Wind turbine generator transient data processing method and system based on IPC hardware platform

Abstract

The invention relates to the technical field of wind power data processing, and particularly discloses a wind turbine generator transient data processing method and system based on an IPC hardware platform, and the method comprises the steps: collecting the equipment state data, key operation data and environment data of a wind turbine generator; processing the equipment state data to obtain an equipment state abnormity evaluation index, processing the key operation data to obtain a wind turbine generator stability evaluation index, and performing comprehensive analysis to obtain a wind turbine generator fault evaluation value; and the IPC hardware platform generates an evaluation report of the wind turbine generator. According to the wind turbine generator transient data processing method and system based on the IPC hardware platform, operation and maintenance personnel can be helped to quickly and accurately position the fault position of the wind turbine generator, making of a more scientific and reasonable maintenance plan is facilitated, the maintenance efficiency is improved, and the maintenance cost is reduced. And the fault type and severity can be quickly judged, a corresponding emergency response plan can be formulated, and the emergency response speed and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power data processing, and in particular to a method and system for processing transient data of a wind turbine generator set based on an IPC hardware platform. Background Art

[0002] At present, wind turbine transient data processing is a very important part of the field of wind power data processing technology. With the advancement of technology and the growth of market demand, improving more refined wind turbine transient data processing methods has become the norm. Efficient and accurate wind turbine transient data systems are crucial.

[0003] For example, the invention patent with announcement number CN113806907B is a method and device for processing electromechanical transient data of a doubly fed wind turbine generator set. The method includes: obtaining basic parameters of the doubly fed wind turbine generator set under low voltage ride-through conditions; determining the active control data and reactive control data of the doubly fed wind turbine generator set during and after the low voltage ride-through period based on the basic parameters and the least squares parameter identification rules; determining the low voltage ride-through characteristics of the doubly fed wind turbine generator set based on the active control data, reactive control data, low voltage ride-through implementation method data, and low voltage ride-through status judgment data of the doubly fed wind turbine generator set.

[0004] For example, the invention patent with announcement number CN109918733B is a method for electromagnetic transient equivalent modeling of a doubly fed wind turbine generator set, including: establishing an electromagnetic transient simulation model of a doubly fed wind turbine generator set according to the topological structure of the doubly fed wind turbine generator set simulation system, and obtaining the admittance array elements and node injection current sources of the simulation system according to the electrical connection relationship of each module of the simulation system; obtaining the historical injection current of the equivalent model according to the equivalent admittance array to obtain the system equivalent model; solving the system equivalent model and the external power grid jointly to obtain the node voltage of each electrical node inside the doubly fed wind turbine generator set and the branch current of each model; at the same time, calculating the historical injection current source of each module in the next simulation time step according to the node voltage and branch current of the current time step; solving the non-electrical part according to the branch current and node voltage; and judging whether to update the admittance array elements in the next simulation time step.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: the current wind turbine transient data processing method focuses more on the real-time data acquisition, but the collection of wind turbine operating status data is not comprehensive enough, and the accuracy of data processing is difficult to guarantee. Summary of the Invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for processing transient data of a wind turbine generator set based on an IPC hardware platform, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: In the first aspect of the present invention, a method for processing transient data of a wind turbine based on an IPC hardware platform is provided, including: collecting equipment status data, key operation data, and environmental data of the wind turbine.

[0008] Process the equipment status data to obtain an equipment status anomaly evaluation index, process the key operation data to obtain a wind turbine stability evaluation index, process the environmental data to obtain an environmental interference value, and comprehensively analyze to obtain a wind turbine fault evaluation value.

[0009] The IPC hardware platform generates an evaluation report of the wind turbine based on the wind turbine fault evaluation value and gives feedback.

[0010] As a further method, the process of processing the equipment status data to obtain an equipment status anomaly evaluation index is as follows: The equipment status data includes the voltage values of each stator winding, the current values of each stator winding, the output power, and the grid frequency.

[0011] Extract the reference standard voltage value, allowable deviation voltage value, reference standard current value, allowable deviation current value, reference standard output power, allowable deviation output power, reference standard grid frequency, and allowable deviation grid frequency from the wind turbine database, and comprehensively analyze to obtain the equipment status anomaly evaluation index.

[0012] As a further method, the process of processing the key operation data to obtain a wind turbine stability evaluation index is as follows: The key operation data includes the temperature of each temperature monitoring point, the vibration frequency of each vibration monitoring point, and the generator speed.

[0013] Extract the reference standard temperature, allowable deviation temperature, reference standard vibration frequency, allowable deviation vibration frequency, reference standard speed, and allowable deviation speed from the wind turbine database, comprehensively analyze to obtain the wind turbine stability evaluation index, and adjust the pitch angle of the blade according to the wind turbine stability evaluation index.

[0014] As a further method, the process of processing the environmental data to obtain an environmental interference value is as follows: The environmental data includes the environmental temperature, environmental humidity, and wind speed.

[0015] Extract the reference standard environmental temperature, allowable deviation environmental temperature, reference standard environmental humidity, allowable deviation environmental humidity, and critical wind speed from the wind turbine database, and comprehensively analyze to obtain the environmental interference value.

[0016] As a further method, the comprehensive analysis obtains a fault evaluation value of the wind turbine. The specific analysis process is as follows: According to the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value, a comprehensive analysis is performed to obtain the fault evaluation value of the wind turbine. The fault evaluation value of the wind turbine is used to quantify the fault degree of the wind turbine.

[0017] As a further method, the pitch angle of the blade is adjusted according to the wind turbine stability evaluation index. The specific analysis process is as follows: The wind turbine stability evaluation threshold is extracted from the wind turbine database, and the wind turbine stability evaluation index is compared with the wind turbine stability evaluation threshold. If the wind turbine stability evaluation index is greater than or equal to the wind turbine stability evaluation threshold, no additional operation is performed. If the wind turbine stability evaluation index is less than the wind turbine stability evaluation threshold, the pitch angle of the blade is adjusted smaller until the wind turbine stability evaluation index is greater than or equal to the wind turbine stability evaluation threshold.

[0018] As a further method, the IPC hardware platform generates an evaluation report of the wind turbine based on the fault evaluation value of the wind turbine and gives feedback. The specific evaluation process is as follows: The first wind turbine fault evaluation threshold and the second wind turbine fault evaluation threshold are extracted from the wind turbine database, and the wind turbine fault evaluation value is compared with the first wind turbine fault evaluation threshold. If the wind turbine fault evaluation value is greater than or equal to the first wind turbine fault evaluation threshold, the maintenance strategy of the wind turbine is adjusted. At the same time, it is judged whether the wind turbine fault evaluation value is greater than the second wind turbine fault evaluation threshold. If the wind turbine fault evaluation value is less than the first wind turbine fault evaluation threshold, no additional operation is performed.

[0019] An evaluation report is generated according to the comparison results of the wind turbine fault evaluation value with the first and second wind turbine fault evaluation thresholds.

[0020] As a further method, the adjustment of the maintenance strategy of the wind turbine. The specific adjustment process is as follows: The maintenance strategy of the wind turbine refers to the maintenance frequency of the wind turbine.

[0021] Obtain the initial maintenance frequency of the wind turbine, input the wind turbine fault evaluation value into the wind turbine database to match the maintenance frequency compensation value corresponding to each wind turbine fault evaluation value interval, add the initial maintenance frequency and the maintenance frequency compensation value to obtain the updated maintenance frequency, and perform maintenance on the wind turbine according to the updated maintenance frequency.

[0022] As a further method, the fault evaluation value of the wind turbine. The specific numerical expression is:

[0023]

[0024] Among them, Wb represents the fault evaluation value of the wind turbine, Mu represents the equipment status anomaly evaluation index, Ws represents the wind turbine stability evaluation index, En represents the environmental interference value, θ1 represents the influence factor of the wind turbine fault evaluation corresponding to the set equipment status anomaly evaluation index, θ2 represents the influence factor of the wind turbine fault evaluation corresponding to the set wind turbine stability evaluation index, and θ3 represents the influence factor of the wind turbine fault evaluation corresponding to the set environmental interference value.

[0025] The second aspect of the present invention provides a wind turbine transient data processing system based on the IPC hardware platform, including: a data acquisition module for acquiring equipment status data, key operation data, and environmental data of the wind turbine.

[0026] A wind turbine fault analysis module for processing the equipment status data to obtain the equipment status anomaly evaluation index, processing the key operation data to obtain the wind turbine stability evaluation index, processing the environmental data to obtain the environmental interference value, and comprehensively analyzing to obtain the wind turbine fault evaluation value.

[0027] A wind turbine evaluation module, and the IPC hardware platform generates an evaluation report of the wind turbine based on the wind turbine fault evaluation value and gives feedback.

[0028] Compared with the prior art, the embodiments of the present invention at least have the following advantages or beneficial effects:

[0029] (1) By providing a wind turbine transient data processing method and system based on the IPC hardware platform, the present invention can help the operation and maintenance personnel quickly and accurately locate the fault position of the wind turbine, contribute to formulating a more scientific and reasonable maintenance plan, thereby improving the maintenance efficiency, and can also quickly judge the fault type and severity, and formulate corresponding emergency response plans to improve the emergency response speed and accuracy.

[0030] (2) By evaluating the equipment status anomaly evaluation index, the present invention helps to take preventive measures before the occurrence of faults, can understand the wear and aging degree of each component of the wind turbine, thereby formulating a reasonable maintenance plan, can also reduce unnecessary maintenance and inspection times, and the operation and maintenance personnel can carry out repairs or replacements targeted to avoid over-maintenance or missed maintenance.

[0031] (3) By evaluating the wind turbine stability evaluation index, the present invention helps to ensure that the wind turbine operates in the best state, thereby improving the power generation efficiency, increasing the power output, and can also reduce the losses caused by fault shutdowns. Further, more effective risk management measures can be formulated to improve the overall safety of the wind farm. Description of the Drawings

[0032] The present invention will be further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the following drawings without creative efforts.

[0033] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0034] Figure 2 It is a schematic diagram of the connection of system modules of the present invention.

[0035] Figure 3 It is a schematic diagram of the functional relationship between the fault evaluation value of the wind turbine and the abnormal evaluation index of the equipment state of the present invention. Detailed implementation manners

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0037] Refer to Figure 1 As shown, the first aspect of the present invention provides a method for processing transient data of a wind turbine based on an IPC hardware platform, including: collecting equipment state data, key operation data, and environmental data of the wind turbine.

[0038] Process the equipment state data to obtain an abnormal evaluation index of the equipment state, process the key operation data to obtain a stability evaluation index of the wind turbine, process the environmental data to obtain an environmental interference value, and comprehensively analyze to obtain a fault evaluation value of the wind turbine.

[0039] The IPC hardware platform generates an evaluation report of the wind turbine according to the fault evaluation value of the wind turbine and gives feedback.

[0040] Specifically, processing the equipment state data to obtain an abnormal evaluation index of the equipment state, the specific processing process is: the equipment state data includes the voltage values of each stator winding, the current values of each stator winding, the output power, and the grid frequency.

[0041] Extract the reference standard voltage value, allowable deviation voltage value, reference standard current value, allowable deviation current value, reference standard output power, allowable deviation output power, reference standard grid frequency, and allowable deviation grid frequency from the wind turbine database, and comprehensively analyze to obtain an abnormal evaluation index of the equipment state.

[0042] In a specific embodiment, the voltage values of each stator winding can be obtained through a digital voltmeter, and the current values of each stator winding can be obtained through a digital ammeter. By monitoring and adjusting the voltage and current values of the stator winding, it is possible to ensure that the motor operates in the optimal working state, thereby improving the conversion efficiency and output power of the motor. Moreover, reasonable voltage and current settings can also reduce the losses and heat generation of the motor, extending the service life of the motor. The output power of a wind turbine refers to the power generated by the wind turbine capturing wind energy through the blades at different wind speeds, converting it into mechanical energy, and then driving the generator to generate electricity. It is an important indicator for measuring the power generation capacity and performance of the wind turbine and can be obtained through a power sensor. The grid frequency of a wind turbine refers to the alternating current frequency of the power system to which the wind turbine is connected and can be measured through a grid frequency measuring instrument. The stability of the grid frequency is crucial for the operating efficiency of the wind turbine. By ensuring that the electrical energy output by the wind turbine matches the grid frequency, the impact of grid fluctuations on the wind turbine can be reduced, and the operating stability of the unit can be improved.

[0043] Further, the equipment status abnormal evaluation index, with the specific numerical expression as:

[0044]

[0045] Among them, Mu represents the equipment status abnormal evaluation index, U i represents the voltage value of the i-th stator winding, U0 represents the reference standard voltage value, ΔU represents the allowable deviation voltage value, I i represents the current value of the i-th stator winding, I0 represents the reference standard current value, ΔI represents the allowable deviation current value, e represents the natural constant, P represents the output power, P0 represents the reference standard output power, ΔP represents the allowable deviation output power, f represents the grid frequency, f0 represents the reference standard grid frequency, Δf represents the allowable deviation grid frequency, ρ1 represents the equipment status abnormal evaluation influence factor corresponding to the set voltage value of the stator winding, ρ2 represents the equipment status abnormal evaluation influence factor corresponding to the set current value of the stator winding, ρ3 represents the equipment status abnormal evaluation influence factor corresponding to the set output power, ρ4 represents the equipment status abnormal evaluation influence factor corresponding to the set grid frequency, i represents the number of each stator winding, i = 1, 2, 3,..., m, and m represents the total number of stator windings.

[0046] The algorithm of this embodiment combines the voltage values of each stator winding, the current values of each stator winding, the output power, and the grid frequency, and comprehensively analyzes to obtain an abnormal equipment status evaluation index. When the voltage in the stator winding increases, if the motor load remains unchanged, the current usually increases correspondingly to maintain power balance; in a wind turbine generator, the magnitude of the stator winding current directly affects the output power. When the current increases, if the voltage remains unchanged and the power factor is high, the output power will also increase correspondingly; at the same time, when the output power increases, if the other power sources in the grid remain unchanged, the grid frequency may decrease slightly because more electrical energy is injected into the grid. Through comprehensive analysis, a more comprehensive abnormal equipment status evaluation index can be obtained.

[0047] It should be noted that in this embodiment, four key factors are considered, namely the voltage values of each stator winding, the current values of each stator winding, the output power, and the grid frequency, which can promptly detect abnormal conditions such as motor overheating and overload, thereby preventing the occurrence of motor failures. It can also help diagnose faults such as short circuits and open circuits inside the motor, providing a timely basis for maintenance and replacement. It can ensure that the unit will not cause excessive impact and interference to the grid during grid-connected operation, protect the safe and stable operation of the grid, help reduce the downtime caused by motor failures, and improve the availability and power generation efficiency of the wind turbine generator. By standardizing the voltage values of each stator winding, the current values of each stator winding, the output power, and the grid frequency, it is ensured that they are compared on the same magnitude level, improving the fairness and comparability of the evaluation. At the same time, the setting of U0, I0, P0, and f0 can avoid equipment damage or performance degradation caused by excessive voltage and current, ensure that the wind turbine generator operates within the rated power range, avoid overloading operation, and ensure the stable operation of the power system and power quality. By weighting the impacts of the voltage values of each stator winding, the current values of each stator winding, the output power, and the grid frequency, their relative importance in the evaluation index is reflected, and the weights of different factors can be adjusted according to different needs, making the formula have good adaptability. It is not difficult to see that the greater the deviation of the voltage value of each stator winding, the current value of each stator winding, the output power, or the grid frequency, the greater the abnormal equipment status evaluation index. By evaluating the abnormal equipment status evaluation index, it helps to take preventive measures before the occurrence of faults, avoid the expansion of faults or more serious consequences, understand the wear and aging degree of each component of the wind turbine generator, thereby formulating a reasonable maintenance plan, and can also reduce unnecessary maintenance and inspection times, thereby reducing maintenance costs. And the operation and maintenance personnel can carry out targeted repairs or replacements, avoiding over-maintenance or missed maintenance. At the same time, the abnormal evaluation index can reflect the overall operating status of the wind turbine generator, ensure that the unit operates within a safe range, help avoid safety accidents caused by equipment failures, and ensure the life safety of the operation and maintenance personnel and the stable operation of the wind farm.

[0048] In a specific embodiment, the value range of the equipment status abnormal evaluation influence factors corresponding to the stator winding voltage value, stator winding current value, output power, and grid frequency is between 0 and 1, which represents the numerical values of the influence degrees of the stator winding voltage value, stator winding current value, output power, and grid frequency on the equipment status abnormal evaluation index. Each equipment status abnormal evaluation influence factor can be obtained from the wind turbine database. By adjusting the value of the influence factor, the influence degrees of different factors on the final equipment status abnormal evaluation index can be flexibly adjusted.

[0049] It should be understood that in this embodiment, based on the relationship between the stator winding voltage value, stator winding current value, output power, and grid frequency in historical data and the equipment status abnormal evaluation index, a mapping set of the equipment status abnormal evaluation influence factors corresponding to the stator winding voltage value, stator winding current value, output power, and grid frequency is constructed. The real-time stator winding voltage value, stator winding current value, output power, and grid frequency are input, and the corresponding equipment status abnormal evaluation influence factors are obtained from the mapping set.

[0050] It should be explained that the equipment status abnormal evaluation index in this embodiment is a quantitative index obtained by analyzing each stator winding voltage value, each stator winding current value, output power, and grid frequency, and is used to quantify the degree of equipment status abnormality.

[0051] Specifically, the key operation data is processed to obtain the wind turbine stability evaluation index. The specific processing process is as follows: the key operation data includes the temperature of each temperature monitoring point, the vibration frequency of each vibration monitoring point, and the generator speed.

[0052] The reference standard temperature, allowable deviation temperature, reference standard vibration frequency, allowable deviation vibration frequency, reference standard speed, and allowable deviation speed are extracted from the wind turbine database, and the wind turbine stability evaluation index is obtained through comprehensive analysis. The pitch angle of the blade is adjusted according to the wind turbine stability evaluation index.

[0053] In a specific embodiment, temperature monitoring points are usually set at key parts such as the oil temperature of the gearbox, the temperature of the main shaft bearing, the temperature of the generator, the temperature of the brake, and the temperature of the nacelle. By monitoring the temperature changes at these parts, potential overheating problems can be detected and addressed in a timely manner. The temperature of each temperature monitoring point can be obtained through temperature sensors. Vibration monitoring points are usually set on key components such as the main shaft, bearings, and gearbox. By monitoring parameters such as the vibration frequency and vibration amplitude of these components, mechanical failures and imbalance problems can be detected and diagnosed in a timely manner. The vibration frequency of each vibration monitoring point can be obtained through vibration sensors. The generator speed refers to the rotational speed of the generator main shaft, that is, the maximum number of revolutions that can be completed within one minute. The generator speed is one of the important indicators for measuring the performance of a wind turbine generator set, and it is directly related to the power generation efficiency and stability of the wind turbine generator set. The generator speed can be obtained through a speed sensor.

[0054] Furthermore, the stability evaluation index of the wind turbine generator set has a specific numerical expression as follows:

[0055]

[0056] Where, Ws represents the stability evaluation index of the wind turbine generator set, T j represents the temperature of the jth temperature monitoring point, T j0 represents the reference standard temperature of the jth temperature monitoring point, ΔT represents the allowable deviation temperature, e represents the natural constant, F x represents the vibration frequency of the xth vibration monitoring point, F0 represents the reference standard vibration frequency, ΔF represents the allowable deviation vibration frequency, N represents the generator speed, N0 represents the reference standard speed, ΔN represents the allowable deviation speed, ω1 represents the influence factor of the stability evaluation of the wind turbine generator set corresponding to the set temperature, ω2 represents the influence factor of the stability evaluation of the wind turbine generator set corresponding to the set vibration frequency, ω3 represents the influence factor of the stability evaluation of the wind turbine generator set corresponding to the set generator speed, j represents the number of each temperature monitoring point, j = 1, 2, 3,..., n, n represents the total number of temperature monitoring points, x represents the number of each vibration monitoring point, x = 1, 2, 3,..., y, and y represents the total number of vibration monitoring points.

[0057] The algorithm of this embodiment combines the temperatures of each temperature monitoring point, the vibration frequencies of each vibration monitoring point, and the generator speed, and comprehensively analyzes to obtain the stability evaluation index of the wind turbine generator set. During the high-speed operation of the generator, a large amount of heat will be generated. If the heat dissipation is poor, it will cause the generator temperature to rise. Excessive temperature will affect the performance and lifespan of the generator, and even cause failures. Therefore, the increase in the generator speed may be accompanied by an increase in temperature, especially under high-load operating conditions; the change in temperature may affect the material properties and structural stability of each component in the wind turbine generator set, thereby affecting the vibration characteristics. For example, components such as the main shaft bearing and gearbox may cause an increase in vibration frequency due to material expansion or poor lubrication at high temperatures; at the same time, the increase in vibration frequency may also lead to increased friction and wear between components, and further generate more heat, forming a vicious cycle; the change in the generator speed will directly affect the vibration characteristics of the wind turbine generator set. At a specific speed, the wind turbine generator set may generate a resonance phenomenon, resulting in an increase in vibration frequency. On the other hand, the change in vibration frequency may also reflect the abnormality of the generator speed. For example, when the vibration frequency suddenly increases, it may be caused by the fluctuation or instability of the generator speed. Through comprehensive analysis, a more comprehensive, accurate, and in-depth stability evaluation index of the wind turbine generator set can be obtained.

[0058] Table 1 Example data of the stability evaluation index of the wind turbine generator set

[0059]

[0060]

[0061] As shown in Table 1, the stability evaluation index of the wind turbine is jointly determined by the temperatures of each temperature monitoring point, the vibration frequencies of each vibration monitoring point, and the generator speed. In a specific embodiment, n = y = 1, the reference standard temperature is 80 °C, the allowable deviation temperature is 10 °C, the reference standard vibration frequency is 12 Hz, the allowable deviation vibration frequency is 3 Hz, the reference standard speed is 500 r / min, and the allowable deviation speed is 30 r / min. The influence factor of the wind turbine stability evaluation corresponding to the set temperature is 0.3, the influence factor of the wind turbine stability evaluation corresponding to the set vibration frequency is 0.3, and the influence factor of the wind turbine stability evaluation corresponding to the set generator speed is 0.4. This formula takes into account three key factors, namely the temperatures of each temperature monitoring point, the vibration frequencies of each vibration monitoring point, and the generator speed, which can understand the overall performance and operating status of the wind turbine, help formulate more scientific operation and maintenance strategies, improve the reliability and efficiency of the equipment, and also discover the trend of equipment performance degradation and take measures for optimization, such as adjusting the control strategy, replacing worn parts, etc. It can also timely detect potential safety hazards, so as to take measures in time to avoid accidents. Further, it can timely detect and handle equipment failures, reduce the failure rate, improve the reliability and stability of the equipment, and reasonable operation and maintenance strategies can reduce the wear and fatigue of the equipment, extend the service life of the equipment, and reduce the replacement cost. By standardizing the temperatures of each temperature monitoring point, the vibration frequencies of each vibration monitoring point, and the generator speed, it ensures that they are compared on the same magnitude, improving the fairness and comparability of the evaluation. At the same time, the setting of T j0 , F0, and N0 can avoid equipment failures or performance degradation problems caused by overheating, excessive vibration, or abnormal speed. By weighting the influences of the temperatures of each temperature monitoring point, the vibration frequencies of each vibration monitoring point, and the generator speed, it reflects their relative importance in the evaluation index, and the weights of different factors can be adjusted according to different requirements, making the model have good adaptability. It is not difficult to see that the smaller the deviation of the temperature of each temperature monitoring point, the vibration frequency of each vibration monitoring point, or the generator speed, the larger the wind turbine stability evaluation index. By evaluating the wind turbine stability evaluation index, it helps to ensure that the wind turbine operates in the best state, thereby improving the power generation efficiency, increasing the power output, reducing the losses caused by fault shutdowns, timely detecting and handling potential fault hazards, thus avoiding greater damage to the unit caused by faults, and formulating more reasonable operation and maintenance strategies, such as adjusting the maintenance cycle, optimizing spare parts management, etc., thereby improving the operation and maintenance efficiency and reducing the operation and maintenance cost. Further, more effective risk management measures can be formulated to improve the overall safety of the wind farm.

[0062] In a specific embodiment, the value ranges of the influencing factors for the stability assessment of the wind turbine corresponding to temperature, vibration frequency, and generator speed are between 0 and 1, which represent the numerical values of the influence degrees of temperature, vibration frequency, and generator speed on the stability assessment index of the wind turbine. Each influencing factor for the stability assessment of the wind turbine can be obtained from the wind turbine database. By adjusting the values of the influencing factors, the influence degrees of different factors on the final stability assessment index of the wind turbine can be flexibly adjusted.

[0063] It should be understood that in this embodiment, based on the relationships between temperature, vibration frequency, and generator speed in historical data and the stability assessment index of the wind turbine, a mapping set of the influencing factors for the stability assessment of the wind turbine corresponding to temperature, vibration frequency, and generator speed is constructed. By inputting real-time temperature, vibration frequency, and generator speed, the corresponding influencing factors for the stability assessment of the wind turbine are obtained from the mapping set.

[0064] It should be explained that the stability assessment index of the wind turbine in this embodiment is a quantitative index obtained by analyzing the temperature at each temperature monitoring point, the vibration frequency at each vibration monitoring point, and the generator speed, and is used to quantify the stability degree of the wind turbine.

[0065] In a specific embodiment, the pitch angle of the blade is adjusted according to the stability assessment index of the wind turbine. The specific analysis process is as follows: The stability assessment threshold of the wind turbine is extracted from the wind turbine database, and the stability assessment index of the wind turbine is compared with the stability assessment threshold. If the stability assessment index of the wind turbine is greater than or equal to the stability assessment threshold, no additional operation is performed. If the stability assessment index of the wind turbine is less than the stability assessment threshold, the pitch angle of the blade is adjusted smaller until the stability assessment index of the wind turbine is greater than or equal to the stability assessment threshold.

[0066] Specifically, the environmental data is processed to obtain an environmental interference value. The specific processing process is as follows: The environmental data includes environmental temperature, environmental humidity, and wind speed.

[0067] The reference standard environmental temperature, allowable deviation environmental temperature, reference standard environmental humidity, allowable deviation environmental humidity, and critical wind speed are extracted from the wind turbine database, and the environmental interference value is obtained through comprehensive analysis.

[0068] In a specific embodiment, if the wind turbine components are in an environment with lower or higher temperatures for a long time, they may accelerate aging or damage. Therefore, the temperature needs to be set within a reasonable range. The ambient temperature can be obtained through a temperature sensor. Humidity is an important factor affecting the corrosion or aging of external and internal components of wind turbine equipment. The higher the humidity, the more likely metal components are to rust, and the insulation performance of electrical components may decrease, and even cause short circuit failures. It is worth noting that the lower the humidity is, the better it is when wind power generation equipment is running. For example, the lower the temperature or the higher the temperature, the more likely it is to generate static electricity and other problems, which may affect the normal and stable operation of the wind power generation equipment. The ambient humidity can be obtained through a humidity sensor, and the wind speed can be obtained through a wind speed sensor.

[0069] Furthermore, the specific numerical expression of the environmental interference value is:

[0070]

[0071] Among them, En represents the environmental interference value, t represents the ambient temperature, t0 represents the reference standard ambient temperature, Δt represents the allowable deviation ambient temperature, H represents the ambient humidity, H0 represents the reference standard ambient humidity, ΔH represents the allowable deviation ambient humidity, F represents the wind speed, F0 represents the critical wind speed, β1 represents the environmental interference value assessment influence factor corresponding to the set ambient temperature, β2 represents the environmental interference value assessment influence factor corresponding to the set ambient humidity, and β3 represents the environmental interference value assessment influence factor corresponding to the set wind speed.

[0072] The algorithm of this embodiment combines ambient temperature, ambient humidity and wind speed, and comprehensively analyzes to obtain the environmental interference value. Changes in wind speed will directly affect the distribution and changes of ambient temperature. When the wind speed is greater, the convection of the air will be enhanced, which will help to diffuse and evenly distribute heat, thereby possibly reducing the temperature of the local area; although the ambient temperature itself does not directly determine the size of the wind speed, changes in ambient temperature may affect the stability and stratification structure of the atmosphere, and thus affect the changes in wind speed and direction. For example, when the temperature is higher in summer, the atmospheric stratification may become unstable, which may easily cause convective weather, thereby affecting wind speed and direction; in an environment with higher humidity, the water vapor content in the air is higher, which may increase the air resistance, thereby slowing down the wind speed. Comprehensive analysis can obtain a more comprehensive, accurate and in-depth environmental interference value.

[0073] It should be noted that in this embodiment, three key factors, namely environmental temperature, environmental humidity, and wind speed, are considered, which can predict the possible operating pressure and potential faults faced by the wind turbine. For example, the higher the temperature and humidity, the more likely it is to cause overheating or accelerated corrosion of the equipment, and the sudden change in wind speed may impact mechanical components. Based on these data, a more precise preventive maintenance plan can be formulated to reduce the occurrence of sudden faults, which helps to optimize the scheduling of maintenance personnel and resource allocation. For example, under extreme weather conditions, additional maintenance personnel and equipment can be arranged in advance to ensure the stable operation of the wind turbine. The operating strategy of the wind turbine can be dynamically adjusted to maximize its power output, and potential faults caused by environmental factors can be detected and processed in a timely manner, which can significantly reduce the downtime of the wind turbine and contribute to improving the power generation efficiency and economic benefits of the entire wind farm. By standardizing the environmental temperature, environmental humidity, and wind speed, ensuring that they are compared on the same scale, the fairness and comparability of the evaluation are improved. At the same time, the setting of t0, H0, and F0 helps to slow down the aging or damage of the components of the wind turbine and prevent damage to the wind turbine caused by unreasonable temperature and humidity or excessive wind speed. By weighting the impacts of environmental temperature, environmental humidity, and wind speed, their relative importance in the evaluation index is reflected, and the weights of different factors can be adjusted according to different requirements, making the formula highly adaptable. It is not difficult to see that the greater the deviation of environmental temperature or environmental humidity or wind speed, the greater the environmental interference value. By evaluating the environmental interference value, it can help the wind turbine to more precisely adjust the blade angle and yaw angle to capture more wind energy, thereby improving the power generation efficiency. It can also optimize the cooling system and lubrication system of the wind turbine to ensure that the unit can still operate stably in an environment with higher temperature or humidity, reducing the failure rate caused by overheating or poor lubrication. Furthermore, it can predict and identify extreme weather conditions that may affect the wind turbine and take preventive measures to avoid the occurrence of faults and reduce the risk of damage to the wind turbine caused by extreme weather.

[0074] In a specific embodiment, the value range of the environmental interference value evaluation impact factors corresponding to environmental temperature, environmental humidity, and wind speed is between 0 and 1, which represents the numerical value of the influence degree of environmental temperature, environmental humidity, and wind speed on the environmental interference value. Each environmental interference value evaluation impact factor can be obtained from the wind turbine database. By adjusting the value of the impact factor, the influence degree of different factors on the final environmental interference value can be flexibly adjusted.

[0075] It should be understood that in this embodiment, based on the relationship between environmental temperature, environmental humidity, and wind speed in historical data and the environmental interference value, a mapping set of environmental interference value evaluation impact factors corresponding to environmental temperature, environmental humidity, and wind speed is constructed. By inputting real-time environmental temperature, environmental humidity, and wind speed, the corresponding environmental interference value evaluation impact factors can be obtained from the mapping set.

[0076] Specifically, a fault evaluation value of the wind turbine is obtained through comprehensive analysis. The specific analysis process is as follows: Based on the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value, a fault evaluation value of the wind turbine is obtained through comprehensive analysis. The fault evaluation value of the wind turbine is used to quantify the degree of the wind turbine fault.

[0077] Furthermore, the fault evaluation value of the wind turbine has the following specific numerical expression:

[0078]

[0079] Wherein, Wb represents the fault evaluation value of the wind turbine, Mu represents the equipment status anomaly evaluation index, Ws represents the wind turbine stability evaluation index, En represents the environmental interference value, θ1 represents the wind turbine fault evaluation influence factor corresponding to the set equipment status anomaly evaluation index, θ2 represents the wind turbine fault evaluation influence factor corresponding to the set wind turbine stability evaluation index, and θ3 represents the wind turbine fault evaluation influence factor corresponding to the set environmental interference value.

[0080] As Figure 3 shown, in a specific embodiment, θ1 = 0.3, θ2 = 0.4, θ3 = 0.2, and En = 0.5. When Ws = 0.1, the functional relationship between the fault evaluation value of the wind turbine and the equipment status anomaly evaluation index is as shown by curve a; when Ws = 0.5, the functional relationship between the fault evaluation value of the wind turbine and the equipment status anomaly evaluation index is as shown by curve b; when Ws = 1, the functional relationship between the fault evaluation value of the wind turbine and the equipment status anomaly evaluation index is as shown by curve c.

[0081] The algorithm of this embodiment combines the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value to comprehensively analyze and obtain the fault evaluation value of the wind turbine. When the equipment status anomaly evaluation index increases, it often means that there are certain faults or performance degradation in the equipment, which may lead to a decrease in the stability of the wind turbine. On the contrary, if the equipment status anomaly evaluation index remains at a low level, the stability of the wind turbine is usually high; an increase in the environmental interference value may lead to a decrease in the wind turbine stability evaluation index; and changes in the environmental interference value may cause fluctuations in the equipment status anomaly evaluation index. For example, changes in wind speed may cause wear and fatigue of the wind turbine blades, thereby increasing the equipment failure rate. Through comprehensive analysis, a more comprehensive, accurate, and in-depth fault evaluation value of the wind turbine can be obtained.

[0082] It should be noted that in this embodiment, three key factors are considered, namely, the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value. A more scientific and reasonable maintenance plan can be formulated to avoid over-maintenance or under-maintenance, further determine the severity of the problem and its impact on the overall operation of the wind farm, improve the stability of power output, thereby increasing the power generation of the wind farm, and helping the operation and maintenance personnel to formulate corresponding emergency response plans according to the risk type and severity. By weighting the impacts of the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value, their relative importance in the evaluation index is reflected, and the weights of different factors can be adjusted according to different requirements, making the formula highly adaptable. It is not difficult to see that the larger the equipment status anomaly evaluation index, the smaller the wind turbine stability evaluation index, or the larger the environmental interference value, the larger the wind turbine fault evaluation value. By evaluating the wind turbine fault evaluation value, it can help the operation and maintenance personnel quickly and accurately locate the fault location of the wind turbine, contribute to formulating a more scientific and reasonable maintenance plan, thereby improving the maintenance efficiency. Moreover, the fault evaluation value can reflect the potential risks of the wind turbine, and the operation and maintenance personnel can take preventive measures in advance according to the evaluation results to avoid the occurrence of safety accidents, quickly judge the fault type and severity, and formulate corresponding emergency response plans to improve the speed and accuracy of emergency response.

[0083] In a specific embodiment, the value ranges of the wind turbine fault evaluation impact factors corresponding to the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value are between 0 and 1, representing the numerical values of the influence degrees of the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value on the wind turbine fault evaluation value. Each wind turbine fault evaluation impact factor can be obtained from the wind turbine database. By adjusting the values of the impact factors, the influence degrees of different factors on the final wind turbine fault evaluation value can be flexibly adjusted.

[0084] It should be understood that in this embodiment, based on the relationships between the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value in the historical data and the wind turbine fault evaluation value, a mapping set of the wind turbine fault evaluation impact factors corresponding to the equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value is constructed. By inputting the real-time equipment status anomaly evaluation index, the wind turbine stability evaluation index, and the environmental interference value, the corresponding wind turbine fault evaluation impact factors can be obtained from the mapping set.

[0085] Specifically, the IPC hardware platform generates an evaluation report of the wind turbine generator set based on the fault evaluation value of the wind turbine generator set and gives feedback. The specific evaluation process is as follows: Extract the first threshold value of the wind turbine generator set fault evaluation and the second threshold value of the wind turbine generator set fault evaluation from the wind turbine generator set database. Compare the wind turbine generator set fault evaluation value with the first threshold value of the wind turbine generator set fault evaluation. If the wind turbine generator set fault evaluation value is greater than or equal to the first threshold value of the wind turbine generator set fault evaluation, adjust the maintenance strategy of the wind turbine generator set. At the same time, judge whether the wind turbine generator set fault evaluation value is greater than the second threshold value of the wind turbine generator set fault evaluation. If the wind turbine generator set fault evaluation value is less than the first threshold value of the wind turbine generator set fault evaluation, no additional operation is performed.

[0086] Generate an evaluation report according to the comparison results of the wind turbine generator set fault evaluation value with the first threshold value and the second threshold value of the wind turbine generator set fault evaluation.

[0087] It should be explained that in this embodiment, when adjusting the maintenance strategy of the wind turbine generator set, the specific adjustment process is as follows: The maintenance strategy of the wind turbine generator set refers to the maintenance frequency of the wind turbine generator set.

[0088] Obtain the initial maintenance frequency of the wind turbine generator set from the wind turbine generator set equipment manual. Input the wind turbine generator set fault evaluation value into the wind turbine generator set database to match and obtain the maintenance frequency compensation value corresponding to each wind turbine generator set fault evaluation value interval. Add the initial maintenance frequency and the maintenance frequency compensation value to obtain the updated maintenance frequency, and perform maintenance on the wind turbine generator set according to the updated maintenance frequency.

[0089] Furthermore, when judging whether the wind turbine generator set fault evaluation value is greater than the second threshold value of the wind turbine generator set fault evaluation, the specific judgment process is as follows: Compare the wind turbine generator set fault evaluation value with the second threshold value of the wind turbine generator set fault evaluation. If the wind turbine generator set fault evaluation value is greater than or equal to the second threshold value of the wind turbine generator set fault evaluation, perform maintenance immediately. If the wind turbine generator set fault evaluation value is less than the second threshold value of the wind turbine generator set fault evaluation, no additional operation is performed, where the second threshold value of the wind turbine generator set fault evaluation is greater than the first threshold value of the wind turbine generator set fault evaluation.

[0090] Refer to Figure 2 As shown, the second aspect of the present invention provides a wind turbine generator set transient data processing system based on the IPC hardware platform, including: a data acquisition module for acquiring the equipment status data, key operation data, and environmental data of the wind turbine generator set.

[0091] A wind turbine generator set fault analysis module for processing the equipment status data to obtain an equipment status anomaly evaluation index, processing the key operation data to obtain a wind turbine generator set stability evaluation index, processing the environmental data to obtain an environmental interference value, and comprehensively analyzing to obtain a wind turbine generator set fault evaluation value.

[0092] A wind turbine generator set evaluation module, and the IPC hardware platform generates an evaluation report of the wind turbine generator set based on the wind turbine generator set fault evaluation value and gives feedback.

[0093] A wind turbine database for storing wind turbine-related data, including: reference standard voltage value, allowable deviation voltage value, reference standard current value, allowable deviation current value, reference standard output power, allowable deviation output power, reference standard grid frequency, allowable deviation grid frequency, equipment status anomaly evaluation influence factor corresponding to the set stator winding voltage value, equipment status anomaly evaluation influence factor corresponding to the set stator winding current value, equipment status anomaly evaluation influence factor corresponding to the set output power, equipment status anomaly evaluation influence factor corresponding to the set grid frequency, reference standard temperature, allowable deviation temperature, reference standard vibration frequency, allowable deviation vibration frequency, reference standard rotational speed, allowable deviation rotational speed, wind turbine stability evaluation influence factor corresponding to the set temperature, wind turbine stability evaluation influence factor corresponding to the set vibration frequency, wind turbine stability evaluation influence factor corresponding to the set generator rotational speed, reference standard ambient temperature, allowable deviation ambient temperature, reference standard ambient humidity, allowable deviation ambient humidity, critical wind speed, ambient interference value evaluation influence factor corresponding to the set ambient temperature, ambient interference value evaluation influence factor corresponding to the set ambient humidity, ambient interference value evaluation influence factor corresponding to the set wind speed, wind turbine fault evaluation influence factor corresponding to the set equipment status anomaly evaluation index, wind turbine fault evaluation influence factor corresponding to the set wind turbine stability evaluation index, wind turbine fault evaluation influence factor corresponding to the set ambient interference value, wind turbine stability evaluation threshold, maintenance frequency compensation value corresponding to each wind turbine fault evaluation value interval, wind turbine fault evaluation first threshold, and wind turbine fault evaluation second threshold.

[0094] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they shall fall within the protection scope of the present invention.

Claims

1. A transient data processing method for a wind turbine based on an IPC hardware platform, characterized in that Including: Collecting the equipment status data, key operation data and environmental data of the wind turbine generator set; Processing the equipment status data to obtain an equipment status anomaly evaluation index, processing the key operation data to obtain a wind turbine generator set stability evaluation index, processing the environmental data to obtain an environmental interference value, and comprehensively analyzing to obtain a wind turbine generator set fault evaluation value; The IPC hardware platform generates an evaluation report of the wind turbine generator set according to the wind turbine generator set fault evaluation value and gives feedback.

2. The transient data processing method for a wind turbine unit based on an IPC hardware platform according to claim 1, characterized in that: The process of processing the equipment status data to obtain an equipment status anomaly evaluation index is specifically as follows: The equipment status data includes the voltage values of each stator winding, the current values of each stator winding, the output power and the grid frequency; Extracting the reference standard voltage value, allowable deviation voltage value, reference standard current value, allowable deviation current value, reference standard output power, allowable deviation output power, reference standard grid frequency and allowable deviation grid frequency from the wind turbine generator set database, and comprehensively analyzing to obtain an equipment status anomaly evaluation index.

3. The transient data processing method for a wind turbine based on an IPC hardware platform according to claim 1, characterized in that: The process of processing the key operation data to obtain a wind turbine generator set stability evaluation index is specifically as follows: The key operation data includes the temperature of each temperature monitoring point, the vibration frequency of each vibration monitoring point and the generator speed; Extracting the reference standard temperature, allowable deviation temperature, reference standard vibration frequency, allowable deviation vibration frequency, reference standard speed and allowable deviation speed from the wind turbine generator set database, comprehensively analyzing to obtain a wind turbine generator set stability evaluation index, and adjusting the pitch angle of the blade according to the wind turbine generator set stability evaluation index.

4. The transient data processing method for a wind turbine based on an IPC hardware platform according to claim 1, wherein: The process of processing the environmental data to obtain an environmental interference value is specifically as follows: The environmental data includes the environmental temperature, environmental humidity and wind speed; Extracting the reference standard environmental temperature, allowable deviation environmental temperature, reference standard environmental humidity, allowable deviation environmental humidity and critical wind speed from the wind turbine generator set database, and comprehensively analyzing to obtain an environmental interference value.

5. The transient data processing method of a wind turbine based on an IPC hardware platform according to claim 4, characterized in that: The process of comprehensively analyzing to obtain a wind turbine generator set fault evaluation value is specifically as follows: According to the equipment status anomaly evaluation index, the wind turbine generator set stability evaluation index and the environmental interference value, comprehensively analyzing to obtain a wind turbine generator set fault evaluation value, and the wind turbine generator set fault evaluation value is used to quantify the fault degree of the wind turbine generator set.

6. The transient data processing method for a wind turbine based on an IPC hardware platform according to claim 3, characterized in that: The process of adjusting the pitch angle of the blade according to the wind turbine generator set stability evaluation index is specifically as follows: Extracting the wind turbine generator set stability evaluation threshold from the wind turbine generator set database, comparing the wind turbine generator set stability evaluation index with the wind turbine generator set stability evaluation threshold. If the wind turbine generator set stability evaluation index is greater than or equal to the wind turbine generator set stability evaluation threshold, no additional operation is performed. If the wind turbine generator set stability evaluation index is less than the wind turbine generator set stability evaluation threshold, the pitch angle of the blade is adjusted smaller until the wind turbine generator set stability evaluation index is greater than or equal to the wind turbine generator set stability evaluation threshold.

7. The transient data processing method for a wind turbine based on an IPC hardware platform according to claim 5, characterized in that: The process of the IPC hardware platform generating an evaluation report of the wind turbine generator set according to the wind turbine generator set fault evaluation value and giving feedback is specifically as follows: Extract the first threshold for wind turbine fault assessment and the second threshold for wind turbine fault assessment from the wind turbine database. Compare the wind turbine fault assessment value with the first threshold for wind turbine fault assessment. If the wind turbine fault assessment value is greater than or equal to the first threshold for wind turbine fault assessment, adjust the wind turbine maintenance strategy. At the same time, determine whether the wind turbine fault assessment value is greater than the second threshold for wind turbine fault assessment. If the wind turbine fault assessment value is less than the first threshold for wind turbine fault assessment, no additional operation is performed; Generate an assessment report according to the comparison results of the wind turbine fault assessment value with the first and second thresholds for wind turbine fault assessment.

8. The transient data processing method for a wind turbine based on an IPC hardware platform according to claim 7, characterized in that: The adjustment of the wind turbine maintenance strategy, the specific adjustment process is as follows: The wind turbine maintenance strategy refers to the maintenance frequency of the wind turbine; Obtain the initial maintenance frequency of the wind turbine. Input the wind turbine fault assessment value into the wind turbine database to match the maintenance frequency compensation value corresponding to each wind turbine fault assessment value interval. Add the initial maintenance frequency and the maintenance frequency compensation value to obtain the updated maintenance frequency, and perform maintenance on the wind turbine according to the updated maintenance frequency.

9. The transient data processing method for a wind turbine based on an IPC hardware platform according to claim 5, characterized in that: The wind turbine fault assessment value, the specific numerical expression is: Where, Wb represents the wind turbine fault assessment value, Mu represents the equipment status abnormality assessment index, Ws represents the wind turbine stability assessment index, En represents the environmental interference value, θ1 represents the wind turbine fault assessment influence factor corresponding to the set equipment status abnormality assessment index, θ2 represents the wind turbine fault assessment influence factor corresponding to the set wind turbine stability assessment index, and θ3 represents the wind turbine fault assessment influence factor corresponding to the set environmental interference value.

10. A system for applying the transient data processing method of a wind turbine based on an IPC hardware platform according to any one of claims 1-9, characterized in that: Including: A data acquisition module for collecting the equipment status data, key operation data and environmental data of the wind turbine; A wind turbine fault analysis module for processing the equipment status data to obtain the equipment status abnormality assessment index, processing the key operation data to obtain the wind turbine stability assessment index, processing the environmental data to obtain the environmental interference value, and comprehensively analyzing to obtain the wind turbine fault assessment value; A wind turbine assessment module, and the IPC hardware platform generates an assessment report of the wind turbine according to the wind turbine fault assessment value and gives feedback.

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