Equipment control method and device for wind turbine generator and electronic equipment

Abstract

The invention relates to the technical field of wind turbine generator control, in particular to an equipment control method and device for a wind turbine generator and electronic equipment.The method comprises the steps that equipment data and wind power data of the wind turbine generator are collected in real time, and a blade ionization loss coefficient is established according to the equipment data of the wind turbine generator; determining a blade aging state in a monitoring period, fusing the salt mist concentration and the environment humidity to construct a salt mist corrosion model, updating the blade aging state according to the wind power data and the salt mist corrosion model, obtaining vibration data of a tower drum of the wind turbine generator, and establishing a vibration model of the wind turbine generator; a blade vortex interference coefficient is calculated by combining wind power data with equipment data of the wind turbine generator, then the load state of the wind turbine generator is judged by combining a vibration model of the wind turbine generator and the blade vortex interference coefficient, and a hydraulic braking device in the wind turbine generator is controlled by combining the load state of the wind turbine generator with a blade aging state. The control efficiency of the wind turbine generator is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of wind turbine control technology, and in particular to a method, apparatus and electronic equipment for controlling wind turbines. Background Technology

[0002] Existing wind turbine equipment control technologies still have significant shortcomings in complex environments. Especially in the coupled environment of high humidity, salt spray, and strong winds at sea, blades are prone to ionization discharge, salt spray corrosion, and fatigue damage, leading to accelerated material aging and affecting power generation efficiency and equipment safety. Traditional control methods mostly rely on basic parameters such as wind speed and rotational speed, lacking dynamic assessment of blade aging status and comprehensive consideration of environmental factors.

[0003] Furthermore, existing systems rely on a limited range of methods to assess load conditions, making it difficult to accurately identify abnormal loads caused by vortex disturbances or mechanical vibrations. This leads to delayed or misjudged braking control responses. In particular, the combined effects of blade aging and external disturbances can easily trigger major malfunctions, hindering the reliability and maintenance efficiency of wind turbine operations. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, and electronic device for controlling wind turbine generators, in order to solve at least one of the problems existing in the prior art.

[0005] To achieve the above objectives, according to one aspect of this application, the present invention provides a device control method for a wind turbine generator, comprising: Real-time acquisition of equipment data and wind power data from wind turbine units; Based on the equipment data of the wind turbine, the blade ionization loss coefficient is established to determine the aging status of the blade within the monitoring period. A salt spray corrosion model is constructed by integrating salt spray concentration and ambient humidity, and the aging status of the blade is updated based on wind data and the salt spray corrosion model. Vibration data of the wind turbine tower is obtained and a vibration model of the wind turbine is established. The blade vortex interference coefficient is calculated by combining wind data with the equipment data of the wind turbine. Then, the load status of the wind turbine is judged by combining the vibration model of the wind turbine and the blade vortex interference coefficient. The hydraulic braking device inside the wind turbine is controlled based on the load status of the wind turbine and the aging status of the blades.

[0006] Optionally, the blade ionization loss coefficient is constructed using the equipment data of the wind turbine and denoted as λ. A blade ionization threshold is set to compare the blade ionization coefficient with the blade ionization threshold. The blade ionization state when the blade ionization coefficient is greater than or equal to the blade ionization threshold is determined to be abnormal; the blade ionization state when the blade ionization coefficient is less than the blade ionization threshold is determined to be normal. Calculate the ionization offset index when the blade ionization state is abnormal, and calculate the sum of each ionization offset index within the monitoring period. If the sum of the ionization offset indices within the monitoring period exceeds the interval detection threshold, the blade aging state within the monitoring period is determined to be abnormal; otherwise, the blade aging state within the monitoring period is determined to be normal.

[0007] Optionally, a corrosion risk index is established based on the wind turbine blade data within the monitoring period and set as CR, with CR=k1×Csalt / Cmax+k2×H / Hmax; where Csalt represents salt spray concentration, H represents ambient humidity, Cmax and Hmax represent salt spray concentration threshold and humidity threshold, respectively, k1 and k2 represent salt spray weight and humidity weight, respectively, and k1+k2=1.

[0008] Optionally, a risk threshold is set, and the offset ratio of the corrosion risk index relative to the risk threshold is used as the independent variable of the natural exponential function to obtain the value of the dependent variable of the natural exponential function. Then, the product of the value of the dependent variable of the natural exponential function and the blade ionization loss coefficient is used as the updated blade ionization loss coefficient. The aging status of the blades during the monitoring period was updated using the updated blade ionization loss coefficient.

[0009] Optionally, the vibration bearing capacity index α of the wind turbine can be constructed using the equipment data of the wind turbine and the vibration data of the wind turbine tower. Set a mechanical load threshold and determine the vibration load status by comparing the unit vibration load index with the mechanical load index: set the vibration load status when the unit vibration load index is greater than or equal to the mechanical load threshold as normal; otherwise, set the vibration load status as abnormal. The results of the vibration load condition assessment are used as the output of the vibration model of the wind turbine.

[0010] Optionally, the blade vortex interference coefficient is calculated by combining wind power data with the equipment data of the wind turbine. The calculation expression for the blade vortex interference coefficient is as follows: β=a1×(kK) / K+a2×|u1-u2| / U; In the formula, k represents the turbulence intensity at the blade tip, K represents the turbulence intensity threshold, u1 represents the blade tip wind speed, u2 represents the wind speed near the motor end of the blade, U represents the differential speed threshold, and a1 and a2 are the turbulence interference weight and wind speed difference interference weight, respectively.

[0011] Optionally, when the vibration load condition is normal, if the blade vortex interference coefficient is less than the vortex interference threshold, the load condition of the wind turbine is determined to be normal; if the blade vortex interference coefficient is greater than or equal to the vortex interference threshold, the load condition of the wind turbine is determined to be abnormal blade vortex load. When the vibration load condition is abnormal, if the blade vortex interference coefficient is greater than or equal to the vortex interference threshold, the load condition of the wind turbine is judged to be abnormal; if the blade vortex interference coefficient is less than the vortex interference threshold, the load condition of the wind turbine is judged to be abnormal mechanical load.

[0012] Optionally, when the wind turbine's load condition is abnormal blade eddy load, if the blade aging condition is abnormal, a blade damage alarm is sent to the user; if the blade aging condition is normal, no alarm information is sent to the user. When the wind turbine's load status is abnormal, an alarm for the turbine's load capacity will be sent to the user; when the wind turbine's load status is normal, no alarm information will be sent to the user. When the load condition of the wind turbine is abnormal, an overload alarm is sent to the user; When the alarm result is blade damage, a reverse torque F is applied to the wind turbine rotor by the hydraulic braking device inside the wind turbine unit; When the alarm result indicates abnormal mechanical load, the blade angle is set to feathering mode using the pitch control system. When the alarm result is an overload alarm, it is recommended that the user shut down the wind turbine generator set.

[0013] According to another aspect of this application, an equipment control device for a wind turbine generator is provided, comprising: The data acquisition module is used to collect equipment data and wind power data of the wind turbine in real time; The blade aging analysis module is used to establish the blade ionization loss coefficient based on the equipment data of the wind turbine, and then determine the aging status of the blade within the monitoring period. The corrosion update module is used to integrate salt spray concentration and ambient humidity to build a salt spray corrosion model, and update the aging status of the blades based on wind data and the salt spray corrosion model. The load status judgment module is used to acquire the vibration data of the wind turbine tower and establish the vibration model of the wind turbine. It calculates the blade vortex interference coefficient by combining the wind power data with the equipment data of the wind turbine, and then judges the load status of the wind turbine by combining the vibration model of the wind turbine and the blade vortex interference coefficient. The unit control module is used to control the hydraulic braking device inside the wind turbine based on the load status of the wind turbine and the aging status of the blades.

[0014] According to another aspect of this application, an electronic device is provided, the electronic device comprising: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the device control method for wind turbine units.

[0015] Compared with existing technologies, the advantages of this invention are as follows: By integrating equipment data, wind data, and environmental parameters, this invention constructs a blade ionization loss coefficient and a salt spray corrosion model, achieving dynamic and accurate assessment of blade aging status. Combining a vibration model with the blade vortex interference coefficient effectively improves the accuracy of wind turbine load status judgment. Furthermore, by comprehensively considering load status and blade aging information, intelligent control of the hydraulic braking device is implemented, enabling differentiated response strategies under various abnormal operating conditions, such as applying reverse torque, feathering protection, or shutdown recommendations, significantly enhancing the safety and stability of turbine operation. This solution improves the wind turbine's adaptability and control efficiency in complex environments, helps extend equipment life, reduces maintenance costs, and enhances the overall reliability of the wind power system. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the equipment control method for wind turbine generators in this embodiment.

[0018] Figure 2 This is a flowchart illustrating the wind turbine load status determination method in this embodiment.

[0019] Figure 3 This is a schematic diagram of the equipment control device for wind turbine generators provided in this embodiment.

[0020] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this embodiment. Detailed Implementation

[0021] To more clearly illustrate the present invention, the following description, in conjunction with preferred embodiments and accompanying drawings, further explains the invention. Similar components in the drawings are indicated by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0022] It should be noted that although the terms first, second, third, etc., may be used in the embodiments of this application for description, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of this application, first can also be referred to as second, and similarly, second can also be referred to as first.

[0023] The acquisition, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.

[0024] Specifically, the equipment control method for wind turbine generators provided in this application is applied to the intelligent control of offshore wind turbine generators in salt spray, high humidity, and typhoon environments. In this application scenario, wind turbine generators are susceptible to generator failures or blade damage due to energy loss caused by the interaction between blade tip discharge and wake, as well as material aging problems caused by the coupled environment of multiple factors such as turbulence, high humidity, and salt spray. The wind turbine generator described in this application is a horizontal axis wind turbine generator.

[0025] To apply the above-mentioned application scenarios, this application provides a device control method for wind turbine generators, the flowchart of which can be found in the document. Figure 1 As shown, it includes: Step S101: Collect equipment data and wind power data of the wind turbine in real time.

[0026] The equipment data of the wind turbine unit includes: the blade speed ratio, blade tip speed, generator torque, blade corona discharge amplitude, and blade corona discharge frequency; the blade speed ratio is specifically the number of revolutions of the wind turbine generator when the blade rotates one revolution, and this ratio is determined by the planetary acceleration gear inside the wind turbine unit. The wind data includes: wind speed, wind direction, atmospheric pressure, and blade tip speed ratio; the blade tip speed ratio is the ratio of the linear velocity at the tip of the blade in the wind turbine to the wind speed.

[0027] Specifically, the blade speed ratio in the equipment data of the wind turbine described in this application can be collected through user interaction; the blade corona discharge amplitude and frequency can be collected by setting high-frequency sensors at the blade tips; the wind power data can be obtained by wind power monitoring sensors and wind direction monitoring sensors on the wind turbine; real-time collection of equipment data and wind power data of the wind turbine provides a comprehensive and dynamic information foundation for subsequent status analysis. This step ensures that the control system can acquire key operating parameters in a timely manner, enhances its perception of the turbine's operating environment, improves the response speed and accuracy of the overall control strategy, and lays a data foundation for achieving intelligent and refined control.

[0028] Please continue reading. Figure 1 As shown, the equipment control method for wind turbine generators further includes: Step S102: Establish the blade ionization loss coefficient based on the equipment data of the wind turbine, and then determine the blade aging status within the monitoring period; the duration of the monitoring period mentioned in this application is 1 day.

[0029] Specifically, in step S102, the process of determining the aging state of the blades within the monitoring period is as follows: The blade ionization loss coefficient is constructed using the equipment data of the wind turbine and denoted as λ. The formula is set as λ = b1×E / E0 + b3×df / DF + b3×yv / Yv. In the formula, E is the blade corona discharge amplitude, df is the blade corona discharge frequency, yv is the blade tip speed, b1, b2 and b3 are the weights of corona discharge amplitude, corona discharge frequency and blade tip speed, respectively, and b1+b2+b3=1. E0, DF and Yv are the thresholds of blade corona discharge amplitude, blade corona discharge frequency and blade tip speed, respectively. A blade ionization threshold is set to compare the blade ionization coefficient with the blade ionization threshold. The blade ionization state when the blade ionization coefficient is greater than or equal to the blade ionization threshold is determined to be abnormal; the blade ionization state when the blade ionization coefficient is less than the blade ionization threshold is determined to be normal. Calculate the ionization offset index when the blade ionization state is abnormal, and calculate the sum of each ionization offset index within the monitoring period. If the sum of the ionization offset indices within the monitoring period exceeds the interval detection threshold, the blade aging state within the monitoring period is determined to be abnormal; otherwise, the blade aging state within the monitoring period is determined to be normal.

[0030] Specifically, the blade ionization threshold value in this application is 0.8; the interval detection threshold value is 5; the ionization offset index in this application is the offset coefficient of the blade electric coefficient relative to the ionization threshold; at the same time, the values ​​of the blade corona discharge amplitude threshold, the blade corona discharge frequency threshold, and the blade tip velocity threshold in this application are all set according to the wind turbine safety standards.

[0031] Specifically, by constructing a blade ionization loss coefficient and combining it with ionization state analysis, a preliminary assessment of the blade's aging state can be achieved. This method effectively identifies material performance degradation caused by corona discharge, assesses aging trends using the cumulative offset index within the monitoring period, improves the early warning capability for early aging faults, and enhances the scientific rigor and reliability of blade health status monitoring.

[0032] Please continue reading. Figure 1 As shown, the equipment control method for wind turbine generators further includes: Step S103: Construct a salt spray corrosion model by integrating salt spray concentration and ambient humidity, and update the aging status of the blades based on wind data and the salt spray corrosion model.

[0033] Specifically, the monitoring period in this application is 1 day.

[0034] Specifically, in step S103, environmental data of the wind turbine during the monitoring period needs to be obtained before constructing the salt spray corrosion model; the environmental data includes salt spray concentration and ambient humidity; in this application, the environmental data of the wind turbine can be obtained through relevant sensors inside the wind turbine.

[0035] Specifically, in step S103, the process of constructing a salt spray corrosion model using environmental data from the wind turbine is as follows: A corrosion risk index was established based on the annual wind turbine blade data during the monitoring period, and it was set as CR. The formula is: CR = k1 × Csalt / Cmax + k2 × H / Hmax; where Csalt represents the salt spray concentration, H represents the ambient humidity, Cmax and Hmax represent the salt spray concentration threshold and humidity threshold, respectively, k1 and k2 represent the salt spray weight and humidity weight, respectively, and k1 + k2 = 1. Set a risk threshold and use the offset ratio of the corrosion risk index relative to the risk threshold as the independent variable of the natural exponential function to obtain the value of the dependent variable of the natural exponential function. Then, use the product of the value of the dependent variable of the natural exponential function and the blade ionization loss coefficient as the updated blade ionization loss coefficient. The aging status of the blades during the monitoring period was updated using the updated blade ionization loss coefficient.

[0036] Specifically, the salt spray concentration threshold and humidity threshold mentioned in this application are taken as the observed values ​​of salt spray concentration and humidity when the blade surface has a salt scale thickness of 0.2 mm during the monitoring period.

[0037] Specifically, a salt spray corrosion model was constructed by integrating salt spray concentration and ambient humidity, and the aging status of the blades was dynamically updated, fully considering the long-term corrosive effects of the high-humidity and high-salt marine environment on the materials. This step improved the environmental adaptability of the aging assessment, made the condition judgment closer to actual working conditions, and significantly enhanced the robustness and prediction accuracy of the system in harsh environments.

[0038] Please continue reading. Figure 1 As shown, the equipment control method for wind turbine generators further includes: Step S104: Obtain vibration data of the wind turbine tower and establish a vibration model of the wind turbine. Calculate the blade vortex interference coefficient using wind power data and equipment data of the wind turbine. Then, combine the vibration model of the wind turbine and the blade vortex interference coefficient to determine the load status of the wind turbine.

[0039] Please see Figure 2 As shown, it is a flowchart illustrating the wind turbine load state determination method provided in this application, including: Step S401: Obtain vibration data of the wind turbine tower; the vibration data of the wind turbine tower includes: vibration amplitude of the wind turbine tower and vibration frequency of the wind turbine tower.

[0040] Please continue reading. Figure 2 As shown, the wind turbine load status determination method further includes: Step S402: Establish a vibration model of the wind turbine based on the vibration data of the wind turbine tower and the equipment data of the wind turbine.

[0041] Specifically, in step S402, the process of constructing the vibration model of the wind turbine is as follows: The vibration load index of the wind turbine is constructed using the equipment data and vibration data of the wind turbine tower. The expression for the vibration load index is as follows: α = Tv / Yv + Tf / Yf; In the formula, α represents the vibration load index of the unit, Tv represents the vibration frequency of the wind turbine tower, Tf represents the vibration amplitude of the wind turbine tower, Yv represents the vibration frequency of the wind turbine blade, and Yf ​​represents the vibration amplitude of the wind turbine blade. Set a mechanical load threshold and determine the vibration load status by comparing the unit vibration load index with the mechanical load index: set the vibration load status when the unit vibration load index is greater than or equal to the mechanical load threshold as normal; otherwise, set the vibration load status as abnormal. The results of the vibration load condition assessment are used as the output of the vibration model of the wind turbine.

[0042] Specifically, the mechanical load threshold value described in this application is 1.2.

[0043] It is worth noting that when constructing the vibration bearing index of the wind turbine unit from the equipment data of the wind turbine unit and the vibration data of the wind turbine tower in this application, the relevant vibration data used needs to be preprocessed to eliminate noise and interference vibration.

[0044] Please continue reading. Figure 2 As shown, the wind turbine load status determination method further includes: Step S403: Calculate the blade vortex interference coefficient using wind power data combined with the wind turbine's equipment data. The calculation expression for the blade vortex interference coefficient is as follows: β=a1×(kK) / K+a2×|u1-u2| / U; In the formula, k represents the turbulence intensity at the blade tip, K represents the turbulence intensity threshold, u1 represents the blade tip wind speed, u2 represents the wind speed near the motor end of the blade, U represents the differential speed threshold, and a1 and a2 are the turbulence interference weight and wind speed difference interference weight, respectively.

[0045] It is worth noting that the turbulence intensity at the blade tip position described in this application is acquired by collecting the wind speed standard deviation measured by an anemometer; at the same time, the differential speed threshold value in this application is 5 m / s, and the turbulence intensity threshold value is 0.15.

[0046] Please continue reading. Figure 2 As shown, the wind turbine load status determination method further includes: Step S404: Combine the vibration model of the wind turbine with the blade vortex interference coefficient to determine the load status of the wind turbine.

[0047] When the vibration load condition is normal, if the blade vortex interference coefficient is less than the vortex interference threshold, the load condition of the wind turbine is determined to be normal; if the blade vortex interference coefficient is greater than or equal to the vortex interference threshold, the load condition of the wind turbine is determined to be abnormal blade vortex load. When the vibration load condition is abnormal, if the blade vortex interference coefficient is greater than or equal to the vortex interference threshold, the load condition of the wind turbine is judged to be abnormal; if the blade vortex interference coefficient is less than the vortex interference threshold, the load condition of the wind turbine is judged to be abnormal mechanical load.

[0048] Specifically, the eddy current interference threshold value described in this application is 0.75.

[0049] Specifically, by establishing a vibration model and calculating the blade vortex interference coefficient, the load status of the wind turbine is comprehensively judged. This method achieves synergistic analysis of mechanical vibration and aerodynamic interference, accurately identifies different types of load anomalies, improves the system's ability to identify complex dynamic loads, and provides a reliable basis for precise control.

[0050] Please continue reading. Figure 1 As shown, the equipment control method for wind turbine generators further includes: Step S105: Control the hydraulic braking device inside the wind turbine based on the load status of the wind turbine and the aging status of the blades.

[0051] Specifically, in step S105, before controlling the hydraulic braking device inside the wind turbine, a status alarm needs to be issued to the user based on the load status and blade aging status of the wind turbine. The process is as follows: When the load condition of the wind turbine is abnormal blade eddy load, if the blade aging condition is abnormal, a blade damage alarm will be sent to the user; if the blade aging condition is normal, no alarm information will be sent to the user. When the wind turbine's load status is abnormal, an alarm for the turbine's load capacity will be sent to the user; when the wind turbine's load status is normal, no alarm information will be sent to the user. When the load condition of the wind turbine is abnormal, an overload alarm is sent to the user.

[0052] Specifically, in step S105, the process of controlling the hydraulic braking device inside the wind turbine is as follows: When the alarm result is blade damage alarm, the hydraulic braking device inside the wind turbine applies a reverse torque F to the wind turbine rotor. F is set as F = f × exp{(sum of power offset indices within the monitoring period - interval detection threshold) / interval detection threshold}; f is the magnitude of the reverse torque within the monitoring period. When the alarm result indicates abnormal mechanical load, the blade angle is set to feathering mode using the pitch control system. When the alarm result is an overload alarm, it is recommended that the user shut down the wind turbine generator set.

[0053] Specifically, the hydraulic braking system is intelligently controlled by combining load conditions and blade aging status, enabling differentiated and adaptive response strategies. Under different alarm conditions, reverse torque, feathering, or shutdown recommendations are implemented, effectively preventing the escalation of faults, improving unit safety and operational stability, and significantly enhancing the wind turbine's self-protection capabilities under extreme conditions.

[0054] Please see Figure 4 The diagram shown is a structural schematic of the equipment control device for wind turbine generators provided in this application, including: The data acquisition module is used to collect equipment data and wind power data of the wind turbine in real time; The blade aging analysis module is used to establish the blade ionization loss coefficient based on the equipment data of the wind turbine, and then determine the aging status of the blade within the monitoring period. The corrosion update module is used to integrate salt spray concentration and ambient humidity to build a salt spray corrosion model, and update the aging status of the blades based on wind data and the salt spray corrosion model. The load status judgment module is used to acquire the vibration data of the wind turbine tower and establish the vibration model of the wind turbine. It calculates the blade vortex interference coefficient by combining the wind power data with the equipment data of the wind turbine, and then judges the load status of the wind turbine by combining the vibration model of the wind turbine and the blade vortex interference coefficient. The unit control module is used to control the hydraulic braking device inside the wind turbine based on the load status of the wind turbine and the aging status of the blades.

[0055] The equipment control device for wind turbines provided in this application can execute the equipment control method for wind turbines provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the method.

[0056] From a hardware perspective, to enable the implementation of the aforementioned equipment control method for wind turbine generators in a computer, this application also provides an electronic device; please refer to [link to relevant documentation]. Figure 4 As shown, it is a schematic diagram of the structure of the electronic device described in this application, including: The system comprises a processor 1, a memory 2, a communication interface 3, and a bus 4; wherein the processor 1 and the memory 2, and the memory 2 and the communication interface 3, transmit data via the bus 4; the processor is used to process data in the memory and generate commands, the memory is used to store data, the communication interface is used to receive and send data, and the bus is used to realize data transmission between the processor, the memory, and the communication interface.

[0057] In this embodiment, the equipment control method for wind turbines can be implemented as a runnable computer program. When the computer program is loaded into a processor or memory and processed by the processor via a bus, one or more steps of the equipment control method for wind turbines can be executed.

[0058] This embodiment also provides a computer-readable storage medium for storing the computer-executable instructions. The computer-readable storage medium is a tangible physical storage medium that can store the computer program and various types of data used in the program. The physical storage medium includes, but is not limited to, existing physical storage media or combinations thereof, such as random access memory, read-only memory, optical disk, and hard disk.

[0059] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for controlling equipment in a wind turbine generator set, characterized in that, include: Based on the equipment data of the wind turbine, the blade ionization loss coefficient is established to determine the aging status of the blade within the monitoring period. A salt spray corrosion model is constructed by integrating salt spray concentration and ambient humidity, and the aging status of the blade is updated based on wind data and the salt spray corrosion model. Vibration data of the wind turbine tower is obtained and a vibration model of the wind turbine is established. The blade vortex interference coefficient is calculated by combining wind data with the equipment data of the wind turbine. Then, the load status of the wind turbine is judged by combining the vibration model of the wind turbine and the blade vortex interference coefficient. The hydraulic braking device inside the wind turbine is controlled based on the load status of the wind turbine and the aging status of the blades.

2. The equipment control method for wind turbine generators according to claim 1, characterized in that, The blade ionization loss coefficient is constructed using the equipment data of the wind turbine and denoted as λ. Set a blade ionization threshold to compare the blade ionization coefficient with the blade ionization threshold, and determine the blade ionization state when the blade ionization coefficient is greater than or equal to the blade ionization threshold as abnormal; The blade ionization state when the blade ionization coefficient is less than the blade ionization threshold is defined as normal. Calculate the ionization offset index when the blade ionization state is abnormal, and calculate the sum of each power offset index within the monitoring period. When the sum of the power offset index within the monitoring period exceeds the interval detection threshold, the blade aging state within the monitoring period is determined to be abnormal. Conversely, the aging state of the leaves is considered normal within a defined monitoring period.

3. The equipment control method for wind turbine generators according to claim 2, characterized in that, A corrosion risk index was established based on the annual wind turbine blade data during the monitoring period, and it was set as CR. The formula is CR=k1×Csalt / Cmax+k2×H / Hmax; where Csalt represents salt spray concentration, H represents ambient humidity, Cmax and Hmax represent salt spray concentration threshold and humidity threshold, respectively, k1 and k2 are salt spray weight and humidity weight, respectively, and k1+k2=1.

4. The equipment control method for wind turbine generators according to claim 3, characterized in that, Set a risk threshold and use the offset ratio of the corrosion risk index relative to the risk threshold as the independent variable of the natural exponential function to obtain the value of the dependent variable of the natural exponential function. Then, use the product of the value of the dependent variable of the natural exponential function and the blade ionization loss coefficient as the updated blade ionization loss coefficient. The aging status of the blades during the monitoring period was updated using the updated blade ionization loss coefficient.

5. The equipment control method for wind turbine generators according to claim 4, characterized in that, The vibration bearing capacity index α of the wind turbine is constructed using the equipment data of the wind turbine and the vibration data of the wind turbine tower. Set a mechanical load threshold and determine the vibration load status by comparing the unit vibration load index with the mechanical load index: set the vibration load status when the unit vibration load index is greater than or equal to the mechanical load threshold as normal; otherwise, set the vibration load status as abnormal. The results of the vibration load condition assessment are used as the output of the vibration model of the wind turbine.

6. The equipment control method for wind turbine generators according to claim 5, characterized in that, The blade vortex interference coefficient is calculated by combining wind power data with wind turbine equipment data. The expression for calculating the blade vortex interference coefficient is as follows: β=a1×(kK) / K+a2×|u1-u2| / U; In the formula, k represents the turbulence intensity at the blade tip, K represents the turbulence intensity threshold, u1 represents the blade tip wind speed, u2 represents the wind speed near the motor end of the blade, U represents the differential speed threshold, and a1 and a2 are the turbulence interference weight and wind speed difference interference weight, respectively.

7. The equipment control method for wind turbine generators according to claim 6, characterized in that, When the vibration load condition is normal, if the blade vortex interference coefficient is less than the vortex interference threshold, the load condition of the wind turbine is determined to be normal. If the blade vortex interference coefficient is greater than or equal to the vortex interference threshold, the load status of the wind turbine is determined to be abnormal blade vortex load. When the vibration load condition is abnormal, if the blade vortex interference coefficient is greater than or equal to the vortex interference threshold, the load condition of the wind turbine is judged to be abnormal. If the blade vortex interference coefficient is less than the vortex interference threshold, the load status of the wind turbine is judged to be abnormal mechanical load.

8. The equipment control method for wind turbine generators according to claim 7, characterized in that, When the load condition of the wind turbine is abnormal blade eddy load, if the blade aging condition is abnormal, a blade damage alarm will be sent to the user; if the blade aging condition is normal, no alarm information will be sent to the user. When the wind turbine's load status is abnormal, an alarm for the turbine's load capacity will be sent to the user; when the wind turbine's load status is normal, no alarm information will be sent to the user. When the load condition of the wind turbine is abnormal, an overload alarm is sent to the user; When the alarm result is blade damage, a reverse torque F is applied to the wind turbine rotor by the hydraulic braking device inside the wind turbine unit; When the alarm result indicates abnormal mechanical load, the blade angle is set to feathering mode using the pitch control system. When the alarm result is an overload alarm, it is recommended that the user shut down the wind turbine generator set.

9. An equipment control device for a wind turbine generator set, applied to the equipment control method for a wind turbine generator set as described in any one of claims 1-8, characterized in that, include: The data acquisition module is used to collect equipment data and wind power data of the wind turbine in real time; The blade aging analysis module is used to establish the blade ionization loss coefficient based on the equipment data of the wind turbine, and then determine the aging status of the blade within the monitoring period. The corrosion update module is used to integrate salt spray concentration and ambient humidity to build a salt spray corrosion model, and update the aging status of the blades based on wind data and the salt spray corrosion model. The load status judgment module is used to acquire the vibration data of the wind turbine tower and establish the vibration model of the wind turbine. It calculates the blade vortex interference coefficient by combining the wind power data with the equipment data of the wind turbine, and then judges the load status of the wind turbine by combining the vibration model of the wind turbine and the blade vortex interference coefficient. The unit control module is used to control the hydraulic braking device inside the wind turbine based on the load status of the wind turbine and the aging status of the blades.

10. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the equipment control method for wind turbines as described in any one of claims 1-8.

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