Wind generating set load dynamic prediction method based on wind direction change

Abstract

The invention provides a wind turbine generator system load dynamic prediction method based on wind direction change, and relates to the technical field of wind turbine generator system load prediction, and the method comprises the steps: collecting a real-time wind direction and a real-time wind speed; unit operation parameters are obtained; constructing a load prediction model according to the historical wind direction, the historical wind speed and the historical load data; inputting the real-time wind direction, the real-time wind speed and the unit operation parameters into a load prediction model to generate a load change; and adjusting unit operation parameters according to the load change. The technical problem that in the prior art, deep correlation analysis on multiple parameters such as the wind speed, the wind direction and the load is lacked, and consequently the stability of power output of the wind generating set and equipment are affected can be solved, and the technical purposes of real-time correlation analysis and intelligent adjustment on the wind speed, the wind direction and the load are achieved; the technical effects of timely responding to the wind environment change, improving the power output stability and ensuring the safe operation of the wind generating set are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of wind turbine load prediction, and in particular to a method for dynamically predicting wind turbine load based on wind direction changes. Background Art

[0002] As the global demand for renewable energy continues to increase, wind power generation has been widely used as a clean energy source. During the operation of wind turbines, their output power is affected by many factors, the most critical of which are changes in wind speed and wind direction. In order to optimize power generation efficiency and ensure the long-term stable operation of equipment, the operation of wind turbines requires real-time monitoring of various parameters, such as wind speed, wind direction, unit load, etc.

[0003] At present, the existing wind power control system collects real-time data through wind speed and wind direction sensors, and adjusts the power output of the generator set accordingly based on this data. However, most of the existing control systems use preset fixed parameters for adjustment, lacking in-depth correlation analysis of multiple parameters such as wind speed, wind direction and load. This approach ignores the complexity and instantaneous variability of the wind environment. Especially when the wind speed and wind direction change sharply, the system response is often delayed and the operating status of the unit cannot be adjusted in time, resulting in unstable power output and even equipment overload.

[0004] In summary, the existing technology has technical problems such as lack of in-depth correlation analysis of multiple parameters such as wind speed, wind direction and load, which leads to a lag in system response when wind speed and wind direction change sharply, further affecting the stability of wind turbine power output and the safe operation of the equipment. Summary of the invention

[0005] The purpose of this application is to provide a method for dynamically predicting the load of a wind turbine generator set based on wind direction changes, so as to solve the problem in the prior art that the lack of in-depth correlation analysis of multiple parameters such as wind speed, wind direction and load leads to a system response lag when the wind speed and wind direction change sharply, further affecting the stability of the power output of the wind turbine generator set and the technical problems of the equipment.

[0006] In view of the above problems, the present application provides a method for dynamic prediction of wind turbine load based on wind direction changes, including: collecting real-time wind direction and real-time wind speed; obtaining unit operating parameters, including unit speed, output power and tilt angle; constructing a load prediction model based on historical wind direction, historical wind speed and historical load data; inputting real-time wind direction, real-time wind speed and unit operating parameters into the load prediction model to generate load changes; adjusting the unit operating parameters according to the load changes.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] By collecting real-time wind direction and real-time wind speed; obtaining unit operating parameters, including unit speed, output power and tilt angle; building a load prediction model based on historical wind direction, historical wind speed and historical load data; inputting real-time wind direction, real-time wind speed and unit operating parameters into the load prediction model to generate load changes; adjusting unit operating parameters according to load changes, achieving the technical goal of real-time correlation analysis and intelligent adjustment of multiple parameters such as wind speed, wind direction and load, and achieving the technical effect of timely responding to changes in wind environment, improving power output stability and ensuring safe operation of wind turbines.

[0009] In a possible implementation, the real-time wind direction and real-time wind speed are collected, and the following processing is performed before: determining the synchronous collection parameters according to the operating status of the wind turbine generator set; configuring a multi-parameter synchronous collection module and setting a collection clock; and receiving the synchronous collection parameters through the multi-parameter synchronous collection module according to the collection clock.

[0010] In a possible implementation, an acquisition clock is set and the following processing is performed: the frequency and amplitude of the wind speed and wind direction are obtained according to the changing characteristics of the wind direction and wind speed in the area where the wind turbine generator set is located; the initial data acquisition frequency of the wind direction sensor and the wind speed sensor is set according to the frequency and amplitude; the initial data acquisition frequency is dynamically adjusted by real-time monitoring of the changing frequency and amplitude of the wind direction and wind speed to obtain the acquisition clock.

[0011] In a possible implementation, the following processing is further performed: the change characteristics include seasonal wind speed fluctuations, instantaneous strong winds, and rapid changes in wind direction.

[0012] In a possible implementation, the real-time wind direction and real-time wind speed are collected after the following processing is performed: a wind direction sensor is selected based on the wind direction change frequency and angle range of the area where the wind turbine is located; a wind speed sensor is selected based on the wind field environment of the area where the wind turbine is located; and the wind direction sensor and the wind speed sensor are arranged based on the height, terrain features and wind field characteristics of the wind turbine.

[0013] In a possible implementation, a load prediction model is constructed and the following processing is performed: an initial model is established based on the historical load data; a load correlation analysis is performed according to the historical wind direction and the historical wind speed; and the correlation analysis results are input into the initial model for training to obtain the load prediction model.

[0014] In a possible implementation, the unit operating parameters are adjusted according to the load change, and the following processing is performed: determining whether the load change exceeds a safety threshold; if it exceeds the safety threshold, reducing the unit operating power.

[0015] In a possible implementation, the unit operating parameters are adjusted, and then the following processing is performed: a warning threshold of the load is set; when the load change meets the warning threshold, a warning signal is generated; based on the warning signal, automatic load reduction of the control system is executed, and a warning notification is sent to the operation and maintenance personnel.

[0016] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0018] Figure 1 This is a flow chart of a method for dynamically predicting a load of a wind turbine generator set based on wind direction changes in this application;

[0019] Figure 2 This is a schematic diagram of the process of constructing a load prediction model in the method for dynamically predicting the load of a wind turbine generator set based on wind direction changes in this application. DETAILED DESCRIPTION

[0020] This application provides a method for dynamically predicting the load of a wind turbine generator set based on wind direction changes, thereby solving the technical problem in the prior art that the system response lags when the wind speed and wind direction change sharply, further affecting the stability of the power output of the wind turbine generator set and the technical problem of the equipment due to the lack of in-depth correlation analysis of multiple parameters such as wind speed, wind direction and load. The technical goal of real-time correlation analysis and intelligent adjustment of multiple parameters such as wind speed, wind direction and load is achieved, achieving the technical effect of timely responding to changes in the wind environment, improving the stability of power output and ensuring the safe operation of wind turbine generator sets.

[0021] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0022] Please see attached Figure 1 The present application provides a method for dynamically predicting the load of a wind turbine generator set based on wind direction changes, which specifically includes the following steps:

[0023] Step 1: Collect real-time wind direction and real-time wind speed.

[0024] Specifically, collecting real-time wind direction means continuously obtaining wind direction data through wind direction sensors to reflect the current wind direction in the area where the wind turbine is located. For example, within one second, the wind direction may change from 45 degrees north by east to 30 degrees north by west. Collecting real-time wind speed means using wind speed sensors to continuously obtain the current wind speed, for example, the wind speed increases from 10 meters per second to 15 meters per second. By simultaneously collecting real-time wind direction and wind speed data, changes in wind conditions can be more accurately monitored, thereby providing immediate feedback and adjustment basis for the operation of wind turbines.

[0025] Step 2: Obtain the unit operating parameters, including unit speed, output power and tilt angle.

[0026] Specifically, sensors are used to collect data and information related to the operating status of wind turbines, including the speed, output power and tilt angle of the unit. The speed of the unit refers to the rotation speed of the blades of the generator set, for example, the speed is 15 revolutions per minute. The output power refers to the electrical energy output generated by the unit under the current wind conditions. For example, when the wind speed reaches 12 meters per second, the unit may generate 500 kilowatts of power. The tilt angle refers to the inclination of the wind turbine relative to the vertical direction, which is usually used to adjust the posture of the unit to adapt to changes in wind direction. For example, the tilt angle of the unit is 5 degrees to optimize the windward angle.

[0027] Step 3: Construct a load prediction model based on historical wind direction, historical wind speed and historical load data.

[0028] Specifically, the wind direction, wind speed and load data of wind turbines collected over a period of time are used to establish a mathematical or computational model that can predict future load changes. The historical wind direction, wind speed and load data are collected during the long-term operation of wind turbines, covering the wind conditions and corresponding load conditions experienced by the units at different times and under different environmental conditions. The historical wind direction data includes the changes in wind direction at different times, such as the frequency and pattern of wind direction changing from north wind to southeast wind. The historical wind speed data records the changes in wind speed at different times. For example, the average wind speed in a certain area is 10 meters per second, but the wind speed may rise to 20 meters per second in certain periods. The historical load data is the power output of the unit under different wind speed and wind direction conditions. For example, when the wind speed is 12 meters per second and the wind direction is east wind, the load of the unit may be 350 Newton meters. By analyzing historical data, the load prediction model can predict future load conditions based on the current wind speed and wind direction. For example, when the current wind speed is 15 meters per second and the wind direction is northeast, the predicted load is 400 Newton meters, which helps to optimize the operating status of the unit in advance.

[0029] Step 4: Input the real-time wind direction, the real-time wind speed and the unit operating parameters into the load prediction model to generate load changes.

[0030] Specifically, the wind direction, wind speed and wind turbine operating data collected at the current moment are input into the load prediction model to calculate and predict the overall load change of the unit. Real-time wind direction refers to the direction of the current wind, for example, the wind direction at this time is southeast wind. Real-time wind speed is the current wind speed, for example, the wind speed at this moment is 12 meters per second. The unit operating parameters include the speed, output power and tilt angle of the generator set. For example, the current speed of the unit is 20 revolutions per minute, the power output is 300 kilowatts, and the tilt angle is 5 degrees. By inputting real-time data into the load prediction model, the overall load change in the future period is calculated. For example, after inputting the current data, the model predicts that in the next hour, the overall load of the unit may increase from 300 Newton meters to 350 kilowatts, and the operating status of the unit is adjusted in real time to adapt to future load requirements.

[0031] Step 5: Adjust the unit operating parameters according to the load change.

[0032] Specifically, by monitoring and predicting the load changes of wind turbines, the operating status of the units is dynamically adjusted to ensure their efficient and safe operation. Load changes refer to the fluctuation of the power output of the generator set with changes in wind speed and wind direction. For example, when the wind speed increases from 10 meters per second to 15 meters per second, the load may increase from 200 kilowatts to 300 kilowatts. The operating parameters of the unit include speed, output power, and tilt angle. For example, if the load increases, the operation is optimized by increasing the speed of the unit or adjusting the tilt angle, or when the wind speed is too high and the load is too large, the power output is reduced to protect the equipment. Specifically, if the current load is 350 kilowatts, the load is predicted to be 400 kilowatts after the wind speed increases, and the speed or tilt angle is adjusted accordingly to maintain the unit operating within a safe range.

[0033] The method for dynamically predicting the load of a wind turbine generator set based on wind direction changes can achieve the technical goal of real-time correlation analysis and intelligent adjustment of multiple parameters such as wind speed, wind direction and load, and achieve the technical effect of timely responding to changes in the wind environment, improving power output stability and ensuring the safe operation of the wind turbine generator set.

[0034] Furthermore, the present application also includes:

[0035] According to the operating status of the wind turbine generator set, synchronous acquisition parameters are determined; a multi-parameter synchronous acquisition module is configured and an acquisition clock is set; according to the acquisition clock, the synchronous acquisition parameters are received through the multi-parameter synchronous acquisition module.

[0036] Specifically, according to the operating status of the wind turbine, the key parameters that need to be collected synchronously, including the speed, output power and tilt angle of the unit, play a key role in the prediction of wind turbine load. By analyzing these parameters, we can better understand the working condition of the wind turbine and improve the accuracy of the prediction. For example, if the speed of the unit suddenly drops without a significant change in wind speed, it means that some kind of load is abnormal.

[0037] Next, configure the multi-parameter synchronous acquisition module, which can simultaneously process data from different sensors, including speed sensors, power sensors, and tilt angle sensors, to ensure synchronous operation and avoid errors caused by the time difference in data collection from different sensors. For example, in actual applications, if the speed changes significantly within 1 second and the power data is collected with a delay, the accuracy of the prediction model will be reduced, so synchronous collection is performed.

[0038] In order to ensure that the data is collected at the same time point, a unified collection clock is set. The collection clock determines that all sensors collect data in the same time period. For example, if the collection frequency is set to once per second, the collection clock will ensure that all sensors collect data synchronously at the same time every second. Clock synchronization can avoid data distortion caused by time difference.

[0039] After setting the acquisition clock, the parameters collected synchronously are received through the multi-parameter synchronous acquisition module. The data is stored temporarily through the cache technology to avoid transmission delay or loss. For example, if the speed of the unit is 15 rpm, the output power is 500 kW, and the tilt angle is 3 degrees, these data will be collected and transmitted to the model at the same time.

[0040] By reasonably determining the synchronous acquisition parameters, configuring the synchronous acquisition module and setting the acquisition clock, the multi-parameter data of the wind turbine can be synchronously acquired and transmitted to ensure the accuracy and consistency of the data. This not only improves the accuracy of wind turbine load prediction, but also effectively prevents abnormal conditions in the equipment through fast and synchronous data feedback, thereby ensuring the safe and efficient operation of the generator set.

[0041] Furthermore, the present application also includes:

[0042] According to the changing characteristics of wind direction and wind speed in the area where the wind turbine generator set is located, the frequency and amplitude of wind speed and wind direction are obtained; according to the frequency and amplitude, the initial data acquisition frequency of the wind direction sensor and the wind speed sensor is set; by real-time monitoring the changing frequency and amplitude of the wind direction and wind speed, the initial data acquisition frequency is dynamically adjusted to obtain the acquisition clock.

[0043] Specifically, the frequency and amplitude of wind speed and direction are obtained according to the wind direction and wind speed change characteristics of the area where the wind turbine is located. For example, a certain area may have obvious seasonal wind direction, while the wind speed fluctuates less over time. Therefore, the wind direction and wind speed change patterns in the area are accurately evaluated through historical data or real-time monitoring, which provides a basis for the subsequent acquisition frequency setting.

[0044] Next, according to the frequency and amplitude of the acquired wind speed and wind direction, set the initial data collection frequency of the wind direction sensor and wind speed sensor. The collection frequency refers to the time interval between sensor data recording. Rapidly changing wind speed and wind direction require a higher collection frequency to ensure real-time performance. For example, if the wind speed changes frequently, it is recommended to collect data once per second, while for wind direction data that changes more slowly, the collection frequency can be set to once every 5 seconds. With this setting, the sensor can reasonably track the changing dynamics of the wind field.

[0045] Next, by monitoring the frequency and amplitude of wind direction and wind speed changes in real time, the initial data collection frequency is dynamically adjusted to quickly respond to sudden changes in wind speed and direction, such as a sudden increase in wind speed or a sharp change in wind direction, and the collection frequency is adjusted so that the sensor can obtain data more frequently to ensure data accuracy. For example, when the wind speed rises rapidly from 10 meters per second to 20 meters per second, the collection frequency can be increased from once per second to once every half a second to ensure that important change information is not missed.

[0046] Finally, the acquisition clock is obtained through the dynamically adjusted acquisition frequency. The acquisition clock is the core time control unit that synchronizes all sensors, ensuring that wind direction and wind speed data can be collected and transmitted at appropriate time intervals, thereby ensuring the uniformity and real-time nature of the data. For example, if the acquisition clock is set to once per second, all sensors will start data collection at the same time per second, effectively improving data quality.

[0047] By analyzing the wind speed and wind direction change characteristics in the area where the wind turbines are located, the frequency and amplitude of the wind speed and wind direction are determined, and then the initial collection frequency is set based on these data. The frequency is dynamically adjusted during real-time monitoring, and finally a unified collection clock is generated to ensure the synchronization and accuracy of wind speed and wind direction data. Timely adjustments are made when wind speed and wind direction change drastically to ensure the accuracy and reliability of wind turbine load prediction.

[0048] Furthermore, the present application also includes:

[0049] The changing characteristics include seasonal wind speed fluctuations, instantaneous strong winds, and sudden changes in wind direction.

[0050] Specifically, seasonal wind speed fluctuations in the variation characteristics refer to the obvious differences in wind speed in different seasons. For example, in some areas, the wind speed is higher in winter, but relatively stable in summer. Seasonal wind speed changes will have a long-term impact on the operation of wind turbines. Therefore, when collecting data, adjusting the sensor's collection frequency according to the fluctuation characteristics can adapt to the wind speed changes in different seasons. For example, in winter, the wind speed may fluctuate by 2 to 3 meters per second per hour, while in summer it changes more steadily.

[0051] Next, instantaneous strong wind refers to the phenomenon of rapid increase in wind speed in a short period of time, such as typhoons, thunderstorms or sudden wind increase. Instantaneous strong winds put great pressure on the operation of wind turbines and easily cause equipment overload. Therefore, the frequency of data acquisition needs to be greatly increased in order to quickly capture sudden changes in wind speed. For example, when the wind speed suddenly rises from 10 meters per second to 20 meters per second, the acquisition frequency can be increased from once per second to once every half a second to ensure accurate monitoring of this instantaneous change.

[0052] In addition, a sudden change in wind direction refers to a situation where the wind direction changes at a large angle in a short period of time. In severe weather or complex terrain conditions, a sudden change in wind direction will affect the working stability of the wind turbine, so sensors are needed to track wind direction changes in real time. For example, when the wind direction changes rapidly from north wind to east wind, the frequency of data collection must be increased to ensure that the wind turbine can adjust its operating parameters in time.

[0053] By comprehensively analyzing seasonal wind speed fluctuations, instantaneous strong winds, and rapid changes in wind direction, we can fully understand the dynamic characteristics of the wind farm, rationally adjust the data collection strategy, and ensure the safe and efficient operation of wind turbines under various weather conditions.

[0054] Furthermore, the present application also includes:

[0055] A wind direction sensor is selected according to the wind direction change frequency and angle range of the area where the wind turbine is located; a wind speed sensor is selected according to the wind field environment of the area where the wind turbine is located; and the wind direction sensor and the wind speed sensor are arranged according to the height, terrain features and wind field characteristics of the wind turbine.

[0056] Specifically, select the appropriate wind direction sensor based on the frequency and angle range of wind direction changes in the area where the wind turbine is located. The frequency of wind direction changes refers to the speed of wind direction changes, while the angle range is the amplitude of wind direction deflection. For example, in an area where wind direction changes frequently, select a wind direction sensor with high sensitivity and wide angle measurement range to accurately track changes in wind direction. If the wind direction changes three times per minute and the angle range is 0 to 360 degrees, select a sensor with full-range angle detection capabilities and fast response.

[0057] Next, select a wind speed sensor based on the wind farm environment in the area where the wind turbine is located. The wind farm environment refers to the changing characteristics of wind speed and the strength of the wind in the area. If the wind speed changes dramatically in the wind farm environment, the sensor needs to have the characteristics of fast response and high precision, and be able to adapt to changes from low-speed breezes to high-speed strong winds. For example, in an area where wind speed changes frequently and strong winds suddenly occur, the sensor needs to be able to maintain high-precision measurements even when the wind speed quickly rises from 5 meters per second to 30 meters per second, so a sensor that can detect a wide range of wind speeds is selected.

[0058] Then, arrange the wind direction sensor and wind speed sensor according to the height of the wind turbine, the terrain features and the characteristics of the wind field. The placement of the sensor will directly affect the accuracy of its measurement, especially in complex terrain and high altitude areas. The wind direction sensor needs to be installed away from the airflow interference of the generator itself, while the wind speed sensor should be installed in an open area that is not blocked by obstacles and can fully reflect the wind speed. For example, if the height of the generator is 80 meters and the surrounding terrain is complex, the wind speed sensor should be arranged at the top of the tower, while the wind direction sensor can be placed on the beam away from the wind blades.

[0059] By selecting high-sensitivity, high-range sensors and arranging them in the best position based on the frequency of wind direction changes, angle range, wind field environment, and the terrain and height characteristics of the generator set, efficient operation of the wind turbine can be ensured.

[0060] For further information, please see the attached Figure 2 , this application also includes:

[0061] An initial model is established based on the historical load data; a load correlation analysis is performed according to the historical wind direction and the historical wind speed; and the correlation analysis result is input into the initial model for training to obtain the load prediction model.

[0062] Specifically, the initial model is constructed using past load data, reflecting the load changes of the generator set under different conditions. The initial model lays the foundation for further optimization and prediction.

[0063] Next, load correlation analysis based on historical wind direction and historical wind speed refers to analyzing the relationship between wind direction, wind speed and load. For example, during the analysis process, it may be found that when the wind direction changes from north-east to due north, the load decreases by 10%, or when the wind speed increases from 8 meters per second to 12 meters per second, the load increases by 20%. Through correlation analysis, the specific impact of wind direction and wind speed changes on unit load is clarified, thereby providing key data for further optimization of the model.

[0064] Then, inputting the correlation analysis results into the initial model for training means inputting the data obtained through the correlation analysis into the initial model for optimization, obtaining a load prediction model, and improving the prediction ability of the model. The process of load prediction model training is the process of continuously correcting and adjusting model parameters through a large amount of historical data. For example, after inputting a large amount of historical wind speed, wind direction and load correlation data, the load prediction model can more accurately predict the future load conditions under a certain wind speed and wind direction, and finally form an accurate load prediction model.

[0065] A preliminary model is established through historical load data, and then a detailed correlation analysis is carried out based on historical wind direction and wind speed data. Finally, these analysis results are input into the initial model for training, and ultimately a model is generated that can accurately predict the future load of the wind turbine and accurately guide the operation of the wind turbine.

[0066] Furthermore, the present application also includes:

[0067] Determine whether the load change exceeds a safety threshold; if it exceeds the safety threshold, reduce the operating power of the unit.

[0068] Specifically, judging whether the load change exceeds the safety threshold means analyzing the load change of the unit based on the real-time monitoring data to determine whether it exceeds the preset safety range. For example, the safety threshold can be set to the maximum load capacity of the unit. If the load of the unit is 500 kilowatts, and at a certain moment the load suddenly increases to 550 kilowatts, it means that the safety threshold may be exceeded. Through real-time monitoring and calculation, it is determined whether the operation of the unit is safe.

[0069] Then, if the safety threshold is exceeded, reducing the unit's operating power means that once it is detected that the load has exceeded the safety range, the control system will automatically reduce the unit's power output to protect the equipment from overload damage. By reducing the power output, the unit's operating pressure is reduced and the equipment's stability is maintained. For example, if the unit's power output is reduced from 550 kilowatts to 450 kilowatts, the equipment can continue to operate within a safe range to avoid damage or shutdown.

[0070] By judging in real time whether the load change exceeds the preset safety threshold, if it exceeds the threshold, measures are automatically taken to reduce the power output of the unit, thereby ensuring the safe operation of the wind turbine.

[0071] Furthermore, the present application also includes:

[0072] A warning threshold of the load is set; when the load change meets the warning threshold, a warning signal is generated; based on the warning signal, the control system automatically reduces the load and sends a warning notification to the operation and maintenance personnel.

[0073] Specifically, a load upper limit of a safe range is set for the wind turbine generator set, and a warning is issued when the load exceeds the range. For example, assuming that the maximum safe operating load of the unit is 500 kilowatts, an early warning is triggered when the load approaches or exceeds this value. The threshold is set based on the physical bearing capacity of the unit and historical data analysis to avoid damage to the equipment due to overload.

[0074] When the real-time monitored load reaches or exceeds the set threshold, an alarm signal is automatically generated. For example, when the wind speed suddenly increases, causing the load of the unit to rise from 450 kW to 500 kW, this change is detected and an early warning signal is generated to alert the operating system or personnel of the impending risk.

[0075] When the warning signal is triggered, the load reduction program is automatically started to reduce the load pressure by reducing the output power or adjusting the unit operating parameters, and the warning information is notified to the relevant operation and maintenance personnel. For example, when the load reaches the threshold of 500 kilowatts, the power output of the unit is reduced from 500 kilowatts to 450 kilowatts, and a notification is sent to the operation and maintenance personnel for further inspection and processing.

[0076] The safe operation of the unit is ensured by setting a warning threshold for the load. When the load approaches or exceeds this threshold, a warning signal is automatically generated, and automatic load reduction is performed based on this signal. At the same time, the operation and maintenance personnel are notified to ensure that the unit can respond in time when facing overload to avoid damage to the equipment.

[0077] In summary, the method for dynamic prediction of wind turbine load based on wind direction change provided by the present application has the following technical effects:

[0078] By collecting real-time wind direction and real-time wind speed; obtaining unit operating parameters, including unit speed, output power and tilt angle; building a load prediction model based on historical wind direction, historical wind speed and historical load data; inputting real-time wind direction, real-time wind speed and unit operating parameters into the load prediction model to generate load changes; adjusting unit operating parameters according to load changes, achieving the technical goal of real-time correlation analysis and intelligent adjustment of multiple parameters such as wind speed, wind direction and load, and achieving the technical effect of timely responding to changes in wind environment, improving power output stability and ensuring safe operation of wind turbines.

[0079] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0080] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A method for dynamic prediction of wind turbine load based on wind direction change, characterized in that: include: Collect real-time wind direction and real-time wind speed; Obtain unit operating parameters, including unit speed, output power and tilt angle; Construct a load prediction model based on historical wind direction, historical wind speed and historical load data; Inputting the real-time wind direction, the real-time wind speed and the unit operation parameters into the load prediction model to generate load changes; According to the load change, the unit operating parameters are adjusted.

2. The method for dynamic prediction of wind turbine load based on wind direction change according to claim 1, characterized in that: The acquisition of real-time wind direction and real-time wind speed previously includes: Determine the synchronous acquisition parameters according to the operating status of the wind turbine generator set; Configure the multi-parameter synchronous acquisition module and set the acquisition clock; The synchronous acquisition parameters are received by the multi-parameter synchronous acquisition module according to the acquisition clock.

3. The method for dynamic prediction of wind turbine load based on wind direction change according to claim 2, characterized in that: The step of setting the acquisition clock includes: According to the changing characteristics of wind direction and wind speed in the area where the wind turbine generator set is located, the frequency and amplitude of the wind speed and wind direction are obtained; According to the frequency and amplitude, setting the initial data collection frequency of the wind direction sensor and the wind speed sensor; The acquisition clock is obtained by dynamically adjusting the initial data acquisition frequency through real-time monitoring of the change frequency and change amplitude of the wind direction and wind speed.

4. The method for dynamic prediction of wind turbine load based on wind direction change according to claim 3, characterized in that: The changing characteristics include seasonal wind speed fluctuations, instantaneous strong winds, and sudden changes in wind direction.

5. The method for dynamic prediction of wind turbine load based on wind direction change according to claim 1, characterized in that: The collecting of real-time wind direction and real-time wind speed also includes: Select a wind direction sensor based on the wind direction change frequency and angle range in the area where the wind turbine is located; Selecting a wind speed sensor according to the wind field environment of the area where the wind turbine generator set is located; The wind direction sensor and the wind speed sensor are arranged according to the height, terrain features and wind field characteristics of the wind turbine generator set.

6. The method for dynamic prediction of wind turbine load based on wind direction change according to claim 1, characterized in that: The constructing of the load prediction model comprises: Establishing an initial model based on the historical load data; Performing load correlation analysis according to the historical wind direction and the historical wind speed; The correlation analysis results are input into the initial model for training to obtain the load prediction model.

7. The method for dynamic prediction of wind turbine load based on wind direction change according to claim 1, characterized in that: The step of adjusting the unit operating parameters according to the load change includes: Determining whether the load change exceeds a safety threshold; If the safety threshold is exceeded, the operating power of the unit is reduced.

8. The method for dynamic prediction of wind turbine load based on wind direction change according to claim 1, characterized in that: The adjusting of the unit operating parameters then includes: Set the warning threshold of load; When the load change meets the warning threshold, generating a warning signal; Automatic load shedding of the control system is performed based on the early warning signal, and an early warning notification is sent to the operation and maintenance personnel.

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