Adaptive wind direction tracking method, device, equipment and medium for wind power generation system

Abstract

The present application provides a method, device, equipment, and medium for adaptive wind direction tracking in a wind power generation system, which relates to the technical field of wind power generation. The method includes: obtaining wind direction data and wind force data at a target device location; determining the wind direction trend at the target device location based on the wind direction data; when it is determined that the wind direction trend is within a preset wind direction trend, judging whether the wind force at the target device location meets a preset condition based on the wind force data; if it is determined that the wind force at the target device location meets the preset condition, calculating the yaw angle of the target device based on the wind direction data; and generating a control instruction based on the yaw angle to adjust the impeller direction of the target device. The present application can adjust the impeller direction according to the wind energy conditions to maximize the capture of wind energy and thus improve conversion efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of wind power generation, and in particular to a method, device, equipment and medium for adaptive wind direction tracking of a wind power generation system. Background Art

[0002] Wind power generation is the process of converting wind energy into electrical energy. The main principle is to use wind power to propel the blades of a wind turbine, causing them to rotate, thereby driving a generator to generate electricity. This method of power generation utilizes the constant flow of wind energy in nature. It is not only clean and pollution-free, but also reduces dependence on fossil fuels. Wind power generation equipment typically includes a wind turbine, tower, generator, and control system. Wind speed and direction have a significant impact on power generation efficiency.

[0003] When a wind turbine's rotor is tilted at a large angle relative to the wind direction, the effective utilization of wind power is significantly reduced, resulting in lower wind power conversion efficiency. Excessively large yaw angles prevent wind from acting perpendicularly on the blades, reducing the blade's force-bearing area and rotational kinetic energy, ultimately affecting the generator's output power. Therefore, a method is needed to adjust the rotor's direction according to wind conditions to maximize wind energy capture and improve conversion efficiency. Summary of the Invention

[0004] The present application provides a method, device, equipment and medium for adaptive wind direction tracking of a wind power generation system, which can adjust the direction of the impeller according to the wind energy conditions to maximize the capture of wind energy and thus improve conversion efficiency.

[0005] In a first aspect of the present application, a method for adaptive wind direction tracking of a wind power generation system is provided, the method comprising:

[0006] Obtain wind direction data and wind force data at the target device location;

[0007] Determining a wind direction trend at the target device location based on the wind direction data;

[0008] When it is determined that the wind direction trend is in a preset wind direction trend, determining whether the wind force at the target device location meets a preset condition based on the wind force data;

[0009] If it is determined that the wind force at the location of the target device meets the preset condition, calculating the yaw angle of the target device based on the wind direction data;

[0010] A control instruction is generated according to the yaw angle to adjust the impeller direction of the target device.

[0011] By adopting the above technical solution, the wind direction and wind force data of the target device location are obtained in real time to accurately determine the wind direction trend and wind force conditions. First, the wind direction trend is determined based on the wind direction data. When the wind direction trend meets the preset trend conditions, the wind force data is used to determine whether the current wind force meets the preset conditions. If the wind force meets the requirements, the optimal yaw angle of the target device is calculated, and the corresponding control instructions are generated to adjust the direction of the impeller so that it is aligned with the current wind direction. This process ensures that the impeller can always face the optimal wind direction, thereby making full use of wind energy and improving the conversion efficiency of wind power generation. Through adaptive adjustment, the system can dynamically respond to changes in wind direction and wind force, avoiding the problems of energy loss and reduced efficiency, and realizing efficient and stable wind energy capture and conversion.

[0012] Optionally, determining the wind direction trend at the location of the target device based on the wind direction data specifically includes:

[0013] Using data analysis technology to perform pattern recognition on the stored wind direction data to obtain recognition results, wherein the data analysis technology includes time series analysis, sliding window analysis and Fourier transform;

[0014] Determining a predicted change trend of wind direction based on the identification result;

[0015] Obtaining an actual change trend of wind direction with respect to the predicted change trend;

[0016] It is determined whether the actual change trend is consistent with the predicted change trend. If it is determined that the actual change trend is consistent with the predicted change trend, the predicted change trend is set as the wind direction trend.

[0017] By adopting the above technical solution and utilizing data analysis techniques (including time series analysis, sliding window analysis, and Fourier transforms) to perform pattern recognition on stored wind direction data, wind direction trends can be accurately predicted. Specifically, by identifying historical patterns in wind direction data, future wind direction changes are predicted and the predicted results are compared and verified with actual changes. When the actual wind direction trend aligns with the predicted results, the accuracy of the predicted trend is confirmed and set as the wind direction trend. This effectively improves the accuracy of wind direction prediction, enabling wind turbine systems to pre-adjust the rotor direction to always face the optimal wind direction, thereby maximizing wind energy capture, improving power generation efficiency, and minimizing energy loss.

[0018] Optionally, determining that the wind direction trend is within a preset wind direction trend specifically includes:

[0019] determining a first direction of wind direction based on the wind direction trend;

[0020] Acquire a second direction corresponding to the impeller direction;

[0021] determining a deviation angle according to the first direction and the second direction;

[0022] If it is determined that the deviation angle is greater than or equal to the preset angle threshold, it is determined that the wind direction trend is in the preset wind direction trend.

[0023] By employing the above technical solution, the first wind direction and the second impeller direction are determined, the deviation angle between the two is calculated, and the determination is made whether the deviation angle is greater than or equal to a preset angle threshold, thereby effectively assessing whether the current wind direction conforms to a preset trend. This ensures that the wind turbine system can promptly detect and confirm significant changes in wind direction, allowing it to quickly adjust the impeller direction to maintain its optimal wind direction.

[0024] Optionally, after determining that the deviation angle is greater than or equal to a preset angle threshold, the method further includes:

[0025] determining a fixed duration for which the wind direction is in the first direction according to the wind direction trend;

[0026] It is determined whether the fixed time length is greater than or equal to a preset time length. If it is determined that the fixed time length is greater than or equal to the preset time length, it is determined that the wind direction trend is within the preset wind direction trend.

[0027] By adopting the above technical solution, after determining that the deviation angle is greater than or equal to the preset angle threshold, the fixed duration of the wind direction in the first direction is further determined based on the wind direction trend, and then a determination is made whether the fixed duration is greater than or equal to the preset duration, thereby ensuring that the wind direction change is continuous. This can effectively avoid unnecessary adjustments caused by short-term wind direction changes, ensuring that the impeller direction is adjusted only when the wind direction is stable and continuous, thereby improving the response accuracy and stability of wind power generation, reducing mechanical losses caused by frequent adjustments, and improving overall operational efficiency and reliability.

[0028] Optionally, determining whether the wind force at the target device location meets a preset condition based on the wind force data specifically includes:

[0029] Determining a wind force change trend at the target device location based on the wind force data;

[0030] Determining whether the wind speed change trend is in an upward trend or a stable trend;

[0031] If it is determined that the wind force change trend is in the rising trend, or if it is determined that the wind force change trend is in the stable trend, it is determined that the wind force at the target device location meets the preset condition.

[0032] By employing the above technical solution, the wind force trend at the target device location is determined based on wind data, and whether the wind force trend is rising or stable is determined, thereby ensuring stable and adequate wind conditions. This method accurately identifies the changing patterns of wind force, ensuring that the wind force meets the preset conditions when the wind force is continuously rising or stable. This allows the rotor direction to be adjusted according to the most favorable wind conditions, improving the efficiency and stability of wind power generation and avoiding ineffective adjustments when the wind force is insufficient or fluctuating, thereby optimizing the capture and conversion efficiency of wind energy.

[0033] Optionally, calculating the yaw angle of the target device based on the wind direction data specifically includes:

[0034] determining a first rotation angle and a second rotation angle of the impeller of the target device according to the deviation angle, wherein the first rotation angle is an angle of the impeller of the target device rotating from the second direction to the first direction in a clockwise direction, and the second rotation angle is an angle of the impeller of the target device rotating from the second direction to the first direction in a counterclockwise direction; or the first rotation angle is an angle of the impeller of the target device rotating from the second direction to the first direction in a counterclockwise direction, and the second rotation angle is an angle of the impeller of the target device rotating from the second direction to the first direction in a clockwise direction;

[0035] The first rotation angle is compared with the second rotation angle. If it is determined that the first rotation angle is smaller than the second rotation angle, the first rotation angle is determined to be the yaw angle.

[0036] By employing this technical solution, the target device's impeller's first and second rotation angles—the angles required to rotate from its current orientation to the target orientation, clockwise and counterclockwise, respectively—are calculated. The two angles are compared, and the smaller rotation angle is selected as the yaw angle, thereby optimizing the adjustment path. This ensures that the impeller takes the shortest path during adjustment, reducing rotation time and mechanical wear, improving response speed and adjustment efficiency. This also avoids unnecessary energy consumption, enabling the wind turbine system to respond more quickly to changes in wind direction, maintaining optimal wind energy capture, and improving power generation efficiency and overall system reliability.

[0037] Optionally, the method of performing pattern recognition on the stored wind direction data using data analysis technology to obtain a recognition result specifically includes:

[0038] Performing the time series analysis on the wind direction data to obtain a periodic change trend of the wind direction;

[0039] Performing the sliding window analysis on the wind direction data to obtain a change trend of the wind direction in a preset time period;

[0040] Performing Fourier transform analysis on the wind direction data to obtain periodic data of the wind direction;

[0041] The periodic change trend, the change trend and the periodic data are combined to obtain the recognition result.

[0042] By employing the above technical solution and combining time series analysis, sliding window analysis, and Fourier transform analysis to perform pattern recognition on stored wind direction data, the team was able to comprehensively and accurately capture the changing patterns of wind direction. Time series analysis reveals the cyclical trends of wind direction, sliding window analysis provides the changing trends of wind direction within a preset time period, and Fourier transform extracts the cyclical data of wind direction. These combined analysis results provide a detailed and accurate wind direction identification result, enabling more effective prediction of wind direction changes, thereby optimizing rotor adjustment strategies, improving wind energy utilization efficiency and power generation stability, and maximizing the capture of wind energy resources.

[0043] In a second aspect of the present application, a device for adaptively tracking wind direction in a wind power generation system is provided. The device includes an acquisition module, a judgment module, a processing module, and a control module, wherein:

[0044] The acquisition module is used to acquire wind direction data and wind force data at the target device location;

[0045] The judgment module is used to determine the wind direction trend of the target device location based on the wind direction data;

[0046] The judgment module is configured to judge whether the wind force at the target device location meets a preset condition based on the wind force data when it is determined that the wind direction trend is in a preset wind direction trend;

[0047] The processing module is configured to calculate a yaw angle of the target device based on the wind direction data if it is determined that the wind force at the target device location meets the preset condition;

[0048] The control module is used to generate a control instruction according to the yaw angle to adjust the impeller direction of the target device.

[0049] Optionally, the processing module is configured to perform pattern recognition on the stored wind direction data using data analysis technology to obtain a recognition result, wherein the data analysis technology includes time series analysis, sliding window analysis, and Fourier transform;

[0050] The judgment module is used to determine the predicted change trend of the wind direction based on the recognition result;

[0051] The acquisition module is used to obtain the actual change trend of the wind direction with respect to the predicted change trend;

[0052] The judgment module is used to judge whether the actual change trend is consistent with the predicted change trend. If it is determined that the actual change trend is consistent with the predicted change trend, the predicted change trend is set as the wind direction trend.

[0053] Optionally, the processing module is used to determine a first direction of the wind direction according to the wind direction trend;

[0054] The acquisition module is used to acquire a second direction corresponding to the impeller direction;

[0055] The processing module is configured to determine a deviation angle based on the first direction and the second direction;

[0056] The judgment module is configured to determine that the wind direction trend is within the preset wind direction trend if it is determined that the deviation angle is greater than or equal to a preset angle threshold.

[0057] Optionally, the processing module is configured to determine a fixed duration for which the wind direction is in the first direction according to the wind direction trend;

[0058] The judgment module is used to judge whether the fixed time length is greater than or equal to the preset time length. If it is determined that the fixed time length is greater than or equal to the preset time length, it is determined that the wind direction trend is within the preset wind direction trend.

[0059] Optionally, the judgment module is used to determine the wind force change trend at the target device location based on the wind force data;

[0060] The judging module is configured to judge whether the wind speed change trend is in an upward trend or a stable trend;

[0061] The judgment module is configured to determine whether the wind force at the target device location satisfies the preset condition if it is determined that the wind force change trend is in the rising trend, or if it is determined that the wind force change trend is in the stable trend.

[0062] Optionally, the judgment module is configured to determine a first rotation angle and a second rotation angle of the impeller of the target device according to the deviation angle, wherein the first rotation angle is an angle at which the impeller of the target device rotates from the second direction to the first direction in a clockwise direction, and the second rotation angle is an angle at which the impeller of the target device rotates from the second direction to the first direction in a counterclockwise direction; or the first rotation angle is an angle at which the impeller of the target device rotates from the second direction to the first direction in a counterclockwise direction, and the second rotation angle is an angle at which the impeller of the target device rotates from the second direction to the first direction in a clockwise direction;

[0063] The processing module is configured to compare the first rotation angle with the second rotation angle, and if it is determined that the first rotation angle is smaller than the second rotation angle, determine the first rotation angle as the yaw angle.

[0064] Optionally, the processing module is used to perform the time series analysis on the wind direction data to obtain a periodic change trend of the wind direction;

[0065] The processing module is configured to perform the sliding window analysis on the wind direction data to obtain a change trend of the wind direction in a preset time period;

[0066] The processing module is used to perform Fourier transform analysis on the wind direction data to obtain periodic data of the wind direction;

[0067] The processing module is used to combine the periodic change trend, the change trend and the periodic data to obtain the recognition result.

[0068] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs any of the methods described above.

[0069] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions. When the instructions are executed, any one of the methods described above is executed.

[0070] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0071] By acquiring wind direction and wind force data at the target device location in real time, the wind direction trend and wind force conditions can be accurately determined. First, the wind direction trend is determined based on the wind direction data. When the wind direction trend meets the preset trend conditions, the wind force data is used to determine whether the current wind force meets the preset conditions. If the wind force meets the requirements, the optimal yaw angle of the target device is calculated, and the corresponding control instructions are generated to adjust the direction of the impeller to align it with the current wind direction. This process ensures that the impeller can always face the optimal wind direction, thereby fully utilizing wind energy and improving the conversion efficiency of wind power generation. Through adaptive adjustment, the system can dynamically respond to changes in wind direction and wind force, avoiding energy loss and reduced efficiency, and achieving efficient and stable wind energy capture and conversion. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 1 is a flow chart of a method for adaptive wind direction tracking of a wind power generation system disclosed in an embodiment of the present application;

[0073] Figure 2 This is a module diagram of the adaptive wind direction tracking device for a wind power generation system disclosed in an embodiment of the present application;

[0074] Figure 3 This is a structural diagram of an electronic device disclosed in an embodiment of the present application.

[0075] Explanation of the reference numerals: 201, acquisition module; 202, judgment module; 203, processing module; 204, control module; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0076] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0077] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0078] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0079] Wind power generation is the process of converting wind energy into electrical energy. The main principle is to use wind power to propel the blades of a wind turbine, causing them to rotate, thereby driving a generator to generate electricity. This method of power generation utilizes the constant flow of wind energy in nature. It is not only clean and pollution-free, but also reduces dependence on fossil fuels. Wind power generation equipment typically includes a wind turbine, tower, generator, and control system. Wind speed and direction have a significant impact on power generation efficiency.

[0080] When a wind turbine's rotor is tilted at a large angle relative to the wind direction, the effective utilization of wind power is significantly reduced, resulting in lower wind power conversion efficiency. Excessively large yaw angles prevent wind from acting perpendicularly on the blades, reducing the blade's force-bearing area and rotational kinetic energy, ultimately affecting the generator's output power. Therefore, a method is needed to adjust the rotor's orientation to maximize wind energy capture and improve conversion efficiency.

[0081] This embodiment discloses a method for adaptively tracking wind direction in a wind power generation system. Figure 1 , including the following steps S110-S150:

[0082] S110, obtaining wind direction data and wind force data at the target device location.

[0083] The adaptive wind direction tracking method for a wind power generation system disclosed in an embodiment of the present application is applied to an intelligent control system of a target device, and the target device is preferably a wind turbine generator set.

[0084] The wind turbine also includes a blade self-cleaning device, installed in a concealed location inside or on the blade edge. It comprises a microclimate monitoring module, an intelligent spray system, and a self-cleaning coating. The microclimate monitoring module monitors the humidity, temperature, and dirt accumulation on the blade surface. The intelligent spray system activates according to this monitoring data, using a built-in ultrasonic atomizer to convert the cleaning fluid into fine droplets that are evenly sprayed onto the blade surface, effectively removing accumulated dust, bird droppings, and other debris. The self-cleaning coating utilizes advanced super-hydrophobic or photocatalytic technologies to enhance the blade surface's ability to repel pollutants, slowing the rate of dirt deposition and further enhancing cleaning effectiveness.

[0085] The intelligent control system is a comprehensive system that integrates sensor data acquisition, real-time data analysis, decision-making algorithms, and executive control. It uses high-precision wind direction and speed sensors to acquire environmental data, employs advanced computing models and machine learning algorithms to calculate the optimal yaw angle in real time, and uses dynamic drive units to precisely adjust the wind turbine's direction, ensuring the rotors always face the strongest wind flow. This maximizes wind energy capture efficiency and improves power generation performance.

[0086] Common wind direction sensors used to measure wind direction and wind force at the target device include wind vanes (vanes) and electronic wind direction sensors. A wind vane's rotating part indicates the wind's direction, while an electronic wind direction sensor uses internal magnetic components or changes in resistance to measure wind direction angle. Mounting the wind direction sensor on top of the target device or on a nearby tower ensures it is free from interference from surrounding structures and accurately reflects natural wind direction.

[0087] Common wind speed sensors include cup anemometers, hot wire anemometers, and ultrasonic anemometers. Cup anemometers measure wind speed using a rotating cup, hot wire anemometers measure wind speed by changes in heat conduction, and ultrasonic anemometers calculate wind speed by varying the speed of sound waves through air. Wind speed sensors are also mounted on the top of the target equipment or on a tower, working in conjunction with wind direction sensors to ensure accurate measurement data.

[0088] Wind direction and speed sensors use built-in electronic circuits to convert the measured physical quantity into an electrical signal (such as voltage, current, or digital signal). The sensor output signal is transmitted to the intelligent control system of the target device via wired or wireless means.

[0089] S120: Determine the wind direction trend at the target device location based on the wind direction data.

[0090] In one possible implementation, based on wind direction data, the wind direction trend of the target device location is determined, specifically including: using data analysis technology to perform pattern recognition on the stored wind direction data to obtain a recognition result, wherein the data analysis technology includes time series analysis, sliding window analysis, and Fourier transform; determining the predicted change trend of the wind direction based on the recognition result; obtaining the actual change trend of the wind direction for the predicted change trend; judging whether the actual change trend is consistent with the predicted change trend, and if it is determined that the actual change trend is consistent with the predicted change trend, setting the predicted change trend as the wind direction trend.

[0091] Specifically, the collected wind direction data is preprocessed to remove outliers and noise. Common methods include moving average filtering and median filtering to ensure data smoothness and stability. The preprocessed wind direction data is stored in a time series database to facilitate subsequent analysis and calculations. Time series analysis is performed on the stored wind direction data, using methods such as the autoregressive integrated moving average (ARIMA) model to analyze historical trends and cyclical changes in the wind direction data. Time series analysis can identify long-term trends, seasonal fluctuations, and short-term fluctuations in wind direction data, providing a basis for subsequent forecasts.

[0092] Alternatively, use sliding window analysis. Define a sliding window with a size that depends on the application scenario, such as 5 minutes or 10 minutes. Calculate the wind direction trend within the sliding window, including the mean, standard deviation, and rate of change. This allows real-time identification of short-term wind direction trends and captures both dramatic fluctuations and steady changes. Alternatively, use the Fourier transform to convert wind direction data from the time domain to the frequency domain and analyze the periodicity and frequency components within the data. The Fourier transform can identify key periods in wind direction fluctuations, helping to predict future wind direction changes.

[0093] Combine time series analysis, sliding window analysis, and Fourier transform analysis to comprehensively assess current wind direction patterns. Use regression analysis or machine learning algorithms (such as long-short-term memory (LSTM) networks) to build a forecasting model based on historical and current data to predict future wind direction trends. The predicted trends include information such as the direction, rate, and period of wind direction change.

[0094] In one possible implementation, data analysis technology is used to perform pattern recognition on the stored wind direction data to obtain recognition results, specifically including: performing time series analysis on the wind direction data to obtain the periodic change trend of the wind direction; performing sliding window analysis on the wind direction data to obtain the change trend of the wind direction in a preset time period; performing Fourier transform analysis on the wind direction data to obtain the periodic data of the wind direction; and combining the periodic change trend, the change trend and the periodic data to obtain the recognition result.

[0095] Specifically, the preprocessed wind direction data is stored in a time series database. An appropriate time series analysis model, such as the autoregressive integrated moving average (ARIMA) model, is selected. The ARIMA model is trained using historical wind direction data to determine model parameters. The trained model is then used to analyze the wind direction data, identifying long-term trends, seasonal fluctuations, and short-term fluctuations, thereby determining the cyclical variation trends of wind direction. This trend information can include the long-term average direction of wind direction and seasonal variation patterns.

[0096] Set the sliding window size, such as 5 or 10 minutes, depending on the application scenario. Calculate the mean, standard deviation, and rate of change of wind direction within the sliding window to determine the wind direction trend over that time period. The sliding window continuously slides, calculating the trend of each new data segment to capture short-term fluctuations and trend changes in wind direction. Sliding window analysis can identify characteristics of wind direction changes over a shorter period of time, such as sudden or steady changes.

[0097] A Fourier transform is performed on the wind direction data to convert the time domain data into the frequency domain. The Fourier transform is used to analyze the frequency components of the wind direction data and identify major periodic variations. The periodic data includes major and minor periods of wind direction variation, reflecting the periodic fluctuations of wind direction on different time scales. The intensity and frequency of these periodic variations are analyzed using a spectrogram to identify significant periods of wind direction variation.

[0098] The cyclical trend obtained from time series analysis, the trend over a preset time period obtained from sliding window analysis, and the periodic data obtained from Fourier transform analysis are integrated. Using data fusion technology, the results from different analysis methods are combined to form a unified recognition result. Data fusion methods can include weighted averaging and Bayesian fusion. Through comprehensive analysis, a comprehensive wind direction trend is obtained, and the main change patterns and cyclical characteristics of wind direction are identified.

[0099] Continuously collect the latest wind direction data in real time and compare it with the forecast model. The actual change trend is calculated based on the latest real-time wind direction data, reflecting the actual changes in wind direction during the current time period. To determine whether the actual change trend is consistent with the forecast trend, the actual change trend is compared with the forecast trend to determine their consistency. Criteria for judgment can include differences in wind direction angles, deviations in change rates, and the degree of matching of periodic changes. If the actual change trend and the forecast trend are consistent within the set tolerance range, the forecast trend is considered accurate.

[0100] If the actual wind direction trend is consistent with the predicted wind direction trend, the predicted wind direction trend is set as the current wind direction trend. The wind direction trend is used for subsequent wind force determination and yaw angle calculation to ensure that the wind turbine can accurately adjust the rotor direction and maximize wind energy capture efficiency.

[0101] S130: When it is determined that the wind direction trend is in the preset wind direction trend, it is determined based on the wind force data whether the wind force at the target device location meets a preset condition.

[0102] First, the first direction of the wind direction is determined based on the wind direction trend. Wind direction data at the target device is collected in real time using a high-precision wind direction sensor and stored in a time series database after preprocessing. Using data analysis techniques such as time series analysis, sliding window analysis, and Fourier transform, the changing pattern and predicted trend of the wind direction are identified. The wind direction trend at the current moment is determined, and the first direction of the wind direction (i.e., the wind direction angle) is obtained, which represents the main flow direction of the current wind direction. The second direction corresponding to the impeller direction is obtained, and the dynamic yaw drive unit and control system monitor the current direction of the wind turbine impeller in real time. The impeller direction is usually measured by an encoder or angle sensor installed on the impeller shaft, and the current impeller heading angle is recorded as the second direction.

[0103] Calculate the deviation between the wind's first direction (wind angle) and the impeller's second direction (impeller angle). The deviation angle is calculated using the formula: Deviation angle = |first direction - second direction|. Ensure the result is a positive value. The calculated result reflects the difference between the impeller direction and the actual wind direction.

[0104] A preset angle threshold is set, determined based on the system's sensitivity and response requirements, for example, between 5 and 10 degrees. The calculated deviation angle is compared with the preset angle threshold. If the deviation angle is greater than or equal to the threshold, it is determined that the current impeller direction does not match the wind direction and requires adjustment. The wind direction trend is determined to be within the preset wind direction trend. When the deviation angle is greater than or equal to the preset angle threshold, the current wind direction trend is determined to be within the preset wind direction trend range.

[0105] Furthermore, the wind direction data is continuously monitored, and the time period during which the wind direction remains in the first direction is recorded. The wind direction data is analyzed using a sliding window or time-stamping technique, and the duration (fixed duration) during which the wind direction is in the first direction is counted. A preset duration threshold (preset duration) is set, which can be determined based on historical data and actual application requirements, and is usually between a few minutes and tens of minutes. The fixed duration during which the wind direction is in the first direction is compared with the preset duration. If the fixed duration is greater than or equal to the preset duration, it is confirmed that the wind direction trend is stable and is in the preset wind direction trend. When it is determined that the wind direction trend is in the preset wind direction trend, and the deviation angle is greater than or equal to the preset angle threshold, a specific control instruction is generated to instruct the dynamic yaw drive unit to adjust the impeller direction.

[0106] S140: If it is determined whether the wind force at the target device location meets the preset condition, the yaw angle of the target device is calculated based on the wind direction data.

[0107] The collected wind data is preprocessed to remove outliers and noise. Common methods include moving average filtering and median filtering to ensure smooth and stable data. The preprocessed wind data is stored in a database to facilitate subsequent analysis and calculations. A time series database can be used for data storage, facilitating rapid retrieval and processing.

[0108] Using sliding window analysis technology, we analyze short-term trends in stored wind data. We define a sliding window, the size of which can be customized to meet specific needs, such as 5 or 10 minutes. We calculate the wind speed trend within the sliding window, including the wind speed mean, standard deviation, and rate of change. By moving the sliding window, we continuously calculate the wind data trend and generate real-time wind speed trends.

[0109] If the wind speed values ​​within the sliding window show a clear, gradual increase, and the rate of change is positive, the wind is considered to be on an upward trend. Regression analysis can be used to determine the direction and rate of wind speed change by measuring the slope of the fitted line. If the wind speed values ​​within the sliding window fluctuate within a certain range, and the rate of change is close to zero, the wind is considered to be on a stable trend. Wind speed stability can be determined by calculating the standard deviation and rate of change.

[0110] When it is determined that the wind force change trend is in an upward trend, or if it is determined that the wind force change trend is in a stable trend, it is determined that the wind force at the target device location meets the preset conditions. On the contrary, when it is determined that the wind force change trend is in a downward trend, it is determined that the wind force gradually decreases until it reaches zero, and the wind force at the target device location does not meet the preset conditions. Alternatively, if the wind force change trend is in an upward trend, and the current wind speed value is greater than or equal to the preset wind speed threshold, it is determined that the wind force at the target device location meets the preset conditions. If the wind force change trend is in a stable trend, and the current wind speed value is greater than or equal to the preset wind speed threshold, it is also determined that the wind force at the target device location meets the preset conditions.

[0111] In a possible embodiment, the yaw angle of the target device is calculated based on the wind direction data, specifically including: determining a first rotation angle and a second rotation angle of the impeller of the target device according to the deviation angle, wherein the first rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a clockwise direction, and the second rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a counterclockwise direction; or the first rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a counterclockwise direction, and the second rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a clockwise direction; and comparing the size relationship between the first rotation angle and the second rotation angle, if it is determined that the first rotation angle is smaller than the second rotation angle, then determining that the first rotation angle is the yaw angle.

[0112] The impeller's deviation angle is calculated based on the current wind direction angle (first direction) measured by the wind direction sensor and the current impeller direction (second direction) measured by the impeller angle sensor or encoder. Based on the deviation angle, the impeller's angle of rotation from the second direction clockwise to the first direction is calculated to obtain the first rotation angle, and the impeller's angle of rotation from the second direction counterclockwise to the first direction is calculated to obtain the second rotation angle. Alternatively, based on the deviation angle, the impeller's angle of rotation from the second direction counterclockwise to the first direction is calculated to obtain the first rotation angle, and the impeller's angle of rotation from the second direction clockwise to the first direction is calculated to obtain the second rotation angle. The first rotation angle and the second rotation angle are compared. If the first rotation angle is smaller than the second rotation angle, the first rotation angle is selected as the yaw angle. If the second rotation angle is smaller than the first rotation angle, the second rotation angle is selected as the yaw angle.

[0113] S150: Generate a control instruction according to the yaw angle to adjust the impeller direction of the target device.

[0114] Based on the selected optimal rotation angle, a control command is generated and sent to the dynamic yaw drive unit. Upon receiving the command, the dynamic yaw drive unit drives the servo motor to adjust the impeller's direction to align with the wind. During this adjustment process, the impeller's direction is monitored in real time. If the direction is inaccurate, the system recalculates and adjusts to ensure that the impeller is always aligned with the wind.

[0115] By adopting the technical solution of the present application, the wind direction trend and wind conditions can be accurately determined by acquiring the wind direction and wind force data of the target device location in real time. First, the wind direction trend is determined based on the wind direction data. When the wind direction trend meets the preset trend conditions, the wind force data is used to determine whether the current wind force meets the preset conditions. If the wind force meets the requirements, the optimal yaw angle of the target device is calculated, and the corresponding control instructions are generated to adjust the direction of the impeller so that it is aligned with the current wind direction. This process ensures that the impeller can always face the optimal wind direction, thereby making full use of wind energy and improving the conversion efficiency of wind power generation. Through adaptive adjustment, the system can dynamically respond to changes in wind direction and wind force, avoiding the problems of energy loss and reduced efficiency, and achieving efficient and stable wind energy capture and conversion.

[0116] This embodiment also discloses a wind power generation system adaptive wind direction tracking device, referring to Figure 2 The device includes an acquisition module, a judgment module, a processing module and a control module, wherein:

[0117] The acquisition module is used to obtain wind direction data and wind force data at the target device location.

[0118] The judgment module is used to determine the wind direction trend of the target device location based on the wind direction data.

[0119] The judgment module is used to judge whether the wind force at the target device location meets the preset conditions based on the wind force data when it is determined that the wind direction trend is in the preset wind direction trend.

[0120] The processing module is configured to calculate the yaw angle of the target device based on the wind direction data if it is determined that the wind force at the target device location meets a preset condition.

[0121] The control module is used to generate control instructions according to the yaw angle to adjust the impeller direction of the target device.

[0122] In a possible implementation, the processing module is configured to perform pattern recognition on the stored wind direction data using data analysis techniques to obtain recognition results, wherein the data analysis techniques include time series analysis, sliding window analysis, and Fourier transform.

[0123] The judgment module is used to determine the predicted change trend of wind direction based on the recognition result.

[0124] The acquisition module is used to obtain the actual change trend of the wind direction with respect to the predicted change trend.

[0125] The judgment module is used to judge whether the actual change trend is consistent with the predicted change trend. If it is determined that the actual change trend is consistent with the predicted change trend, the predicted change trend is set as the wind direction trend.

[0126] In a possible implementation, the processing module is configured to determine a first direction of the wind direction according to a wind direction trend.

[0127] The acquisition module is used to acquire a second direction corresponding to the impeller direction.

[0128] The processing module is configured to determine a deviation angle according to the first direction and the second direction.

[0129] The judgment module is used to determine that the wind direction trend is in a preset wind direction trend if it is determined that the deviation angle is greater than or equal to a preset angle threshold.

[0130] In a possible implementation, the processing module is configured to determine a fixed duration for which the wind direction is in the first direction according to a wind direction trend.

[0131] The judging module is used to judge whether the fixed time length is greater than or equal to the preset time length. If it is determined that the fixed time length is greater than or equal to the preset time length, it is determined that the wind direction trend is in the preset wind direction trend.

[0132] In a possible implementation, the judgment module is configured to determine a wind force variation trend at the target device location based on wind force data.

[0133] The judgment module is used to judge whether the wind speed change trend is in an upward trend or a stable trend.

[0134] The judgment module is used to determine whether the wind force at the target device location meets a preset condition if it is determined that the wind force change trend is in an upward trend, or if it is determined that the wind force change trend is in a stable trend.

[0135] In one possible embodiment, the judgment module is configured to determine a first rotation angle and a second rotation angle of the impeller of the target device based on the deviation angle, wherein the first rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a clockwise direction, and the second rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a counterclockwise direction. Alternatively, the first rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a counterclockwise direction, and the second rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a clockwise direction.

[0136] The processing module is configured to compare the first rotation angle with the second rotation angle, and if it is determined that the first rotation angle is smaller than the second rotation angle, determine that the first rotation angle is a yaw angle.

[0137] In a possible implementation, the processing module is configured to perform time series analysis on the wind direction data to obtain a periodic variation trend of the wind direction.

[0138] The processing module is used to perform sliding window analysis on the wind direction data to obtain the change trend of the wind direction in a preset time period.

[0139] The processing module is used to perform Fourier transform analysis on the wind direction data to obtain the periodic data of the wind direction.

[0140] The processing module is used to combine the periodic change trend, the change trend and the periodic data to obtain the recognition result.

[0141] It should be noted that the above embodiments provide devices that implement their functions using only the division of the above functional modules as examples. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0142] This embodiment also discloses an electronic device, referring to Figure 3 The electronic device may include: at least one processor 301 , at least one communication bus 302 , a user interface 303 , a network interface 304 , and at least one memory 305 .

[0143] The communication bus 302 is used to implement the connection and communication between these components.

[0144] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0145] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0146] The processor 301 may include one or more processing cores. Using various interfaces and circuits, the processor 301 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in the memory 305, as well as accesses data stored in the memory 305, to perform various server functions and process data. Optionally, the processor 301 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 301 but implemented as a separate chip.

[0147] Memory 305 may include random access memory (RAM) or read-only memory (ROM). Optionally, the memory may include non-transitory computer-readable storage medium. Memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. Memory 305 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, sound playback function, image playback function, etc.), instructions for implementing the aforementioned method embodiments, etc.; the data storage area may store data related to the aforementioned method embodiments, etc. Memory 305 may also optionally be at least one storage device located remotely from the processor 301. Memory 305, as a computer storage medium, may include an operating system, a network communication module, a user interface 303 module, and an application program for the adaptive wind direction tracking method for a wind power generation system.

[0148] exist Figure 3 In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call the application program stored in the memory 305 for the adaptive wind direction tracking method of the wind power generation system. When executed by one or more processors 301, the electronic device executes one or more methods as in the above embodiments.

[0149] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0150] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0151] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0152] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0153] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0154] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory 305 and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of this application. The aforementioned memory 305 includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a magnetic disk, or an optical disk.

[0155] The present application also discloses a computer-readable storage medium storing instructions, which, when executed by one or more processors 301, enable an electronic device to execute one or more of the methods described in the above embodiments.

[0156] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art that are not recorded in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for adaptive wind direction tracking of a wind power generation system, characterized in that: The method includes: obtaining wind direction data and wind force data at a target device location; determining a wind direction trend at the target device location based on the wind direction data; when it is determined that the wind direction trend is within a preset wind direction trend, judging whether the wind force at the target device location meets a preset condition based on the wind force data; if it is determined that the wind force at the target device location meets the preset condition, calculating a yaw angle of the target device based on the wind direction data; and generating a control instruction based on the yaw angle to adjust the impeller direction of the target device; Determining the wind direction trend at the target device location based on the wind direction data specifically includes: performing pattern recognition on the stored wind direction data using data analysis technology to obtain a recognition result, wherein the data analysis technology includes time series analysis, sliding window analysis, and Fourier transform; determining a predicted change trend of the wind direction based on the recognition result; obtaining an actual change trend of the wind direction with respect to the predicted change trend; determining whether the actual change trend is consistent with the predicted change trend, and if it is determined that the actual change trend is consistent with the predicted change trend, setting the predicted change trend as the wind direction trend; Determining that the wind direction trend is in a preset wind direction trend specifically includes: determining a first direction of the wind direction according to the wind direction trend; obtaining a second direction corresponding to the impeller direction; determining a deviation angle according to the first direction and the second direction; and determining that the wind direction trend is in the preset wind direction trend if it is determined that the deviation angle is greater than or equal to a preset angle threshold; The calculating the yaw angle of the target device based on the wind direction data specifically includes: determining a first rotation angle and a second rotation angle of the impeller of the target device according to the deviation angle, wherein the first rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a clockwise direction, and the second rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a counterclockwise direction; or the first rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a counterclockwise direction, and the second rotation angle is the angle of the impeller of the target device rotating from the second direction to the first direction in a clockwise direction; comparing the size relationship between the first rotation angle and the second rotation angle, if it is determined that the first rotation angle is smaller than the second rotation angle, determining that the first rotation angle is the yaw angle.

2. The method for adaptive wind direction tracking of a wind power generation system according to claim 1, characterized in that: After determining that the deviation angle is greater than or equal to the preset angle threshold, the method further includes: determining a fixed time duration that the wind direction is in the first direction based on the wind direction trend; judging whether the fixed time duration is greater than or equal to the preset time duration; if it is determined that the fixed time duration is greater than or equal to the preset time duration, determining that the wind direction trend is in the preset wind direction trend.

3. The method for adaptive wind direction tracking of a wind power generation system according to claim 1, wherein: The determining whether the wind force at the target device location meets the preset conditions based on the wind force data specifically includes: determining the wind force change trend at the target device location based on the wind force data; determining whether the wind force change trend is in an upward trend or a stable trend; if it is determined that the wind force change trend is in the upward trend, or if it is determined that the wind force change trend is in the stable trend, then determining that the wind force at the target device location meets the preset conditions.

4. The method for adaptive wind direction tracking of a wind power generation system according to claim 1, wherein: The method of using data analysis technology to perform pattern recognition on the stored wind direction data to obtain the recognition result specifically includes: performing the time series analysis on the wind direction data to obtain the periodic change trend of the wind direction; performing the sliding window analysis on the wind direction data to obtain the change trend of the wind direction in a preset time period; performing Fourier transform analysis on the wind direction data to obtain the periodic data of the wind direction; and combining the periodic change trend, the change trend in the preset time period and the periodic data to obtain the recognition result.

5. An adaptive wind direction tracking device for a wind power generation system, according to the adaptive wind direction tracking method for a wind power generation system according to any one of claims 1 to 4, characterized in that: The device comprises an acquisition module (201), a judgment module (202), a processing module (203) and a control module (204), wherein: the acquisition module (201) is used to acquire wind direction data and wind force data at the target device location; the judgment module (202) is used to determine the wind direction trend at the target device location based on the wind direction data; the judgment module (202) is used to determine whether the wind force at the target device location meets a preset condition based on the wind force data when it is determined that the wind direction trend is in a preset wind direction trend; the processing module (203) is used to calculate the yaw angle of the target device based on the wind direction data if it is determined that the wind force at the target device location meets the preset condition; and the control module (204) is used to generate a control instruction based on the yaw angle to adjust the impeller direction of the target device.

6. An electronic device, characterized in that: The electronic device comprises a processor (301), a user interface (303), a network interface (304) and a memory (305), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are both used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device executes the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 4 is executed.

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