Fan single-blade clearance compensation dynamic control method, system, device and medium

Abstract

Embodiments of the present disclosure provide a fan single-blade clearance compensation dynamic control method, system, device and medium. The method comprises: obtaining the current wind speed, current turbulence and current passing period of the fan; obtaining the best variable pitch compensation value that meets the clearance requirement in the corresponding data cluster according to the current wind speed, current turbulence and current passing period; obtaining the clearance dynamic variable pitch strategy of the current passing tower blade according to the original variable pitch angle of the current passing tower blade, the wind wheel azimuth angle and the best variable pitch compensation value; and controlling the dynamic variable pitch of the current passing tower blade according to the clearance dynamic variable pitch strategy. Embodiments of the present disclosure find the best variable pitch compensation value of the fan under different wind conditions through a data clustering algorithm, perform dynamic clearance compensation when a single blade passes through the tower, improve the flexible blade clearance value of the large-capacity unit, reduce the risk of blade tower scanning, improve the safety of the unit, and minimize the impact on the wind energy utilization efficiency, which is conducive to reducing the cost and increasing the efficiency of the unit material.

Description

Technical Field

[0001] The embodiments disclosed herein belong to the field of wind turbine clearance control technology, specifically relating to a dynamic control method, system, equipment, and medium for single-blade clearance compensation of a wind turbine. Background Technology

[0002] Currently, the trend of wind turbines towards larger sizes and more intelligent control schemes is becoming increasingly evident, and this trend is accelerating. Larger turbines are experiencing increased weight and flexibility in their main components, leading to more complex load conditions. Therefore, optimized load control is necessary to ensure safe operation. Simultaneously, the implementation of grid parity policies has significantly reduced wind power equipment prices, putting immense pressure on cost reduction. Previous safety design concepts are no longer sufficient to meet current market demands. Regarding clearance design, the minimum distance between the rotor and the tower surface during rotation must be no less than 8 meters. However, with the increase in blade length and flexibility, this requirement has become a primary technical challenge hindering cost reduction for large-megawatt turbines.

[0003] Current mainstream turbine models have increased in power from 2 MW to approximately 6 MW, while rotor diameters have increased from 86m to approximately 195m. Due to cost reduction requirements, blade stiffness has generally decreased, resulting in significant out-of-plane oscillation of the blades during turbine operation. This increases the risk of blade tip swirl. Blade tip swirl is a major safety hazard and the primary risk factor for turbine collapse. A single swirl swirl can lead to blade breakage, causing millions in economic losses, or even turbine collapse resulting in direct losses exceeding tens of millions. Therefore, standards strictly stipulate clearance requirements, such as a minimum clearance of 8m for 5 MW turbines. To meet this stringent requirement, load calculations employ various methods to reduce blade thrust and increase clearance.

[0004] Currently, hub thrust reduction control is a common technique for increasing turbine headroom. This approach works by actively increasing the pitch angle as wind speed increases to reduce overall hub thrust and thus improve headroom. For example, a 5 MW turbine actively feathers the blades when power reaches 3 MW, causing the pitch angle to deviate from the optimal power absorption angle. Generally, when power reaches the rated value, the minimum pitch angle is already around 8 degrees. This strategy macroscopically reduces thrust to increase headroom, but it doesn't achieve precise adjustment. In a case study of a 5 MW turbine, a wind speed of 9 m / s could normally achieve a power output of 4.8 MW, but due to the premature feathering caused by the hub thrust reduction control strategy, the power output is reduced to only around 3.2 MW. Thrust reduction control directly leads to a decrease in wind energy absorption rate, causing economic losses; the greater the reduction, the greater the power loss.

[0005] Besides thrust reduction control strategies, increasing the nacelle pitch angle and other mechanical structural designs during the design process are also common methods to increase clearance. However, increasing the nacelle pitch angle means changing the overall stress structure of the unit, affecting power absorption performance, and causing other key indicators to decline accordingly.

[0006] Therefore, even with the application of various algorithms and structural improvement schemes, the air clearance problem remains a technical challenge in the unit design process, and a better solution needs to be found to reduce the risk of tower sweeping without affecting other technical indicators of the unit. Summary of the Invention

[0007] The embodiments disclosed herein aim to at least solve one of the technical problems existing in the prior art, and provide a method, system, device and medium for dynamic control of single blade headroom compensation of a wind turbine.

[0008] One aspect of this disclosure provides a dynamic control method for single-blade headroom compensation in a wind turbine, the method comprising:

[0009] Obtain the current wind speed, current turbulence intensity, and current passage cycle of the wind turbine;

[0010] Based on the current wind speed, the current turbulence intensity, and the current passage period, the optimal pitch compensation value that meets the clearance requirements in the corresponding data cluster is obtained.

[0011] Based on the original pitch angle of the current overpass blade, the rotor azimuth angle, and the optimal pitch compensation value, the current overpass blade's clearance dynamic pitch strategy is obtained.

[0012] The current pitch of the tower blades is controlled according to the aforementioned air clearance dynamic pitch strategy.

[0013] Optionally, the current turbulence intensity is the ratio of the standard deviation of wind speed over three minutes to the sliding average of wind speed.

[0014] Further, obtaining the optimal pitch compensation value that meets the clearance requirements in the corresponding data cluster based on the current wind speed, the current turbulence intensity, and the current passage period includes:

[0015] The wind speed dimension value is obtained based on the current wind speed, the turbulence dimension value is obtained based on the current turbulence intensity, and the passage period dimension value is obtained based on the current passage period.

[0016] Data clustering based on the wind speed dimension value, the turbulence intensity dimension value, and the pitch compensation value determined by the period dimension value;

[0017] The pitch compensation value that meets the clearance requirements in the data cluster is determined as the optimal pitch compensation value.

[0018] Further, obtaining the wind speed dimension value based on the current wind speed, obtaining the turbulence dimension value based on the current turbulence intensity, and obtaining the passage period dimension value based on the current passage period includes:

[0019] When the current wind speed is in the range of (3 m / s, 8 m / s), the wind speed dimension value is determined to be 1; when the current wind speed is in the range of (8 m / s, 12 m / s), the wind speed dimension value is determined to be 2; when the current wind speed is in the range of (12 m / s, 20 m / s), the wind speed dimension value is determined to be 3; and / or,

[0020] When the current turbulence intensity is in the range (0,1], the turbulence intensity dimension value is determined to be 1; when the current turbulence intensity is in the range (1,2], the turbulence intensity dimension value is determined to be 2; when the current turbulence intensity is greater than 2, the turbulence intensity dimension value is determined to be 3; and / or,

[0021] When the current passing period coincides with the wind turbine rotation period and the tower vibration period, the passing period dimension value is determined to be 1; when the current passing period coincides with the wind turbine rotation period and the blade vibration period, the passing period dimension value is determined to be 2; and when the current passing period coincides with the wind turbine rotation period, the tower vibration period, and the blade vibration period, the passing period dimension value is determined to be 3.

[0022] Furthermore, the data clustering is obtained through the following steps:

[0023] Obtain multiple headroom values ​​for the fan, as well as the wind speed, turbulence intensity, and passage period corresponding to each headroom value;

[0024] The multiple clearance values ​​are clustered once based on the wind speed dimension value;

[0025] Perform secondary clustering on each of the first clusters based on the turbulence dimension value;

[0026] Based on the period dimension value, a third clustering is performed on each of the secondary clusters to obtain data clusters corresponding to each wind speed dimension value, turbulence dimension value, and net value through the period dimension value.

[0027] Further, determining the pitch compensation value that meets the clearance requirements in the data cluster as the optimal pitch compensation value includes:

[0028] Calculate the confidence level of the pitch compensation value relative to the preset clearance value;

[0029] The pitch compensation value with a confidence level of 90% or higher is determined as the optimal pitch compensation value.

[0030] Furthermore, the headroom dynamic pitch strategy is expressed by the following formula:

[0031]

[0032] In the formula, β is the pitch angle of the current tower blades. r For the original pitch angle, L ijk The optimal pitch compensation value is given by: i = wind speed, j = turbulence intensity, and k = passage period. This is the current azimuth angle of the blade. This is the azimuth angle when the blade coincides with the tower.

[0033] Another aspect of this disclosure provides a dynamic control system for single-blade headroom compensation in a wind turbine, the system comprising:

[0034] The acquisition module is used to acquire the current wind speed, current turbulence intensity, and current passage cycle of the wind turbine;

[0035] The compensation module is used to obtain the optimal pitch compensation value that meets the clearance requirements in the corresponding data cluster based on the current wind speed, the current turbulence intensity and the current passage period;

[0036] The strategy module is used to obtain the current dynamic pitch strategy for the clearance of the current blade passing the tower based on the original pitch angle of the current blade passing the tower, the rotor azimuth angle, and the optimal pitch compensation value.

[0037] The control module is used to control the dynamic pitch of the current tower blades according to the aforementioned headroom dynamic pitch strategy.

[0038] Another aspect of this disclosure provides an electronic device, comprising:

[0039] At least one processor; and,

[0040] A memory communicatively connected to the at least one processor is used to store one or more programs that, when executed by the at least one processor, enable the at least one processor to implement the dynamic control method for single-blade headroom compensation of the wind turbine described above.

[0041] Another aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the dynamic control method for single-blade headroom compensation of a wind turbine described above.

[0042] This disclosure discloses a dynamic control method, system, device, and medium for single-blade clearance compensation of a wind turbine. By employing a data clustering algorithm, it identifies the optimal pitch compensation value for the wind turbine under different wind conditions. Dynamic clearance compensation for a single blade is performed only during the blade's passage over the tower, improving the clearance value of flexible blades in large-capacity wind turbines. This significantly reduces the risk of tower sweeping during turbine operation, enhances turbine safety, and minimizes the impact on other loads and wind energy utilization efficiency. It achieves optimal control to meet clearance requirements, satisfying the clearance design requirements of large-megawatt turbines. This solves the clearance technology problems that have plagued turbine design, freeing up design margins without altering the overall structural stress of the turbine, and greatly contributing to cost reduction and efficiency improvement of turbine materials. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating a dynamic control method for single-blade headroom compensation of a wind turbine according to an embodiment of this disclosure.

[0044] Figure 2 This is a schematic diagram of the confidence function according to another embodiment of the present disclosure;

[0045] Figure 3 This is a schematic diagram of the structure of a dynamic control system for single-blade headroom compensation of a wind turbine according to another embodiment of this disclosure;

[0046] Figure 4 This is a schematic diagram of the structure of an electronic device according to another embodiment of the present disclosure. Detailed Implementation

[0047] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. Based on the embodiments of this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this disclosure.

[0048] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0049] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0050] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another. Therefore, the first component discussed below may be referred to as the second component without departing from the teachings of this disclosure. As used in this disclosure, the term "and / or" includes all combinations of any and more of the associated listed items.

[0051] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of exemplary embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing this disclosure, and therefore cannot be used to limit the scope of protection of this disclosure.

[0052] like Figure 1 As shown, one embodiment of this disclosure provides a dynamic control method for single-blade headroom compensation of a wind turbine, the method comprising:

[0053] Step S1: Obtain the current wind speed, current turbulence intensity, and current passage cycle of the fan.

[0054] Specifically, the wind speed, turbulence intensity, and the current passage cycle of the blades about to pass over the tower are obtained based on various sensors, measuring instruments, PLCs, etc., commonly found in existing wind turbines. The formula and calculation process for turbulence intensity have clear standard provisions, namely the ratio of the standard deviation of wind speed to the average wind speed over ten minutes. However, in real-time control, such calculations consume significant resources and cannot quickly reflect changes in current wind speed. Therefore, in this embodiment, the turbulence intensity is obtained by calculating the ratio of the standard deviation of wind speed to the moving average of wind speed over three minutes. The current passage cycle of the blades passing over the tower is divided into the coincidence period of the rotor rotation cycle and the tower vibration cycle, the coincidence period of the rotor rotation cycle and the blade vibration cycle, and the common coincidence period of all three. This is obtained based on the analysis of the rotor speed, the first-order out-of-plane vibration mode of the tower, and the first-order out-of-plane vibration mode of the blades.

[0055] Step S2: Based on the current wind speed, the current turbulence intensity, and the current passage period, obtain the optimal pitch compensation value that meets the clearance requirements in the corresponding data cluster.

[0056] Specifically, the optimal pitch compensation value in this embodiment is obtained based on data clustering and confidence level calculation. The data clustering used is pre-established based on three dimensions: wind speed, turbulence intensity, and passage period. The steps are as follows:

[0057] 1. Obtain a large number of headroom values ​​and corresponding wind speed, turbulence intensity, and throughput data sets from historical data of existing wind turbines or bladed simulation experiments of new turbine models. The number of data sets needs to be sufficient for confidence level statistics. For existing wind turbines, headroom values ​​can be obtained using a headroom measurement lidar installed below the nacelle, such as the Molas CL4 headroom radar, which is based on the Time-of-Flight (ToF) principle to measure the distance from different blade positions to the nacelle, thereby deriving the distance from the blades to the tower. Bladed simulations can easily set the required wind speed, turbulence intensity, and other environmental conditions, making it easy to obtain sufficient data before the new turbine model is built. The headroom values ​​and other data obtained through the above process can be directly stored in the PLC for subsequent calculations.

[0058] 2. Perform a first-order clustering of the clearance values ​​based on the wind speed dimension. In a specific embodiment, the wind turbine operates in a wind speed range of 3m / s to 20m / s. When the wind speed is in the range of (3m / s, 8m / s), it is considered a low-wind zone, and the wind speed dimension value i = 1 is determined; when the wind speed is in the range of (8m / s, 12m / s), it is considered a rated wind speed zone, and the wind speed dimension value i = 2 is determined; when the wind speed is in the range of (12m / s, 20m / s), it is considered a high-wind zone, and the wind speed dimension value i = 3 is determined. Based on this, the clearance value data is divided into three groups of first-order clustered data. It can be understood that... Based on the characteristics of the wind turbine, the maximum blade thrust will occur near the rated wind speed. Below the rated wind speed, the wind turbine is in a low wind range with very small thrust and sufficient headroom. At this time, no headroom compensation is needed, and the optimal pitch compensation value can be directly determined as 0 to minimize the impact on normal unit control. There is no need to perform further subdivision clustering in the second and third dimensions. However, when the wind turbine is in the rated wind speed range and the high wind range, the thrust increases and the headroom is insufficient. Therefore, further subdivision clustering in the second dimension (turbulence intensity) and the third dimension (passage period) is required.

[0059] 3. Based on the turbulence intensity dimension value, a secondary clustering is performed on the data groups formed by the primary clustering. Considering that the primary clustering includes a wind speed dimension value i=1, a total of six secondary clustering data groups can be formed. Turbulence intensity has a significant impact on headroom. High turbulence intensity means large wind speed fluctuations, increased and irregular thrust change rate, making the blade headroom value change complex and reducing the minimum headroom value. In this embodiment, the turbulence intensity dimension is divided into a low turbulence intensity region, a normal turbulence intensity region, and a high turbulence intensity region. When the turbulence intensity is in the range (0,1], it is the low turbulence intensity region, and the turbulence intensity dimension value is determined to be j=1; when the turbulence intensity is in the range (1,2], it is the normal turbulence intensity region, and the turbulence intensity dimension value is determined to be j=2; when the turbulence intensity is greater than 2, it belongs to the high turbulence intensity region, and the turbulence intensity dimension value is determined to be j=3. It is understood that in practical applications, the specific boundary values ​​of the three turbulence intensity regions should be comprehensively considered based on the wind turbine model and the characteristics of the wind field.

[0060] 4. Based on the data from the secondary clustering using the periodic dimension value, a tertiary clustering is performed, ultimately resulting in eighteen subclasses of net clearance value data clusters. Under the same wind conditions, the net clearance values ​​of a single blade passing over the tower multiple times are not identical, and there is a recurring cycle. This pattern is determined by the characteristics of the wind turbine itself. Both the tower and the blades have their own natural vibration modes and mode shapes. The tower and blades are connected together in the form of multibody motion, forming unique vibration modes in multibody dynamics. Among these, the first-order out-of-plane vibration modes of the tower and the first-order out-of-plane vibration modes of the blades are the most important. The first-order out-of-plane vibration mode of the tower is denoted as W1 with the tower base as the fixed point, and its natural vibration frequency is denoted as f1. The blade is denoted as W2 with the blade root as the relatively fixed point, and its natural vibration frequency is denoted as f2. Simultaneously considering the rotation of the wind turbine, since the wind turbine speed has reached the rated speed in the rated wind speed and high wind areas, the wind turbine rotation frequency is fixed and denoted as W3, and the vibration period is denoted as f3. Therefore, the least common multiple of f1 and f3 is the coincidence period of the rotor rotation period and the tower vibration period, which may result in larger vibrations and thus smaller headroom. Similarly, the least common multiple of f2 and f3 is the coincidence period of the rotor rotation period and the blade vibration period, which may result in even larger vibrations and thus smaller headroom. The most dangerous is the coincidence period of the above three, that is, the least common multiple of f1, f2 and f3. At this time, the most severe vibration may be triggered, resulting in the smallest headroom. For example, if the first out-of-plane vibration mode of the tower is 0.25Hz, the first out-of-plane vibration mode of the blade is 0.5Hz, and the rotor frequency is 0.2Hz, then the period values ​​are f1 = 4s, f2 = 2s, f3 = 5s, and the least common multiple is 20s. As described above, after considering the modal characteristics of the main components of the unit to find the most unfavorable clearance cycle, the clearance cycle dimension value k for the three overlapping cycles is determined to be 1, 2, and 3 respectively, and three clusters are performed to finally obtain the clearance value data clusters corresponding to each wind speed dimension value, turbulence intensity dimension value, and clearance cycle dimension value.

[0061] After obtaining the net clearance data clustering, for each subclass, the minimum pitch compensation value L is used. ijk Start collecting data and recording clearance values ​​from 0, and calculate the confidence level of the obtained data for clearance values ​​not lower than the required clearance value (e.g., 8m). Then gradually increase the pitch compensation value, for example, L. ijk =0.5 Continue collecting data, while recording the clearance value, and calculate the confidence level of the obtained data for a clearance value not lower than the required clearance value, until the pitch compensation value L is reached. ijk The pitch compensation value L is increased until the collected data has a confidence level of 90% or higher for a value not lower than the required airspace value. ijk This represents the optimal pitch compensation value for the corresponding data cluster subclass. Ultimately, this yields a complete set of optimal pitch compensation values ​​required for airspace compensation under different wind conditions.

[0062] The above confidence level calculation process is a traditional probability and statistics process, requiring repeated simulations to collect data, which consumes significant computational resources. Statistical analysis reveals that, using the pitch compensation value as the input function, the confidence level obtained for a value not lower than the required clearance value exhibits a sigmf distribution characteristic. Therefore, this embodiment introduces the sigmf distribution as a confidence level function to describe the relationship between the pitch compensation value and the confidence level for meeting the required clearance value. The confidence level function expression is as follows:

[0063]

[0064] In the formula, λ is the pitch compensation value, a is the shape parameter of the distribution, c is the concentration parameter of the distribution, and e is the natural constant. When a takes a positive value, f is a monotonically increasing function with a limit of 1. This is consistent with the fact that the confidence probability is always within the interval [0,1], which conforms to the description of fuzzy mathematics.

[0065] By introducing the confidence function mentioned above, a small number of pitch compensation values ​​L can be used. ijk By fitting the data with the corresponding confidence level data, the specific values ​​of a and c can be obtained, which can then clearly reflect the pitch compensation value L. ijk The relationship between the pitch compensation value and its corresponding confidence level is then established, and then only an appropriate pitch compensation value L needs to be selected. ijk That's fine. For example... Figure 2 The figure shows the pitch compensation value L for a single blade of a wind turbine. ijk In the high wind region (i=3), high turbulence region (j=3), and subclass with period dimension value k=1, the confidence function is fitted to obtain a=2.5 and c=0.9. Based on the confidence function, the pitch compensation value L is taken at this point. 331 =5 is considered the optimal pitch compensation value, and the pitch compensation value L is suitable. 331 Even with further increases, the improvement in confidence level is limited.

[0066] Based on the current wind speed, current turbulence intensity, and current passage period obtained in the previous step S1, the dimension values ​​of the three are obtained respectively, and then the above method can be used to select the best pitch compensation value in the corresponding data cluster.

[0067] Step S3: Based on the original pitch angle of the current overpass blade, the rotor azimuth angle, and the optimal pitch compensation value, obtain the current overpass blade's clearance dynamic pitch strategy.

[0068] Specifically, to minimize the power loss due to wind turbine pitch control, this embodiment employs precise dynamic control of single-blade pitch compensation. The blades passing the tower begin pitch compensation 50° in advance, based on the original pitch angle set by the turbine. The maximum pitch angle is reached when the blades coincide with the tower. At this point, due to feathering, the blade thrust decreases from its original operating position, thereby increasing the clearance to meet the clearance requirements. Subsequently, the blades gradually return to their original pitch within a 50° azimuth angle after passing the tower, canceling the compensation. Meanwhile, the remaining blades continue to execute the original pitch control commands of the turbine, minimizing the impact on power output. The above dynamic pitch control strategy can be expressed as follows:

[0069]

[0070] In the formula, β is the pitch angle of the current tower blades. r For the original pitch angle, L ijk The optimal pitch compensation value is given by: i = wind speed, j = turbulence intensity, and k = passage period. This is the current azimuth angle of the blade. This is the azimuth angle when the blade coincides with the tower.

[0071] Taking a three-bladed wind turbine as an example, the azimuth angles of the three blades differ by 120°. Assuming the azimuth angle when the first blade coincides with the tower is 180°, the dynamic pitch control strategy for the first blade's headroom is expressed by the following formula:

[0072]

[0073] Similarly, the dynamic pitch control strategies for the second and third blades can be expressed as follows:

[0074]

[0075] The various statistical algorithms in steps S2 and S3 above can all be implemented in the PLC of the wind turbine itself using software, and can be embedded as a subroutine block in the overall unit control program of the PLC. The program can directly call the stored data in the PLC for calculation. The statistical process can be set to run once a week to reduce the PLC's operating resource consumption.

[0076] Step S4: Control the dynamic pitch of the current tower blades according to the aforementioned headroom dynamic pitch strategy.

[0077] Specifically, the pitch control system controls the pitch angle of each blade individually when it passes the tower, based on the headroom dynamic pitch strategy in the previous step S3, so that the headroom value meets the requirements.

[0078] This disclosure discloses a dynamic control method for single-blade clearance compensation of a wind turbine. By using a data clustering algorithm, the optimal pitch compensation value for the wind turbine under different wind conditions is found. Dynamic clearance compensation for a single blade is only performed when the blade passes through the tower. This improves the clearance value of flexible blades in large-capacity wind turbine units, significantly reduces the risk of tower sweeping during unit operation, enhances unit safety, and minimizes the impact on other loads and wind energy utilization efficiency of the unit. It can meet the clearance design requirements of large-megawatt units and greatly helps to reduce the cost and increase the efficiency of unit materials.

[0079] like Figure 3 As shown, another embodiment of this disclosure provides a dynamic control system for single-blade headroom compensation of a wind turbine, the system comprising:

[0080] The acquisition module 310 is used to acquire the current wind speed, current turbulence intensity and current passage cycle of the wind turbine;

[0081] The compensation module 320 is used to obtain the optimal pitch compensation value that meets the clearance requirements in the corresponding data cluster based on the current wind speed, the current turbulence intensity and the current passage period;

[0082] Strategy module 330 is used to obtain the current pitch dynamic pitch strategy for the current blade passing the tower based on the original pitch angle of the current blade passing the tower, the rotor azimuth angle and the optimal pitch compensation value.

[0083] Control module 340 is used to control the dynamic pitch of the current tower blades according to the headroom dynamic pitch strategy.

[0084] Specifically, the wind turbine single-blade clearance compensation dynamic control system of this disclosure is used to implement the wind turbine single-blade clearance compensation dynamic control method described in the above embodiments. The specific implementation process has been described in detail in the above embodiments and will not be repeated here.

[0085] This disclosure discloses a dynamic control system for single-blade headroom compensation in wind turbines. This system uses a data clustering algorithm to find the optimal pitch compensation value for different wind conditions and performs dynamic headroom compensation only when the blade passes over the tower. This improves the headroom value of flexible blades in large-capacity wind turbines, significantly reduces the risk of tower sweeping during turbine operation, enhances turbine safety, and minimizes the impact on other loads and wind energy utilization efficiency. It can meet the headroom design requirements of large-megawatt turbines and greatly contributes to cost reduction and efficiency improvement of turbine materials.

[0086] like Figure 4 As shown, another embodiment of this disclosure provides an electronic device, including:

[0087] At least one processor 401; and a memory 402 communicatively connected to the at least one processor 401 for storing one or more programs that, when executed by the at least one processor 401, enable the at least one processor 401 to implement the dynamic control method for single-blade headroom compensation of the wind turbine described above.

[0088] The memory 402 and processor 401 are connected via a bus, which may include any number of interconnecting buses and bridges. The bus connects various circuits of one or more processors 401 and memory 402 together. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by processor 401 is transmitted over a wireless medium via an antenna, which further receives data and transmits it to processor 401.

[0089] Processor 401 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory 402 can be used to store data used by processor 401 during operation.

[0090] Another embodiment of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the dynamic control method for single-blade headroom compensation of a wind turbine described above.

[0091] The computer-readable storage medium may be included in the systems or electronic devices disclosed herein, or it may exist independently.

[0092] Computer-readable storage media can be any tangible medium that contains or stores a program, and can be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, optical fibers, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0093] Computer-readable storage media may also include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code, specific examples of which include, but are not limited to, electromagnetic signals, optical signals, or any suitable combination thereof.

[0094] It is understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of this disclosure, and this disclosure is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this disclosure, and these modifications and improvements are also considered to be within the scope of protection of this disclosure.

Claims

1. A dynamic control method for single-blade headroom compensation in a wind turbine, characterized in that, The method includes: Obtain the current wind speed, current turbulence intensity, and current passage cycle of the wind turbine; Based on the current wind speed, the current turbulence intensity, and the current passage period, the optimal pitch compensation value that meets the clearance requirements in the corresponding data cluster is obtained, including: obtaining the wind speed dimension value based on the current wind speed, obtaining the turbulence intensity dimension value based on the current turbulence intensity, and obtaining the passage period dimension value based on the current passage period; determining the data cluster corresponding to the pitch compensation value based on the wind speed dimension value, the turbulence intensity dimension value, and the passage period dimension value; and determining the pitch compensation value that meets the clearance requirements in the data cluster as the optimal pitch compensation value; wherein... The step of obtaining the wind speed dimension value based on the current wind speed, the turbulence dimension value based on the current turbulence intensity, and the passage period dimension value based on the current passage period includes: determining the wind speed dimension value as 1 when the current wind speed is in the range of (3 m / s, 8 m / s), determining the wind speed dimension value as 2 when the current wind speed is in the range of (8 m / s, 12 m / s), and determining the wind speed dimension value as 3 when the current wind speed is in the range of (12 m / s, 20 m / s); and / or determining the turbulence dimension value when the current turbulence intensity is in the range of (0, 1). The turbulence dimension is set to 1 when the current turbulence intensity is within the range (1,2], and 2 when the current turbulence intensity is greater than 2; and / or, the passage period dimension is set to 1 when the current passage period coincides with the rotor rotation period and the tower vibration period, 2 when the current passage period coincides with the rotor rotation period and the blade vibration period, and 3 when the current passage period coincides with the rotor rotation period, the tower vibration period, and the blade vibration period; and, The data clustering is obtained through the following steps: acquiring multiple headroom values ​​of the wind turbine and the corresponding wind speed, turbulence intensity, and passage period for each headroom value; performing a first clustering of the multiple headroom values ​​based on the wind speed dimension value; performing a second clustering of each of the first clustering values ​​based on the turbulence intensity dimension value; and performing a third clustering of each of the second clustering values ​​based on the passage period dimension value, to obtain headroom value data clusters corresponding to each wind speed dimension value, turbulence intensity dimension value, and passage period dimension value. Based on the original pitch angle of the current overpass blade, the rotor azimuth angle, and the optimal pitch compensation value, the current overhead dynamic pitch strategy for the overpass blade is obtained; wherein, the overhead dynamic pitch strategy is expressed by the following formula: In the formula, β The pitch angle of the current tower blades. β r For the original pitch angle, L ijk For the optimal pitch compensation value, i This represents the wind speed dimension value. j This represents the turbulence dimension value. k To pass through the period dimension value, φ This is the current azimuth angle of the blade. φ 0 represents the azimuth angle when the blade coincides with the tower; The current pitch of the tower blades is controlled according to the aforementioned air clearance dynamic pitch strategy.

2. The method according to claim 1, characterized in that, The current turbulence intensity is the ratio of the standard deviation of wind speed over three minutes to the sliding average wind speed.

3. The method according to claim 1, characterized in that, The step of determining the pitch compensation value that meets the clearance requirements in the data cluster as the optimal pitch compensation value includes: Calculate the confidence level of the pitch compensation value relative to the preset clearance value; The pitch compensation value with a confidence level of 90% or higher is determined as the optimal pitch compensation value.

4. A dynamic control system for single-blade headroom compensation of a wind turbine, used to implement the dynamic control method for single-blade headroom compensation of a wind turbine as described in any one of claims 1 to 3, characterized in that, The system includes: The acquisition module is used to acquire the current wind speed, current turbulence intensity, and current passage cycle of the wind turbine; The compensation module is used to obtain the optimal pitch compensation value that meets the clearance requirements in the corresponding data cluster based on the current wind speed, the current turbulence intensity and the current passage period; The strategy module is used to obtain the current dynamic pitch strategy for the clearance of the current blade passing the tower based on the original pitch angle of the current blade passing the tower, the rotor azimuth angle, and the optimal pitch compensation value. The control module is used to control the dynamic pitch of the current tower blades according to the aforementioned headroom dynamic pitch strategy.

5. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor is used to store one or more programs, which, when executed by the at least one processor, enable the at least one processor to implement the wind turbine single-blade headroom compensation dynamic control method as described in any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the dynamic control method for wind turbine single-blade clearance compensation as described in any one of claims 1 to 3.

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