stability evaluation parameter in the current environment of the wind turbine generator set according to the wind speed information and wind direction change information;

[0092] When the wind state stability evaluation parameter is lower than a preset stability threshold, calling the current wind turbine generator set operation state information collection time interval;

[0093] The operation status information collection time interval is adjusted using a collection time interval adjustment model to obtain an adjusted operation status information collection time interval; wherein the adjusted operation status information collection time interval is obtained by the formula:

[0094]

[0095] Where T represents the adjusted operation status information collection time interval; F y represents the preset stability threshold; F represents the wind state stability evaluation parameter; T d Indicates the time interval for collecting the operating status information of the current wind turbine generator set; T c Indicates the preset initial running status information collection time interval.

[0096] The working principle of the above technical solution is: the system collects wind speed information and wind direction change information in the current environment in real time through a sensor network deployed around the wind turbine. Based on the collected wind speed information and wind direction change information, the system calculates the wind state stability evaluation parameter. The parameter comprehensively considers the fluctuation range of wind speed and the frequency of wind direction change, and can accurately reflect the stability of the current wind environment. When the wind state stability evaluation parameter is lower than the preset stability threshold, the system considers that the current wind environment is unstable and may affect the normal operation of the wind turbine. At this time, the system will call the current wind turbine operating status information collection time interval. Using the collection time interval adjustment model, the system calculates the adjusted operating status information collection time interval based on the wind state stability evaluation parameter and the current collection time interval. The model comprehensively considers the stability threshold, the current evaluation parameter, the current collection time interval and the preset initial collection time interval through a formula to ensure that the collection time interval can be shortened when the wind is unstable, thereby improving the real-time monitoring.

[0097] The technical effect of the above technical solution is: by collecting wind information data in real time and dynamically adjusting the time interval for collecting operating status information according to the stability of the wind state, the system can timely shorten the collection interval when the wind environment is unstable, ensure real-time monitoring of wind turbines, and timely discover and respond to potential operating risks. When the wind environment is relatively stable, the system can appropriately extend the collection time interval to reduce the burden of data processing, thereby optimizing the utilization of system resources and improving overall operating efficiency. Through accurate evaluation of wind state stability and intelligent adjustment of collection time intervals, the system can better adapt to complex and changeable wind environments, reduce unit operation problems caused by unstable environment, and improve the operating stability and reliability of wind turbines. This method combines multiple links such as real-time data collection, stability evaluation, and time interval adjustment to realize intelligent monitoring and control of wind turbines, improve the automation and intelligence level of the system, reduce the need for manual intervention, and improve operation and maintenance efficiency.

[0098] In one embodiment of the present invention, obtaining a wind state stability evaluation parameter in the current environment of the wind turbine generator set according to the wind speed information and the wind direction change information includes:

[0099] Extracting the wind speed information, wherein the wind speed information includes a wind speed value and a wind speed change rate per a first unit time, and the value range of the first unit time is 3 min-5 min;

[0100] The wind speed stability parameter is obtained by using the wind speed value per first unit time and the wind speed change rate; wherein the wind speed stability parameter is obtained by the following formula:

[0101]

[0102] Where S represents the wind speed stability parameter; n represents the total number of complete first unit time experienced by wind information data collection; V pi V represents the average wind speed value corresponding to the i-th first unit time; maxi represents the maximum wind speed value corresponding to the i-th first unit time; T maxi represents the duration of the maximum wind speed in the i-th first unit time; T w represents the corresponding duration of the first unit time; λ represents the wind speed stability compensation coefficient, and the wind speed stability compensation coefficient is obtained by the following formula:

[0103]

[0104] Among them, P z Indicates the comprehensive wind speed change rate from wind information data collection to the current moment; P i represents the wind speed change rate in the i-th first unit time;

[0105] Extracting the wind direction change information, wherein the wind direction change information includes the number of wind direction changes within a first unit time, the wind direction deviation angle, and the wind speed value within a preset initial time period of the wind direction change, and the value range of the preset initial time period is 1min-2min;

[0106] The wind direction stability parameter is obtained by using the number of wind direction changes in the first unit time, the wind direction deviation angle, and the wind speed value in the preset initial time period of the wind direction change; wherein the wind direction stability parameter is obtained by the following formula:

[0107]

[0108] Where X represents the wind direction stability parameter; m represents the number of wind direction changes in the first unit time; α ij represents the wind direction deviation angle corresponding to the j-th wind direction change within the i-th first unit time; P ci V represents the wind direction change rate in the first i-th unit time; hij and V xij They respectively represent the wind speed values ​​corresponding to the start time and the end time of the preset initial time period when the j-th wind direction changes within the i-th first unit time; ξ represents the wind direction stability compensation coefficient, and the wind direction stability compensation coefficient is obtained by the following formula:

[0109]

[0110] Among them, P J represents the standard deviation of the wind direction change rate corresponding to n first unit times;

[0111] The wind speed stability parameter and wind direction change information are used to obtain a wind state stability evaluation parameter; wherein the wind state stability evaluation parameter is obtained by the following formula:

[0112] F=logS+logX

[0113] Wherein, F represents the wind state stability evaluation parameter.

[0114] The working principle of the above technical solution is: extract the wind speed value and wind speed change rate per first unit time (value range is 3min-5min). The wind speed data is collected in real time through the sensor network, and extracted and calculated according to the set time interval. The wind speed value and wind speed change rate per first unit time are combined with the given formula to calculate the wind speed stability parameter. This parameter takes into account the average wind speed, maximum wind speed and its duration, and is corrected by the wind speed stability compensation coefficient to more accurately reflect the stability of the wind speed. The system further extracts wind direction change information, including the number of wind direction changes in the first unit time, the wind direction deviation angle, and the wind speed value within the preset initial time period of the wind direction change (value range is 1min-2min). The above information can reflect the frequency and intensity of wind direction changes. The wind direction stability parameter is calculated using the extracted wind direction change information in combination with the given formula. This parameter takes into account the number of wind direction changes, the deviation angle, the wind speed change rate and the wind direction stability compensation coefficient, and can comprehensively evaluate the stability of the wind direction. According to the wind speed stability parameter and wind direction stability parameter, the wind state stability evaluation parameter is calculated in combination with the given formula. This parameter is a comprehensive evaluation of the wind speed and wind direction stability, which can reflect the overall stability of the current wind environment.

[0115] The technical effect of the above technical solution is: by extracting detailed information on wind speed and wind direction, and combining multiple parameters for comprehensive calculation, the system can accurately evaluate the stability of the wind state. This helps to promptly discover unstable factors in the wind environment and provide strong support for the operation of wind turbines. By setting a reasonable first unit time and a preset initial time period, the system can reduce the burden of data collection and processing while ensuring data accuracy and improve overall efficiency. By accurately evaluating the stability of the wind state, the system can provide timely guidance and adjustment suggestions for the operation of the wind turbine, thereby improving the operational stability and reliability of the unit. This method combines multiple links such as real-time data acquisition, stability assessment, and parameter calculation to achieve intelligent monitoring and control of the operating status of wind turbines, improve the automation and intelligence level of the system, and reduce the need for manual intervention.

[0116] In one embodiment of the present invention, judging whether vortex-induced vibration occurs in the wind turbine generator set based on the operating status information of the wind turbine generator set in combination with a vortex-induced vibration prediction model includes:

[0117] Extracting the operating status information of the wind turbine generator set; wherein the operating status information includes wind speed information, wind direction information, unit speed data and vibration signal;

[0118] Performing data preprocessing on the operating status information to obtain the preprocessed operating status information, wherein the data preprocessing includes data cleaning processing, data noise reduction processing and standardization processing;

[0119] Retrieving a vortex-induced vibration prediction model for vortex-induced vibration prediction from a database; wherein the vortex-induced vibration prediction model adopts a neural network prediction model structure;

[0120] The preprocessed operating status information is input into a vortex-induced vibration prediction model, and the vortex-induced vibration prediction model is used to determine whether vortex-induced vibration occurs in the wind turbine generator set.

[0121] The working principle of the above technical solution is: extract the operating status information of the wind turbine generator set, which includes wind speed information, wind direction information, unit speed data and vibration signals. The above data reflects the current operating status of the unit and is the basis for subsequent analysis and prediction. The extracted operating status information may contain noise, outliers or data of different dimensions, so data preprocessing is required. The preprocessing steps include data cleaning processing (removing duplicate, erroneous or invalid data), data noise reduction processing (reducing random fluctuations and noise in the data), and standardization processing (converting the data to the same dimension or range for subsequent analysis). The system retrieves the pre-trained vortex-induced vibration prediction model from the database. The model adopts a neural network prediction model structure, has strong learning and generalization capabilities, and can accurately predict vortex-induced vibration based on historical data. The preprocessed operating status information is input into the vortex-induced vibration prediction model. The model automatically performs internal calculations and reasoning based on the input data, and finally outputs a judgment result, that is, whether vortex-induced vibration occurs in the wind turbine generator set.

[0122] The technical effect of the above technical scheme is: by extracting comprehensive operating status information and performing data preprocessing, the system can eliminate noise and outliers in the data, improve data quality, and thus enhance the accuracy of vortex-induced vibration prediction. The system can monitor the operating status of the wind turbine in real time, and timely determine whether the unit has vortex-induced vibration through the vortex-induced vibration prediction model. Once vortex-induced vibration is found, the system can immediately issue an early warning to remind the operation and maintenance personnel to take corresponding measures to avoid potential operating risks. Through intelligent vortex-induced vibration prediction, the system can reduce unnecessary inspections and maintenance times and reduce operation and maintenance costs. Through real-time monitoring and prediction of vortex-induced vibration, the system can timely discover and respond to potential operating problems, improve the operating stability and reliability of the wind turbine, and extend the service life of the unit. This method realizes real-time monitoring and early warning of vortex-induced vibration of wind turbines by extracting operating status information, performing data preprocessing, calling vortex-induced vibration prediction models, and judging vortex-induced vibrations, thereby improving the operating stability and reliability of the unit.

[0123] In one embodiment of the present invention, when vortex-induced vibration occurs in the wind turbine generator set, the liquid level in the TLD damper of the wind turbine generator set is adjusted according to the vibration information of the current vortex-induced vibration, including:

[0124] When vortex-induced vibration occurs in the wind turbine generator set, the vibration amplitude and vibration frequency generated within a preset monitoring time period at the start time of the vortex-induced vibration are extracted;

[0125] The target height of the liquid level in the TLD damper is obtained according to the vibration amplitude and vibration frequency generated by the vortex-induced vibration within a preset monitoring time period; wherein the target height is obtained by the following formula:

[0126]

[0127] Wherein, H represents the target height of the liquid level; A represents the average vibration amplitude of the vortex-induced vibration; f represents the average vibration frequency of the vortex-induced vibration; m represents the mass of the current liquid; ρ represents the liquid density; g represents the gravitational acceleration; σ represents the liquid viscosity; S represents the liquid surface cross-sectional area of ​​the liquid in the TLD damper in a static state; v represents the movement speed of the liquid in the TLD damper; t represents the time period from the start time of the vortex-induced vibration of the TLD damper to the end time of the vortex-induced vibration; ξ represents the liquid level compensation coefficient; and the liquid level compensation coefficient is obtained by the following formula:

[0128]

[0129] Among them, A max and A min They represent the maximum vibration amplitude and the minimum vibration amplitude in the vortex-induced vibration process respectively; v max and v min They represent the liquid velocity corresponding to the maximum vibration amplitude and the minimum vibration amplitude in the vortex-induced vibration process; r represents the number of unit times experienced in the vortex-induced vibration process, and the unit time is 1s; f 0i represents the target vibration frequency corresponding to the i-th unit time; f i Indicates the actual vibration frequency corresponding to the i-th unit time; k 01 and k 02 represent the first adjustment coefficient and the second adjustment coefficient respectively, and the first adjustment coefficient and the second adjustment coefficient are obtained by the following formula:

[0130]

[0131] Among them, S max Indicates the maximum cross-sectional area of ​​the liquid surface during vortex-induced vibration; S i represents the liquid surface cross-sectional area corresponding to the i-th unit time; v i represents the liquid velocity corresponding to the i-th unit time;

[0132] The fluid level in the TLD damper is adjusted according to the target height.

[0133] The working principle of the above technical solution is: when vortex-induced vibration occurs in the wind turbine generator set, the system will immediately respond and extract the vibration amplitude and vibration frequency within the preset monitoring time period at the start time of the vortex-induced vibration. The above vibration information is the key basis for evaluating the severity of vortex-induced vibration and determining the adjustment strategy of the TLD damper. Based on the extracted vibration amplitude and vibration frequency, the system uses a preset algorithm or model to calculate the target height of the liquid level in the TLD damper. The TLD damper is a tuned liquid damper. By adjusting the height of the liquid inside it, its damping characteristics can be changed, thereby achieving effective suppression of vortex-induced vibration. According to the calculated target height, the system will control the adjustment mechanism of the TLD damper to adjust the liquid level in the damper. By accurately controlling the liquid level height, it can be ensured that the TLD damper can play the best damping effect when vortex-induced vibration occurs, reducing the vibration amplitude and frequency of the unit.

[0134] The technical effect of the above technical solution is that the system can respond quickly when vortex-induced vibration occurs in the wind turbine generator set, extract vibration information in real time and calculate the target height of the TLD damper. This real-time performance ensures that the system can make timely adjustments to the current vortex-induced vibration conditions and improve the vibration suppression effect. By accurately calculating the target height of the TLD damper and accurately adjusting the liquid level, the system can effectively suppress vortex-induced vibration. This can not only reduce the vibration amplitude and frequency of the unit, reduce the risk of structural fatigue and damage, but also improve the operating stability and reliability of the wind turbine generator set. By timely suppressing vortex-induced vibration, the system can reduce energy loss and downtime caused by vibration, thereby improving the operating efficiency of the wind turbine generator set. This not only helps to reduce operation and maintenance costs, but also increases the power generation of the unit and improves economic benefits. This method combines multiple links such as real-time vibration monitoring and TLD damper control to realize intelligent processing of vortex-induced vibration of wind turbine generator sets. By automatically adjusting the liquid level of the TLD damper, the system can reduce dependence on manual intervention and improve operation and maintenance efficiency and intelligence level.

[0135] On the other hand, when vortex-induced vibration occurs in the wind turbine generator set, the system can extract the vibration amplitude and frequency information of the vortex-induced vibration in real time. Based on the above information, the system can dynamically calculate the target height of the liquid level in the TLD damper and quickly adjust the liquid level. The calculation of the target height is based on the actual characteristics of the vortex-induced vibration (such as average vibration amplitude and frequency), which ensures the pertinence and effectiveness of the damper adjustment. The introduction of the liquid level compensation coefficient takes into account the changing characteristics during the vortex-induced vibration process, making the adjustment more precise and accurate. At the same time, by adjusting the liquid level height in the TLD damper, the damping effect of the damper can be optimized so that it can better adapt to and suppress vortex-induced vibration. The optimized damping effect helps to protect the wind turbine generator set from damage by vortex-induced vibration and improve the reliability and service life of the fan. The above formulas and steps in the technical solution of this embodiment take into account various factors in the vortex-induced vibration process (such as vibration amplitude, frequency, liquid mass, density, viscosity, etc.), so that it can adapt to different vortex-induced vibration scenarios. By introducing adjustment coefficients (such as the first adjustment coefficient and the second adjustment coefficient), the damping effect can be further adjusted and optimized to adapt to different needs and conditions. At the same time, the liquid level height obtained in the above technical solution can effectively suppress vortex-induced vibration, thereby reducing the downtime and maintenance cost of the fan, thereby improving energy utilization efficiency. At the same time, the optimized damping effect can also reduce the energy loss of the fan during vibration, further improving energy conversion efficiency.

[0136] In summary, the above technical solution achieves effective suppression of vortex-induced vibration of wind turbines and optimizes the damping effect by accurately calculating and adjusting the liquid level height in the TLD damper, thereby improving the reliability and energy efficiency of the wind turbine.

[0137] In one embodiment of the present invention, the control system for vibration suppression of a wind turbine generator set comprises:

[0138] A collection interval adjustment module is used to collect wind information data in the environment where the wind turbine generator set is currently located in real time, and dynamically adjust the time interval for collecting the operating status information of the wind turbine generator set according to the wind information data;

[0139] An operation status monitoring module is used to monitor the operation status of the wind turbine generator set in real time according to the operation status information collection time interval corresponding to the current moment, and obtain the operation status information of the wind turbine generator set;

[0140] A vortex-induced vibration judgment module, used to judge whether vortex-induced vibration occurs in the wind turbine generator set according to the operating status information of the wind turbine generator set in combination with a vortex-induced vibration prediction model;

[0141] The vibration adjustment module is used to adjust the height of the liquid level in the TLD damper of the wind turbine generator set according to the vibration information of the current vortex-induced vibration when the wind turbine generator set has vortex-induced vibration.

[0142] The working principle of the above technical solution is: real-time collection of wind information data in the environment where the current wind turbine generator set is located, including key parameters such as wind speed and wind direction. The above data is collected through a sensor network and transmitted to the central processing unit for analysis. According to the collected wind information data, the time interval for collecting the operating status information of the wind turbine generator set will be dynamically adjusted. In periods when the wind is strong or changes rapidly, the collection time interval will be shortened so that possible abnormal conditions can be monitored more timely. In periods when the wind is stable or weak, the collection time interval can be appropriately extended to save resources and improve system efficiency. According to the time interval for collecting the operating status information corresponding to the current moment, the system monitors the operating status of the wind turbine generator set in real time. The monitoring content includes key indicators such as the speed, power generation, temperature, and vibration of the unit. Combined with the vortex-induced vibration prediction model, the system determines whether the unit has vortex-induced vibration based on the operating status information of the wind turbine generator set. The vortex-induced vibration prediction model is built based on a large amount of historical data and machine learning algorithms, and can accurately predict and judge the occurrence of vortex-induced vibration. When the system determines that vortex-induced vibration occurs in the wind turbine, the liquid level in the TLD damper in the unit will be adjusted according to the vibration information of the current vortex-induced vibration. The TLD damper is a tuned liquid damper. By adjusting the height of the liquid inside it, its damping characteristics can be changed, thereby effectively suppressing vortex-induced vibration.

[0143] The technical effect of the above technical solution is: by dynamically adjusting the collection time interval of the operating status information, the system can use resources more efficiently and ensure timely monitoring of the key status of the wind turbine. Using the vortex-induced vibration prediction model, the system can more accurately determine whether the wind turbine has vortex-induced vibration. By adjusting the liquid level in the TLD damper, the system can respond to the changes in vortex-induced vibration in real time, effectively suppress vibration, and protect the stable operation of the wind turbine. The entire system realizes the intelligent monitoring and control of the wind turbine, improves the automation and intelligence level of the system, and reduces the need for manual intervention. By collecting wind information data in real time, dynamically adjusting the collection time interval, monitoring the operating status in real time, predicting vortex-induced vibration, and adjusting the liquid level of the TLD damper, the intelligent monitoring and control of the wind turbine is realized, and the operating efficiency and stability of the unit are improved.

[0144] In one embodiment of the present invention, the collection interval adjustment module includes:

[0145] A data acquisition module is used to collect wind information data in the environment where the current wind turbine generator set is located in real time, wherein the wind information data includes wind speed information and wind direction change information;

[0146] A parameter acquisition module, used to acquire a wind state stability evaluation parameter in the current environment of the wind turbine generator set according to the wind speed information and wind direction change information;

[0147] An interval retrieving module, used for retrieving the time interval for collecting the operating status information of the current wind turbine generator set when the wind state stability evaluation parameter is lower than a preset stability threshold;

[0148] The time interval calculation module is used to adjust the operation status information collection time interval by using the collection time interval adjustment model to obtain the adjusted operation status information collection time interval; wherein the adjusted operation status information collection time interval is obtained by the formula:

[0149]

[0150] Where T represents the adjusted operation status information collection time interval; F y represents the preset stability threshold; F represents the wind state stability evaluation parameter; T d Indicates the time interval for collecting the operating status information of the current wind turbine generator set; T c Indicates the preset initial running status information collection time interval.

[0151] The working principle of the above technical solution is: the system collects wind speed information and wind direction change information in the current environment in real time through a sensor network deployed around the wind turbine. Based on the collected wind speed information and wind direction change information, the system calculates the wind state stability evaluation parameter. The parameter comprehensively considers the fluctuation range of wind speed and the frequency of wind direction change, and can accurately reflect the stability of the current wind environment. When the wind state stability evaluation parameter is lower than the preset stability threshold, the system considers that the current wind environment is unstable and may affect the normal operation of the wind turbine. At this time, the system will call the current wind turbine operating status information collection time interval. Using the collection time interval adjustment model, the system calculates the adjusted operating status information collection time interval based on the wind state stability evaluation parameter and the current collection time interval. The model comprehensively considers the stability threshold, the current evaluation parameter, the current collection time interval and the preset initial collection time interval through a formula to ensure that the collection time interval can be shortened when the wind is unstable, thereby improving the real-time monitoring.

[0152] The technical effect of the above technical solution is: by collecting wind information data in real time and dynamically adjusting the time interval for collecting operating status information according to the stability of the wind state, the system can timely shorten the collection interval when the wind environment is unstable, ensure real-time monitoring of wind turbines, and timely discover and respond to potential operating risks. When the wind environment is relatively stable, the system can appropriately extend the collection time interval to reduce the burden of data processing, thereby optimizing the utilization of system resources and improving overall operating efficiency. Through accurate evaluation of wind state stability and intelligent adjustment of collection time intervals, the system can better adapt to complex and changeable wind environments, reduce unit operation problems caused by unstable environment, and improve the operating stability and reliability of wind turbines. This method combines multiple links such as real-time data collection, stability evaluation, and time interval adjustment to realize intelligent monitoring and control of wind turbines, improve the automation and intelligence level of the system, reduce the need for manual intervention, and improve operation and maintenance efficiency.

[0153] In one embodiment of the present invention, obtaining a wind state stability evaluation parameter in the current environment of the wind turbine generator set according to the wind speed information and the wind direction change information includes:

[0154] A wind speed extraction module, used to extract the wind speed information, wherein the wind speed information includes a wind speed value and a wind speed change rate per a first unit time, and the value range of the first unit time is 3 min-5 min;

[0155] A wind speed parameter calculation module is used to obtain a wind speed stability parameter using the wind speed value per first unit time and the wind speed change rate; wherein the wind speed stability parameter is obtained by the following formula:

[0156]

[0157] Where S represents the wind speed stability parameter; n represents the total number of complete first unit time experienced by wind information data collection; V pi V represents the average wind speed value corresponding to the i-th first unit time; maxi represents the maximum wind speed value corresponding to the i-th first unit time; T maxi represents the duration of the maximum wind speed in the i-th first unit time; T w represents the corresponding duration of the first unit time; λ represents the wind speed stability compensation coefficient, and the wind speed stability compensation coefficient is obtained by the following formula:

[0158]

[0159] Among them, P z Indicates the comprehensive wind speed change rate from wind information data collection to the current moment; P irepresents the wind speed change rate in the i-th first unit time;

[0160] A wind direction extraction module, used to extract the wind direction change information, wherein the wind direction change information includes the number of wind direction changes within a first unit time, the wind direction deviation angle, and the wind speed value within a preset initial time period of the wind direction change, and the value range of the preset initial time period is 1min-2min;

[0161] The wind direction parameter calculation module is used to obtain the wind direction stability parameter by using the number of wind direction changes in the first unit time, the wind direction deviation angle and the wind speed value in the preset initial time period of the wind direction change; wherein the wind direction stability parameter is obtained by the following formula:

[0162]

[0163] Where X represents the wind direction stability parameter; m represents the number of wind direction changes in the first unit time; α ij represents the wind direction deviation angle corresponding to the j-th wind direction change within the i-th first unit time; P ci V represents the wind direction change rate in the first i-th unit time; hij and V xij They respectively represent the wind speed values ​​corresponding to the start time and the end time of the preset initial time period when the j-th wind direction changes within the i-th first unit time; ξ represents the wind direction stability compensation coefficient, and the wind direction stability compensation coefficient is obtained by the following formula:

[0164]

[0165] Among them, P J represents the standard deviation of the wind direction change rate corresponding to n first unit times;

[0166] The wind power evaluation parameter calculation module is used to obtain the wind power state stability evaluation parameter by using the wind speed stability parameter and the wind direction change information; wherein the wind power state stability evaluation parameter is obtained by the following formula:

[0167] F=logS+logX

[0168] Wherein, F represents the wind state stability evaluation parameter.

[0169] The working principle of the above technical solution is: extract the wind speed value and wind speed change rate per first unit time (value range is 3min-5min). The wind speed data is collected in real time through the sensor network, and extracted and calculated according to the set time interval. The wind speed value and wind speed change rate per first unit time are combined with the given formula to calculate the wind speed stability parameter. This parameter takes into account the average wind speed, maximum wind speed and its duration, and is corrected by the wind speed stability compensation coefficient to more accurately reflect the stability of the wind speed. The system further extracts wind direction change information, including the number of wind direction changes in the first unit time, the wind direction deviation angle, and the wind speed value within the preset initial time period of the wind direction change (value range is 1min-2min). The above information can reflect the frequency and intensity of wind direction changes. The wind direction stability parameter is calculated using the extracted wind direction change information in combination with the given formula. This parameter takes into account the number of wind direction changes, the deviation angle, the wind speed change rate and the wind direction stability compensation coefficient, and can comprehensively evaluate the stability of the wind direction. According to the wind speed stability parameter and wind direction stability parameter, the wind state stability evaluation parameter is calculated in combination with the given formula. This parameter is a comprehensive evaluation of the wind speed and wind direction stability, which can reflect the overall stability of the current wind environment.

[0170] The technical effect of the above technical solution is: by extracting detailed information on wind speed and wind direction, and combining multiple parameters for comprehensive calculation, the system can accurately evaluate the stability of the wind state. This helps to promptly discover unstable factors in the wind environment and provide strong support for the operation of wind turbines. By setting a reasonable first unit time and a preset initial time period, the system can reduce the burden of data collection and processing while ensuring data accuracy and improve overall efficiency. By accurately evaluating the stability of the wind state, the system can provide timely guidance and adjustment suggestions for the operation of the wind turbine, thereby improving the operational stability and reliability of the unit. This method combines multiple links such as real-time data acquisition, stability assessment, and parameter calculation to achieve intelligent monitoring and control of the operating status of wind turbines, improve the automation and intelligence level of the system, and reduce the need for manual intervention.

[0171] In one embodiment of the present invention, the vortex-induced vibration judgment module includes:

[0172] An operation information extraction module, used to extract the operation status information of the wind turbine generator set; wherein the operation status information includes wind speed information, wind direction information, unit speed data and vibration signal;

[0173] A preprocessing module, used to perform data preprocessing on the operating status information to obtain the preprocessed operating status information, wherein the data preprocessing includes data cleaning processing, data noise reduction processing and standardization processing;

[0174] A model retrieval module is used to retrieve a vortex-induced vibration prediction model for vortex-induced vibration prediction from a database; wherein the vortex-induced vibration prediction model adopts a neural network prediction model structure;

[0175] The model judgment module is used to input the preprocessed operating status information into the vortex-induced vibration prediction model, and judge whether the wind turbine generator set has vortex-induced vibration through the vortex-induced vibration prediction model.

[0176] The working principle of the above technical solution is: extract the operating status information of the wind turbine generator set, which includes wind speed information, wind direction information, unit speed data and vibration signals. The above data reflects the current operating status of the unit and is the basis for subsequent analysis and prediction. The extracted operating status information may contain noise, outliers or data of different dimensions, so data preprocessing is required. The preprocessing steps include data cleaning processing (removing duplicate, erroneous or invalid data), data noise reduction processing (reducing random fluctuations and noise in the data), and standardization processing (converting the data to the same dimension or range for subsequent analysis). The system retrieves the pre-trained vortex-induced vibration prediction model from the database. The model adopts a neural network prediction model structure, has strong learning and generalization capabilities, and can accurately predict vortex-induced vibration based on historical data. The preprocessed operating status information is input into the vortex-induced vibration prediction model. The model automatically performs internal calculations and reasoning based on the input data, and finally outputs a judgment result, that is, whether vortex-induced vibration occurs in the wind turbine generator set.

[0177] The technical effect of the above technical scheme is: by extracting comprehensive operating status information and performing data preprocessing, the system can eliminate noise and outliers in the data, improve data quality, and thus enhance the accuracy of vortex-induced vibration prediction. The system can monitor the operating status of the wind turbine in real time, and timely determine whether the unit has vortex-induced vibration through the vortex-induced vibration prediction model. Once vortex-induced vibration is found, the system can immediately issue an early warning to remind the operation and maintenance personnel to take corresponding measures to avoid potential operating risks. Through intelligent vortex-induced vibration prediction, the system can reduce unnecessary inspections and maintenance times and reduce operation and maintenance costs. Through real-time monitoring and prediction of vortex-induced vibration, the system can timely discover and respond to potential operating problems, improve the operating stability and reliability of the wind turbine, and extend the service life of the unit. This method realizes real-time monitoring and early warning of vortex-induced vibration of wind turbines by extracting operating status information, performing data preprocessing, calling vortex-induced vibration prediction models, and judging vortex-induced vibrations, thereby improving the operating stability and reliability of the unit.

[0178] In one embodiment of the present invention, the vibration adjustment module includes:

[0179] A vibration information extraction module, used for extracting the vibration amplitude and vibration frequency generated within a preset monitoring time period from the start time of the vortex-induced vibration when the wind turbine generator set generates vortex-induced vibration;

[0180] A height information acquisition module, used to acquire a target height of a liquid level in a TLD damper according to a vibration amplitude and a vibration frequency generated by the vortex-induced vibration within a preset monitoring time period;

[0181] The liquid level adjustment module is used to adjust the liquid level in the TLD damper according to the target height.

[0182] The working principle of the above technical solution is: when vortex-induced vibration occurs in the wind turbine generator set, the system will immediately respond and extract the vibration amplitude and vibration frequency within the preset monitoring time period at the start time of the vortex-induced vibration. The above vibration information is the key basis for evaluating the severity of vortex-induced vibration and determining the adjustment strategy of the TLD damper. Based on the extracted vibration amplitude and vibration frequency, the system uses a preset algorithm or model to calculate the target height of the liquid level in the TLD damper. The TLD damper is a tuned liquid damper. By adjusting the height of the liquid inside it, its damping characteristics can be changed, thereby achieving effective suppression of vortex-induced vibration. According to the calculated target height, the system will control the adjustment mechanism of the TLD damper to adjust the liquid level in the damper. By accurately controlling the liquid level height, it can be ensured that the TLD damper can play the best damping effect when vortex-induced vibration occurs, reducing the vibration amplitude and frequency of the unit.

[0183] The technical effect of the above technical solution is that the system can respond quickly when vortex-induced vibration occurs in the wind turbine generator set, extract vibration information in real time and calculate the target height of the TLD damper. This real-time performance ensures that the system can make timely adjustments to the current vortex-induced vibration conditions and improve the vibration suppression effect. By accurately calculating the target height of the TLD damper and accurately adjusting the liquid level, the system can effectively suppress vortex-induced vibration. This can not only reduce the vibration amplitude and frequency of the unit, reduce the risk of structural fatigue and damage, but also improve the operating stability and reliability of the wind turbine generator set. By timely suppressing vortex-induced vibration, the system can reduce energy loss and downtime caused by vibration, thereby improving the operating efficiency of the wind turbine generator set. This not only helps to reduce operation and maintenance costs, but also increases the power generation of the unit and improves economic benefits. This method combines multiple links such as real-time vibration monitoring and TLD damper control to realize intelligent processing of vortex-induced vibration of wind turbine generator sets. By automatically adjusting the liquid level of the TLD damper, the system can reduce dependence on manual intervention and improve operation and maintenance efficiency and intelligence level.

[0184] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if the above-mentioned modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include the above-mentioned modifications and variations.

Claims

1. A control method for vibration suppression of a wind turbine generator set, characterized in that: The control method for vibration suppression of a wind turbine generator set comprises: Collect wind information data in the current environment of the wind turbine generator set in real time, and dynamically adjust the time interval for collecting operating status information of the wind turbine generator set according to the wind information data; Monitor the operating status of the wind turbine generator set in real time according to the operating status information collection time interval corresponding to the current moment, and obtain the operating status information of the wind turbine generator set; Determining whether vortex-induced vibration occurs in the wind turbine generator set based on the operating status information of the wind turbine generator set and a vortex-induced vibration prediction model; When vortex-induced vibration occurs in the wind turbine generator set, the liquid level in the TLD damper of the wind turbine generator set is height-adjusted according to vibration information of the current vortex-induced vibration.

2. The control method for vibration suppression of a wind turbine generator set according to claim 1, characterized in that: Collecting wind information data in the current environment of the wind turbine generator set in real time, and dynamically adjusting the time interval for collecting operating status information of the wind turbine generator set according to the wind information data, including: Real-time collection of wind information data in the environment where the current wind turbine generator set is located, wherein the wind information data includes wind speed information and wind direction change information; Obtaining a wind state stability evaluation parameter in the current environment of the wind turbine generator set according to the wind speed information and wind direction change information; When the wind state stability evaluation parameter is lower than a preset stability threshold, calling the current wind turbine generator set operation state information collection time interval; The operation status information collection time interval is adjusted using a collection time interval adjustment model to obtain an adjusted operation status information collection time interval; wherein the adjusted operation status information collection time interval is obtained by the formula: Where T represents the adjusted operation status information collection time interval; F y represents the preset stability threshold; F represents the wind state stability evaluation parameter; T d Indicates the time interval for collecting the operating status information of the current wind turbine generator set; T c Indicates the preset initial running status information collection time interval.

3. The control method for wind turbine vibration suppression according to claim 2, characterized in that: The wind state stability evaluation parameters in the current environment of the wind turbine generator set are obtained according to the wind speed information and the wind direction change information, including: Extracting the wind speed information, wherein the wind speed information includes a wind speed value and a wind speed change rate per a first unit time, and the value range of the first unit time is 3 min-5 min; The wind speed stability parameter is obtained by using the wind speed value per first unit time and the wind speed change rate; wherein the wind speed stability parameter is obtained by the following formula: Where S represents the wind speed stability parameter; n represents the total number of complete first unit time experienced by wind information data collection; V pi V represents the average wind speed value corresponding to the i-th first unit time; maxi represents the maximum wind speed value corresponding to the i-th first unit time; T maxi represents the duration of the maximum wind speed in the i-th first unit time; T w represents the corresponding duration of the first unit time; λ represents the wind speed stability compensation coefficient, and the wind speed stability compensation coefficient is obtained by the following formula: Among them, P z Indicates the comprehensive wind speed change rate from wind information data collection to the current moment; P i represents the wind speed change rate in the i-th first unit time; Extracting the wind direction change information, wherein the wind direction change information includes the number of wind direction changes within a first unit time, the wind direction deviation angle, and the wind speed value within a preset initial time period of the wind direction change, and the value range of the preset initial time period is 1min-2min; The wind direction stability parameter is obtained by using the number of wind direction changes in the first unit time, the wind direction deviation angle, and the wind speed value in the preset initial time period of the wind direction change; wherein the wind direction stability parameter is obtained by the following formula: Where X represents the wind direction stability parameter; m represents the number of wind direction changes in the first unit time; α ij represents the wind direction deviation angle corresponding to the j-th wind direction change within the i-th first unit time; P ci V represents the wind direction change rate in the first i-th unit time; hij and V xij They respectively represent the wind speed values ​​corresponding to the start time and the end time of the preset initial time period when the j-th wind direction changes within the i-th first unit time; ξ represents the wind direction stability compensation coefficient, and the wind direction stability compensation coefficient is obtained by the following formula: Among them, P J represents the standard deviation of the wind direction change rate corresponding to n first unit times; The wind speed stability parameter and wind direction change information are used to obtain a wind state stability evaluation parameter; wherein the wind state stability evaluation parameter is obtained by the following formula: F=logS+logX Wherein, F represents the wind state stability evaluation parameter.

4. The control method for wind turbine vibration suppression according to claim 1, characterized in that: Determining whether vortex-induced vibration occurs in the wind turbine generator set according to the operating state information of the wind turbine generator set in combination with a vortex-induced vibration prediction model includes: Extracting the operating status information of the wind turbine generator set; wherein the operating status information includes wind speed information, wind direction information, unit speed data and vibration signal; Performing data preprocessing on the operating status information to obtain the preprocessed operating status information, wherein the data preprocessing includes data cleaning processing, data noise reduction processing and standardization processing; Retrieving a vortex-induced vibration prediction model for vortex-induced vibration prediction from a database; wherein the vortex-induced vibration prediction model adopts a neural network prediction model structure; The preprocessed operating status information is input into a vortex-induced vibration prediction model, and the vortex-induced vibration prediction model is used to determine whether vortex-induced vibration occurs in the wind turbine generator set.

5. The control method for wind turbine vibration suppression according to claim 1, characterized in that: When the wind turbine generator set generates vortex-induced vibration, the liquid level in the TLD damper of the wind turbine generator set is adjusted according to the vibration information of the current vortex-induced vibration, including: When vortex-induced vibration occurs in the wind turbine generator set, the vibration amplitude and vibration frequency generated within a preset monitoring time period at the start time of the vortex-induced vibration are extracted; Obtaining a target height of the liquid level in the TLD damper according to the vibration amplitude and vibration frequency generated by the vortex-induced vibration within a preset monitoring time period; The fluid level in the TLD damper is adjusted according to the target height.

6. A control system for vibration suppression of a wind turbine generator set, characterized in that: The control system for wind turbine generator set vibration suppression includes: A collection interval adjustment module is used to collect wind information data in the environment where the wind turbine generator set is currently located in real time, and dynamically adjust the time interval for collecting the operating status information of the wind turbine generator set according to the wind information data; An operation status monitoring module is used to monitor the operation status of the wind turbine generator set in real time according to the operation status information collection time interval corresponding to the current moment, and obtain the operation status information of the wind turbine generator set; A vortex-induced vibration judgment module, used to judge whether vortex-induced vibration occurs in the wind turbine generator set according to the operating status information of the wind turbine generator set in combination with a vortex-induced vibration prediction model; The vibration adjustment module is used to adjust the height of the liquid level in the TLD damper of the wind turbine generator set according to the vibration information of the current vortex-induced vibration when the wind turbine generator set has vortex-induced vibration.

7. The control system for wind turbine vibration suppression according to claim 6, characterized in that: The acquisition interval adjustment module includes: A data acquisition module is used to collect wind information data in the environment where the current wind turbine generator set is located in real time, wherein the wind information data includes wind speed information and wind direction change information; A parameter acquisition module, used to acquire a wind state stability evaluation parameter in the current environment of the wind turbine generator set according to the wind speed information and wind direction change information; An interval retrieving module, used for retrieving the time interval for collecting the operating status information of the current wind turbine generator set when the wind state stability evaluation parameter is lower than a preset stability threshold; The time interval calculation module is used to adjust the operation status information collection time interval by using the collection time interval adjustment model to obtain the adjusted operation status information collection time interval; wherein the adjusted operation status information collection time interval is obtained by the formula: Where T represents the adjusted operation status information collection time interval; F y represents the preset stability threshold; F represents the wind state stability evaluation parameter; T d Indicates the time interval for collecting the operating status information of the current wind turbine generator set; T c Indicates the preset initial running status information collection time interval.

8. The control system for wind turbine vibration suppression according to claim 7, characterized in that: The wind state stability evaluation parameters in the current environment of the wind turbine generator set are obtained according to the wind speed information and the wind direction change information, including: A wind speed extraction module, used to extract the wind speed information, wherein the wind speed information includes a wind speed value and a wind speed change rate per a first unit time, and the value range of the first unit time is 3 min-5 min; A wind speed parameter calculation module is used to obtain a wind speed stability parameter using the wind speed value per first unit time and the wind speed change rate; wherein the wind speed stability parameter is obtained by the following formula: Where S represents the wind speed stability parameter; n represents the total number of complete first unit time experienced by wind information data collection; V pi V represents the average wind speed value corresponding to the i-th first unit time; maxi represents the maximum wind speed value corresponding to the i-th first unit time; T maxi represents the duration of the maximum wind speed in the i-th first unit time; T w represents the corresponding duration of the first unit time; λ represents the wind speed stability compensation coefficient, and the wind speed stability compensation coefficient is obtained by the following formula: Among them, P z Indicates the comprehensive wind speed change rate from wind information data collection to the current moment; P i represents the wind speed change rate in the i-th first unit time; A wind direction extraction module, used to extract the wind direction change information, wherein the wind direction change information includes the number of wind direction changes within a first unit time, the wind direction deviation angle, and the wind speed value within a preset initial time period of the wind direction change, and the value range of the preset initial time period is 1min-2min; The wind direction parameter calculation module is used to obtain the wind direction stability parameter by using the number of wind direction changes in the first unit time, the wind direction deviation angle and the wind speed value in the preset initial time period of the wind direction change; wherein the wind direction stability parameter is obtained by the following formula: Where X represents the wind direction stability parameter; m represents the number of wind direction changes in the first unit time; α ij represents the wind direction deviation angle corresponding to the j-th wind direction change within the i-th first unit time; P ci V represents the wind direction change rate in the first i-th unit time; hij and V xij They respectively represent the wind speed values ​​corresponding to the start time and the end time of the preset initial time period when the j-th wind direction changes within the i-th first unit time; ξ represents the wind direction stability compensation coefficient, and the wind direction stability compensation coefficient is obtained by the following formula: Among them, P J represents the standard deviation of the wind direction change rate corresponding to n first unit times; The wind power evaluation parameter calculation module is used to obtain the wind power state stability evaluation parameter by using the wind speed stability parameter and the wind direction change information; wherein the wind power state stability evaluation parameter is obtained by the following formula: F=logS+logX Wherein, F represents the wind state stability evaluation parameter.

9. The control system for wind turbine vibration suppression according to claim 6, characterized in that: The vortex-induced vibration judgment module includes: An operation information extraction module, used to extract the operation status information of the wind turbine generator set; wherein the operation status information includes wind speed information, wind direction information, unit speed data and vibration signal; A preprocessing module, used to perform data preprocessing on the operating status information to obtain the preprocessed operating status information, wherein the data preprocessing includes data cleaning processing, data noise reduction processing and standardization processing; A model retrieval module is used to retrieve a vortex-induced vibration prediction model for vortex-induced vibration prediction from a database; wherein the vortex-induced vibration prediction model adopts a neural network prediction model structure; The model judgment module is used to input the preprocessed operating status information into the vortex-induced vibration prediction model, and judge whether the wind turbine generator set has vortex-induced vibration through the vortex-induced vibration prediction model.

10. The control system for wind turbine vibration suppression according to claim 6, characterized in that: The vibration adjustment module includes: A vibration information extraction module, used for extracting the vibration amplitude and vibration frequency generated within a preset monitoring time period from the start time of the vortex-induced vibration when the wind turbine generator set generates vortex-induced vibration; A height information acquisition module, used to acquire a target height of a liquid level in a TLD damper according to a vibration amplitude and a vibration frequency generated by the vortex-induced vibration within a preset monitoring time period; The liquid level adjustment module is used to adjust the liquid level in the TLD damper according to the target height.

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