A wind power generation equipment operating status monitoring system

Abstract

The present invention belongs to the technical field of equipment operation monitoring, and specifically discloses a wind power equipment operation status monitoring system, which includes: a monitoring log import module, a data fusion analysis module, an equipment status monitoring module, an equipment operation analysis module, a monitoring control analysis module, a database, and an operation result feedback terminal. The present invention effectively solves the current problem of insufficient consideration of the time and space level by setting the reference deviation threshold of each monitoring component corresponding to each state parameter according to the tracking monitoring log, ensures the accuracy and pertinence of the reference deviation threshold setting, and significantly reduces the risk misjudgment rate. At the same time, by combining the operating status of each monitoring component, the control requirements of the tracking setting are judged and the control monitoring components and the control tracking frequency are confirmed, so as to facilitate the early identification of components that need maintenance, thereby achieving preventive maintenance, ensuring that the equipment operates in a good state, and improving the power generation efficiency.

Description

Technical Field

[0001] The present invention belongs to the technical field of equipment operation monitoring, and in particular, relates to a wind power generation equipment operation status monitoring system. Background Art

[0002] Wind power equipment operating status monitoring is one of the key technologies to ensure efficient and stable operation of wind power generation systems. This process involves real-time data collection, analysis and processing of wind turbines and their related components, aiming to detect potential failures early, optimize maintenance plans, and improve overall system reliability and economic benefits.

[0003] Prior art, such as a wind turbine operating status monitoring system disclosed in a Chinese invention patent application with application number 202410790851.4, includes: a collection end, the collection end includes an environmental information collection module and a wind turbine working information collection module. The environmental information collection module is used to collect environmental status information data of the area where the wind turbine is working, and the wind turbine working information collection module is used to collect the working parameter data of the wind turbine itself. Analysis module, the analysis module includes an environmental analysis unit, a threshold analysis unit and a troubleshooting analysis unit. The environmental analysis unit is used to perform preliminary analysis on the environmental status information data. In the present invention, the threshold value changes according to the specific working environment of the wind turbine, and the changing threshold standard replaces the unified fault judgment standard under different environments, which can more accurately judge the fault of the wind turbine and reduce the risk of misjudgment.

[0004] Prior art, such as the Chinese invention patent application with application number 201510064827.3, discloses an FPGA-based embedded wind turbine operating status monitoring and fault diagnosis system, which includes a sensor group, a data collector, a data concentrator, a network storage server, a master station server and a master station client, provides a multi-parallel data acquisition system, and uploads it to a remote server in real time. Through the FPGA+ARM embedded processing system, it realizes the complete parallel acquisition of various sensor signals in hardware, overcomes the disadvantage of only being able to collect various signals in time-sharing, realizes online status monitoring and fault diagnosis analysis, concentrates and summarizes the data, compares it with the preset threshold, and determines the fault status. It can effectively realize real-time monitoring and multi-dimensional monitoring of wind turbines, realize online monitoring of large wind turbines, and has low equipment cost and high efficiency.

[0005] Regarding the above two technical solutions, it is obvious that the current wind power equipment operation status monitoring belongs to static monitoring and analysis, and there are still deficiencies in the following aspects: 1. Insufficient consideration of time and space. Although the threshold is adjusted according to the specific working environment, it does not take into account the changing characteristics of wind power equipment in time and space, nor does it consider the specific operation stage of the wind power equipment. As a result, the accuracy and pertinence of the threshold setting still have certain deviations, which leads to certain deficiencies in improving the abnormal identification effect of wind turbines.

[0006] 2. The analysis indicators are relatively simple. Most monitoring systems still focus on monitoring a single or a few key indicators, making it difficult to comprehensively evaluate the overall health status of the equipment. Summary of the invention

[0007] In view of this, in order to solve the problems raised in the above background technology, a wind power generation equipment operation status monitoring system is now proposed.

[0008] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a wind power generation equipment operation status monitoring system, the system includes: a monitoring log import module, used to record the currently monitored wind power generation equipment as a target device, and import the tracking monitoring log and accumulated operating time of the target device.

[0009] The data fusion analysis module is used to analyze the tracking and monitoring logs of the target device and output the change characteristics of each monitoring component.

[0010] The device status monitoring module is used to monitor the corresponding monitoring components of the target device through the monitoring terminal carried by the target device, obtain the current monitoring data, and import the currently set tracking frequency corresponding to the corresponding monitoring components of the target device.

[0011] The equipment operation analysis module is used to set the reference deviation threshold of each monitoring component corresponding to each state parameter and analyze the operation status of each monitoring component.

[0012] The monitoring and control analysis module is used to determine whether the tracking settings of the target device need to be regulated. If it is determined to be necessary, it confirms the regulation and monitoring components and the regulation and tracking frequency of the regulation and monitoring components.

[0013] The database is used to store the reference operation compliance change rate of each monitoring component corresponding to each operation stage, store the equipment parameters of the target equipment, and store the reference value and allowable deviation threshold of each state parameter of each monitoring component.

[0014] The operation result feedback terminal is used to feed back the operation status of each monitoring component to the operation and maintenance management personnel of the target device, and at the same time feed back the control tracking frequency of the control monitoring component to the monitoring and control terminal of the target device for tracking and control.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention combines the tracking monitoring log and the accumulated operating time of the target device to perform change characteristic analysis, and then sets the reference deviation threshold of each monitoring component corresponding to each state parameter, thereby effectively solving the current problem of insufficient consideration of the temporal and spatial aspects, and making up for the current lack of consideration of the temporal and spatial change characteristics of the wind power generation equipment, and the specific operating stage of the wind power generation equipment, thereby ensuring the accuracy and pertinence of the reference deviation threshold setting, while also ensuring the improvement of the abnormal identification effect of the wind turbine, and significantly reducing the risk misjudgment rate.

[0016] (2) The present invention sets a reference deviation threshold and analyzes the operating status of each monitoring component, thereby ensuring the rationality and effectiveness of the analysis results of the operating status of the monitoring components, while also ensuring the accuracy of the operating status determination. It also displays the operating status of multiple monitoring components, avoiding the shortcomings of the current relatively single analysis indicators, taking into account the impact of multiple components on the wind turbine, and realizing in-depth analysis of multiple components, which is convenient for a comprehensive assessment of the overall health status of the equipment.

[0017] (3) When performing change characteristic analysis, the present invention can more accurately reflect the actual operating status of each component by setting an operation change evaluation compensation factor, thereby achieving targeted and adaptive adjustment of the change characteristics, thereby making the evaluation results more accurate, thereby ensuring the effectiveness and representativeness of the change characteristic analysis.

[0018] (4) The present invention determines the control requirements of the tracking settings and confirms the control monitoring components and the control tracking frequency by combining the operating status of each monitoring component, so as to facilitate the early identification of components that need maintenance, thereby achieving preventive maintenance and ensuring that the equipment operates in a good condition, thereby improving power generation efficiency. On another level, it can also avoid unnecessary energy consumption and improve energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0020] Figure 1 It is a schematic diagram of the connection of the system modules of the present invention.

[0021] Figure 2 It is a schematic diagram of the overall monitoring process of the operating status of the wind power generation equipment of the present invention.

[0022] Figure 3It is a schematic diagram of the monitoring, regulation and analysis module flow of the present invention.

[0023] Figure 4 It is a schematic diagram of the composition of the monitoring terminal of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1 and Figure 2 As shown, the present invention provides a wind power generation equipment operation status monitoring system, which includes: a monitoring log import module, a data fusion analysis module, an equipment status monitoring module, an equipment operation analysis module, a monitoring and control analysis module, a database and an operation result feedback terminal.

[0026] In the above, the data fusion analysis module is connected to the monitoring log import module, the database and the equipment operation analysis module respectively. The equipment operation analysis module is also connected to the equipment status monitoring module, the monitoring and control analysis module and the database respectively. The monitoring and control analysis module is connected to the database and the operation result feedback terminal respectively.

[0027] The monitoring log importing module is used to record the currently monitored wind power generation equipment as the target equipment, and import the tracking monitoring log and the accumulated running time of the target equipment.

[0028] Specifically, the tracking monitoring log records the monitoring values ​​of each monitoring component corresponding to each state parameter at each tracking, the total power generation recorded at each tracking, and the meteorological parameters corresponding to each power generation day and other data.

[0029] The data fusion analysis module is used to analyze the tracking and monitoring logs of the target device and output the change characteristics of each monitoring component.

[0030] In a specific embodiment, the monitoring components of the target equipment include blades, a main shaft, a generator and a frequency converter, etc. By way of example, the state parameters of the blades include vibration frequency, temperature value, deformation amount and dust concentration, etc., the state parameters of the main shaft include vibration frequency, temperature value, radial displacement value and axial displacement value, the state parameters of the generator include temperature value, output current value, output voltage value, rotation speed and vibration frequency, etc., and the state parameters of the frequency converter include input voltage, output voltage, input current, output current and temperature value, etc.

[0031] Specifically, parsing the tracking and monitoring log of the target device includes: S1, extracting the monitoring value of each monitoring component corresponding to each state parameter at each tracking from the tracking and monitoring log, and comparing it with the reference value interval of each state parameter set for each monitoring component.

[0032] S2. If the monitoring value of a state parameter corresponding to a certain monitoring component during a certain tracking is within the reference value interval of the state parameter corresponding to the monitoring component, the state parameter is recorded as a matching parameter, and the number of matching parameters of each monitoring component during each tracking is counted.

[0033] S3. Compare the number of matching parameters of each monitoring component at each tracking with the number of state parameters of each monitoring component, and use the ratio as the operation standard, and determine the operation standard change rate of each monitoring component, which is recorded as , Indicates the monitoring part number, .

[0034] S4. Match and compare the accumulated running time of the target device with the running time window corresponding to each set running stage to obtain the matching running stage of the target device, and then extract the reference running standard change rate of each monitoring component corresponding to the matching running stage of the target device from the database, which is recorded as .

[0035] S5. Set the compensation factor for each monitoring component to evaluate the operation change , the compliance degree of each monitoring component’s operation compliance is counted and recorded as , , is the set reference operation change rate difference, and the operation standard change compliance is used as the change feature.

[0036] It should be added that, in a specific embodiment, The specific value can be 0.1.

[0037] The embodiment of the present invention combines the tracking monitoring log and the accumulated operating time of the target device to perform change characteristic analysis, and then sets the reference deviation threshold value of each monitoring component corresponding to each state parameter, thereby effectively solving the current problem of insufficient consideration of the temporal and spatial aspects, and making up for the current lack of combining the temporal and spatial change characteristics of the wind power generation equipment, and not considering the specific operating stage of the wind power generation equipment, thereby ensuring the accuracy and pertinence of the reference deviation threshold setting, while also ensuring the improvement of the abnormal identification effect of the wind turbine, and significantly reducing the risk misjudgment rate.

[0038] Furthermore, regarding step S1, it should be added that the specific setting example of the reference value interval of the status parameter is: [reference value of the status parameter, reference value of the status parameter + corresponding allowable deviation threshold]. When conducting monitoring component inspection, because what is considered is the operating safety and operating status of the equipment, it is sufficient not to exceed the preset upper limit value. When setting the reference value interval, the reference value of the status parameter of the monitoring component is used as the lower limit, and the sum of the reference value and the corresponding allowable deviation threshold is used as the upper limit. Among them, the sources of the reference value of the status parameter and the corresponding allowable deviation threshold can be extracted from the database.

[0039] Furthermore, regarding step S3, confirming the change rate of the operation compliance of each monitoring component includes: S31, extracting the tracking date of each tracking from the tracking monitoring log, grouping two adjacent tracking times into tracking groups, and recording the interval days between each tracking in each tracking group, which are recorded as intermittent tracking days.

[0040] S32. Calculate the difference in the degree of operation compliance of each monitoring component in each tracking group to obtain the corresponding operation compliance change value of each tracking group, and set a time compensation factor based on the number of intermittent tracking days of each tracking group, and then correct the operation compliance change value, and record the correction result as the confirmed operation compliance change value.

[0041] It should be added that, calculating the difference in the operational compliance of each monitoring component in each tracking group refers to subtracting the operational compliance of the previous tracking from the operational compliance of the next tracking in the same tracking group.

[0042] It should be added that the correction method for correcting the change value of the operation state compliance by the time compensation factor includes two scenarios. When the change value of the operation state compliance is positive, it means that the wind power generation equipment is in a good state. This is not a scenario we need to consider. Therefore, in this scenario, the corrected change value of the operation state compliance = the change value of the operation state compliance. When the change value of the operation state compliance is negative, this scenario indicates that the state of the wind power generation equipment is getting worse. Because the time period is long, the difference will be widened, so the difference is supplemented to achieve compensation, that is, the corrected change value of the operation state compliance = the error compensation value of the operation state compliance × time compensation factor + the change value of the operation state compliance.

[0043] In a specific embodiment, the running state calibration error compensation value is a positive value and a fixed setting value. Exemplarily, the running state calibration error compensation value may be 0.2.

[0044] S33, using the tracking group sequence as the horizontal coordinate and the confirmed operation standard change value as the vertical coordinate, constructing the operation standard change curve of each monitoring component, and extracting the slope from the operation standard change curve as the operation standard change rate.

[0045] It can be understood that the setting of the time compensation factor in step S32 includes: calculating the mean of the intermittent tracking days of each tracking group to obtain the average intermittent tracking days.

[0046] The difference between the number of intermittent tracking days of each tracking group and the average number of intermittent tracking days was calculated to obtain the difference in the number of intermittent tracking days.

[0047] If the intermittent tracking day difference corresponding to a tracking group is less than the lower limit of the set reference tracking day difference interval, or is within the set reference tracking day difference interval, 0 is used as the time compensation factor of the tracking group.

[0048] If the intermittent tracking days difference corresponding to a tracking group exceeds the upper limit of the reference tracking days difference interval, the intermittent tracking days difference corresponding to the tracking group and the upper limit of the reference tracking days difference interval are recorded as as well as .

[0049] Will As the time compensation factor of the tracking group, it is recorded as , and the time compensation factor of each tracking group is set to 0 or one of the.

[0050] It should be added that the time compensation factor is used to adjust the deviation of the target change value caused by the different days of intermittent tracking to ensure the comparability of the target change values ​​of different tracking groups. Therefore, by setting the time compensation factor, the changes in the operating status of the equipment in different time periods can be analyzed more accurately, potential problems and trends can be identified, and a scientific basis can be provided for the maintenance and optimization of the equipment.

[0051] It should also be added that long intervals may introduce external factors, such as maintenance, environmental changes, etc. These factors will affect the operating status of the equipment and cause distortion of the standard change value. Through compensation, the data of different intermittent tracking day groups can be made consistent, which is convenient for comparison and analysis across time periods. That is, long intermittent intervals may cause large changes in the equipment status. Obviously, the larger the intermittent interval number of days, the greater the compensation required. Therefore, the present invention does not perform compensation when the intermittent interval number of days is within the set reference tracking day difference interval or is lower than the set reference tracking day difference interval lower limit value, and assigns a value of 0. When the intermittent interval number of days exceeds the set reference tracking day difference interval upper limit value, compensation is set.

[0052] Furthermore, in step S5, the compensation factor for the operation change evaluation of each monitoring component is set, including: S51, counting the number of peak points from the operation standard change curve of each monitoring component, recorded as At the same time, the number of tracking groups between each peak point and its adjacent valley point is counted, as well as the difference in change value that confirms that the operation meets the standard.

[0053] It should be added that the identification of peak values ​​and valley values ​​can use signal processing methods to detect peak values ​​and valley values.

[0054] S52, selecting the minimum value from the tracking group numbers between each peak point and its adjacent valley point as the reference interval tracking group number, recorded as , and the average interval tracking group number is obtained by mean calculation, recorded as ,Will and The mean value of .

[0055] S53, select the maximum value from the difference in the confirmed operation compliance change value between each peak point and its adjacent valley point, and record it as The average confirmed running standard change value difference is obtained by average calculation ,Will and The mean value of .

[0056] S54. Set the compensation factor for each monitoring component to evaluate the operation change , , , and They represent the weights corresponding to the number of peak points, the number of interval tracking groups, and the difference in the running standard change value. , Indicates The number of tracking groups for each tracking component, and They are respectively the set reference peak-to-valley interval tracking group number and the reference operation standard change value difference.

[0057] In a specific embodiment, the reference peak-to-valley interval tracking group number is directly associated with the set tracking group number. For example, the reference peak-to-valley interval tracking group number can be set to , To round up the symbol, assume that the number of tracking groups is set to 10, and the number of tracking groups for the reference peak-to-valley interval is That is, the number of peak-to-valley interval tracking groups can be set to 4, and the difference in the reference running standard change value can be mainly taken as 0.2.

[0058] It should be added that the operation standard change rate is the slope of the operation standard change curve, and the slope of the standard change curve defaults to the slope of the regression line corresponding to the operation standard change curve or defaults to the average of the tangent slopes corresponding to each point in the standard change curve. Both the slope of the regression line corresponding to the operation standard change curve and the average of the tangent slopes corresponding to each point in the standard change curve ignore the detailed change characteristics of the curve. Directly using the slope for operation standard change compliance analysis obviously has a large error. Therefore, in order to adjust and correct the deviation of operation status changes caused by different monitoring cycles and external factors and to ensure the authenticity and reliability of the operation standard change compliance analysis results, the corresponding operation status change evaluation compensation factor of each monitoring component is set.

[0059] It should also be added that the number of peak points reflects the frequency of fluctuations in the operating state. If a component has a large number of peak points, it may mean that the operating state of the component changes frequently, which is a fluctuation influencing factor at the overall level, and also a fluctuation assessment factor at the rough level. It cannot show the specific fluctuation details. Therefore, the weight corresponding to the number of peak points is set to be the smallest, and the specific value can be 0.3. The number of interval tracking groups reflects the time interval from the peak to the valley. Shorter intervals may indicate that the change in the operating state is more continuous, reflecting the detailed change characteristics at the horizontal level, and the difference in the change value of the operating standard reflects the magnitude of each change. A larger difference in change value may mean a drastic change in the operating state, which is a detailed change characteristic at the vertical level. Therefore, the weights corresponding to the number of interval tracking groups and the difference in the change value of the operating standard are set to be consistent and greater than the weight corresponding to the number of peak points. For example, the weights corresponding to the number of interval tracking groups and the difference in the change value of the operating standard can be 0.35 respectively.

[0060] When performing change characteristic analysis, the embodiment of the present invention can more accurately reflect the actual operating status of each component by setting an operation change evaluation compensation factor, thereby achieving targeted and adaptive adjustment of the change characteristics, thereby making the evaluation results more accurate, and thus ensuring the effectiveness and representativeness of the change characteristic analysis.

[0061] The device status monitoring module is used to monitor the corresponding monitoring components of the target device through the monitoring terminal carried by the target device, obtain current monitoring data, and import the currently set tracking frequency corresponding to the corresponding monitoring components of the target device.

[0062] In a specific embodiment, the monitoring terminal carried by the target device is composed of a plurality of sensor devices distributed on various monitoring components. For example, the monitoring terminal is composed of: Figure 4 As shown, the sensor equipment and placement positions of some monitoring components corresponding to the monitoring terminals are shown in Table 1.

[0063] Table 1

[0064]

[0065] The equipment operation analysis module is used to set a reference deviation threshold value of each monitoring component corresponding to each state parameter, and analyze the operation state of each monitoring component.

[0066] Specifically, setting the reference deviation threshold of each monitoring component corresponding to each state parameter includes: extracting the allowable deviation threshold of each monitoring component corresponding to each state parameter from the database, recorded as , Indicates state parameters, .

[0067] Set the reference deviation threshold of each monitoring component corresponding to each state parameter , , To set the reference operation compliance level, is a natural constant.

[0068] In a specific embodiment, The specific value can be 0.3.

[0069] It should be added that, when the target device's operation standard change compliance is greater than or equal to the set reference operation standard change compliance, it indicates that the past operation status of the target device met expectations, that is, the setting range of the reference deviation threshold should not be reduced; and when the target device's operation standard change compliance is less than the set reference operation standard change compliance, it indicates that the past operation status of the target device deviates from expectations, and the reference deviation threshold setting range needs to be reduced to ensure that the abnormal situation of the target device can be detected in time, and the exponential function can amplify the impact of larger values, so as to highlight those operation status changes that deviate significantly from the normal range in the evaluation, and at the same time have better robustness and stability. Therefore, the present invention mainly sets the exponential function form for correction according to the operation standard change compliance.

[0070] In yet another specific embodiment, analyzing the operating status of each monitoring component includes: extracting a current monitoring value of each state parameter corresponding to each monitoring component from the current monitoring data.

[0071] The reference value of each state parameter corresponding to each monitoring component is extracted from the database, and the corresponding difference between the current monitoring value and the reference value is calculated to determine whether the difference is within the corresponding reference deviation threshold range.

[0072] If the difference between a certain monitoring component and a certain state parameter is within the reference deviation threshold of the state parameter, the state parameter is recorded as a matching parameter.

[0073] The number of matching parameters of each monitoring component is counted, the ratio of the number of matching parameters to the number of state parameters is calculated, and it is determined whether it is less than the set operation matching pass ratio.

[0074] The operating state of the monitoring component with a judgment result of yes is recorded as abnormal, and the operating state of the monitoring component with a judgment result of no is recorded as normal.

[0075] It should be added that, in a specific embodiment, the running matching ratio can be specifically set to a value of 0.5.

[0076] The embodiment of the present invention ensures the rationality and effectiveness of the analysis results of the operating status of the monitoring components by setting a reference deviation threshold and analyzing the operating status of each monitoring component, while also ensuring the accuracy of the operating status determination. It also displays the operating status of multiple monitoring components, avoids the deficiency of the current relatively single analysis indicators, takes into account the impact of multiple components on the wind turbine, and realizes in-depth analysis of multiple components, which is convenient for comprehensive evaluation of the overall health status of the equipment.

[0077] See also Figure 3 As shown, the monitoring and control analysis module is used to determine whether the tracking settings of the target device need to be regulated. If it is determined to be necessary, it confirms the regulation and monitoring components and the regulation and tracking frequency of the regulation and monitoring components.

[0078] Specifically, judging whether the tracking setting of the target device needs to be adjusted includes: E1, extracting the total amount of power generation recorded at each tracking and the meteorological parameters corresponding to each power generation day from the tracking monitoring log of the target device.

[0079] E2. Extract the equipment parameters of the target equipment from the database, combine the equipment parameters and meteorological parameters, calculate the expected power generation of the target equipment on each power generation day during each tracking, and sum them up to obtain the total expected power generation of each tracking.

[0080] E3. Record the tracking order of the difference between the total expected power generation and the total recorded power generation within the set range as stable tracking, count the number of stable tracking times, and compare it with the number of tracking times, and record the ratio as the power generation efficiency consistency.

[0081] E4. The target device's power generation efficiency consistency is defined as less than the set power generation efficiency consistency as judgment condition 1.

[0082] E5. The existence of a compliance degree of each monitoring component that is less than a set value is defined as judgment condition 2.

[0083] E6. If any one of the judgment conditions 1 and 2 is met, it will be used as the judgment result. If neither the judgment condition 1 nor the judgment condition 2 is met, it will not be used as the judgment result.

[0084] In a specific embodiment, an example of the specific calculation process for calculating the expected power generation of the target device on each power generation day during each tracking by combining the device parameters and the meteorological parameters in step E2 is as follows: 1) Based on the wind speed parameters in the meteorological parameters and the cut-in wind speed and cut-out wind speed in the equipment parameters, determine the effective power generation time periods of the target device on each power generation day.

[0085] It can be understood that the effective power generation time period refers to the time period when the wind speed is between the cut-in wind speed and the cut-out wind speed, and the wind speed parameter refers to the wind speed in each monitoring time period.

[0086] 2) For each effective power generation time period, the average output power is determined according to the wind speed data and the power curve of the target equipment. Based on the effective power generation time periods of the target equipment in each power generation day, the cumulative effective power generation time of the target equipment in each power generation day is counted, and the average output power is multiplied by the cumulative effective power generation time to obtain the expected power generation for each power generation day. Then, based on this rule, the expected power generation of the target equipment on each power generation day during each tracking is obtained.

[0087] It can be understood that the average output power can be calculated by taking a weighted average of the output powers at different wind speeds.

[0088] It should be added that, in actual calculations, the wind direction parameters in the meteorological parameters may also be added for correction. The present invention calculates the expected power generation based on the existing calculation principle and method, so the specific correction process and the specific calculation process will not be shown in detail.

[0089] The database is used to store the reference operation compliance change rate corresponding to each monitoring component in each operation stage, store the equipment parameters of the target equipment, and store the reference value and allowable deviation threshold of each state parameter corresponding to each monitoring component.

[0090] It should be added that the equipment parameters include cut-in wind speed, cut-out wind speed and power curve.

[0091] Specifically, confirming the control and monitoring components includes: if judgment condition 1 is met, each monitoring component is used as a control and monitoring component.

[0092] If only condition 2 is met, the monitoring component whose operation standard change compliance degree is less than the set reference operation standard change compliance degree will be used as the control monitoring component.

[0093] In another specific embodiment, determining the control tracking frequency of the control monitoring component includes: if only judgment condition 1 is met, taking the absolute value of the difference between the power generation efficiency consistency of the control monitoring component and the set power generation efficiency consistency as evaluation variable 1, recorded as ,Will As a regulatory factor, .

[0094] If judgment condition 1 and judgment condition 2 are both met, the absolute value of the difference between the compliance degree of the monitored component and its set value is used as evaluation variable 2, which is recorded as , will As a regulatory factor, , to set the control factor , The value is or , .

[0095] The tracking frequency of the control monitoring component corresponding to the current setting is recorded as ,Will As a control tracking frequency.

[0096] The embodiment of the present invention combines the operating status of each monitoring component to determine the regulation requirements of the tracking setting and confirm the regulation monitoring components and the regulation tracking frequency, so as to facilitate the early identification of components that need maintenance, thereby achieving preventive maintenance and ensuring that the equipment operates in a good state, thereby improving the power generation efficiency. On another level, it can also avoid unnecessary energy consumption and improve energy utilization efficiency.

[0097] The operation result feedback terminal is used to feed back the operation status of each monitoring component to the operation and maintenance management personnel of the target device, and at the same time feed back the control tracking frequency of the control monitoring component to the monitoring control terminal of the target device for tracking and control.

[0098] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A wind power generation equipment operation status monitoring system, characterized in that: include: The monitoring log import module is used to record the currently monitored wind power generation equipment as the target equipment, and import the tracking monitoring log and accumulated operation time of the target equipment; Data fusion analysis module, used to analyze the tracking and monitoring logs of target devices and output the change characteristics of each monitoring component; The analyzing the tracking and monitoring log of the target device includes: Extract the monitoring value of each monitoring component corresponding to each state parameter at each tracking from the tracking monitoring log, and compare it with the reference value interval of each state parameter set for each monitoring component; If the monitoring value of a state parameter corresponding to a certain monitoring component during a certain tracking is within the corresponding reference value interval, the state parameter is recorded as a matching parameter, and the number of matching parameters of each monitoring component during each tracking is counted; The ratio of the number of matching parameters of each monitoring component at each tracking to the number of state parameters of each monitoring component is used as the operation standard, and the operation standard change rate of each monitoring component is determined based on this, which is recorded as , Indicates the monitoring part number, ; The accumulated operation time of the target device is matched and compared with the operation time window corresponding to each set operation stage to obtain the matching operation stage of the target device, and then the reference operation compliance change rate of each monitoring component corresponding to the matching operation stage of the target device is extracted from the database and recorded as ; Set the compensation factor for each monitoring component to evaluate the operation change , the compliance degree of each monitoring component’s operation compliance is counted and recorded as , , is the set reference operation change rate difference, and the operation standard change compliance is used as the change feature; The equipment status monitoring module is used to monitor the corresponding monitoring components of the target equipment through the monitoring terminal carried by the target equipment, obtain the current monitoring data, and import the currently set tracking frequency of each monitoring component of the target equipment; Equipment operation analysis module, used to set the reference deviation threshold of each monitoring component corresponding to each state parameter , and analyze the operating status of each monitoring component; The monitoring and control analysis module is used to determine whether the tracking settings of the target device need to be regulated. If it is determined to be necessary, it confirms the regulated monitoring components and their regulated tracking frequency; A database for storing reference operation compliance change rates of each monitoring component corresponding to each operation stage, storing equipment parameters of target equipment, and storing reference values ​​and allowable deviation thresholds of each state parameter of each monitoring component; The operation result feedback terminal is used to feed back the operation status of each monitoring component to the operation and maintenance management personnel of the target device, and at the same time feed back the control tracking frequency of the control monitoring component to the monitoring and control terminal of the target device for tracking and control; The setting method is: The allowable deviation threshold of each state parameter corresponding to each monitoring component is extracted from the database and recorded as , Indicates state parameters, ; Set the reference deviation threshold of each monitoring component corresponding to each state parameter , , To set the reference operation compliance level, is a natural constant.

2. A wind power generation equipment operating status monitoring system as claimed in claim 1, characterized in that: The confirmation of the change rate of the operation compliance of each monitoring component includes: Extract the tracking date of each tracking from the tracking monitoring log, group two adjacent tracking times into tracking groups, and record the interval days between each tracking in each tracking group as the intermittent tracking days; Calculate the difference in the degree of operation compliance of each monitoring component in each tracking group, obtain the corresponding operation compliance change value of each tracking group, and set the time compensation factor based on the number of intermittent tracking days of each tracking group, and then correct the operation compliance change value, and record the correction result as the confirmed operation compliance change value; With the tracking group sequence as the horizontal coordinate and the confirmed operation standard change value as the vertical coordinate, an operation standard change curve of each monitoring component is constructed, and the slope is extracted from the operation standard change curve as the operation standard change rate.

3. A wind power generation equipment operating status monitoring system as claimed in claim 2, characterized in that: The setting of the time compensation factor includes: Calculate the mean of the intermittent tracking days of each tracking group to obtain the average intermittent tracking days; Calculate the difference between the number of intermittent tracking days of each tracking group and the average number of intermittent tracking days to obtain the difference in the number of intermittent tracking days; If the intermittent tracking days difference corresponding to a tracking group is less than the lower limit of the set reference tracking days difference interval, or is within the set reference tracking days difference interval, 0 is used as the time compensation factor of the tracking group; If the intermittent tracking days difference corresponding to a tracking group exceeds the upper limit of the reference tracking days difference interval, the intermittent tracking days difference corresponding to the tracking group and the upper limit of the reference tracking days difference interval are recorded as as well as ; Will As the time compensation factor of the tracking group, it is recorded as , and the time compensation factor of each tracking group is set to 0 or one of the.

4. A wind power generation equipment operating status monitoring system as claimed in claim 2, characterized in that: The setting of the compensation factor for each monitoring component corresponding to the operation change evaluation includes: The number of peak points is counted from the operation compliance change curve of each monitoring component and recorded as , and at the same time count the number of tracking groups between each peak point and its adjacent valley point and confirm the difference in change value that meets the operation standard; The minimum value is selected from the tracking groups between each peak point and its adjacent valley point as the reference interval tracking group number, which is recorded as , and the average interval tracking group number is obtained by mean calculation, recorded as ,Will and The mean value of ; The maximum value is selected from the difference in the confirmed operation compliance change value between each peak point and its adjacent valley point, and recorded as The average confirmed running standard change value difference is obtained by average calculation ,Will and The mean value of ; Set the compensation factor for each monitoring component to evaluate the operation change , , , and They represent the weights corresponding to the number of peak points, the number of interval tracking groups, and the difference in the running standard change value. , Indicates The number of tracking groups for each tracking component, and They are respectively the set reference peak-to-valley interval tracking group number and the reference operation standard change value difference.

5. A wind power generation equipment operating status monitoring system as claimed in claim 1, characterized in that: The analyzing the operating status of each monitoring component includes: Extracting the current monitoring value of each state parameter corresponding to each monitoring component from the current monitoring data; Extracting reference values ​​of each state parameter of each monitoring component from the database, performing corresponding difference calculation between the current monitoring value and the reference value, and determining whether the difference is within the corresponding reference deviation threshold range; If the difference value of a certain monitoring component corresponding to a certain state parameter is within the reference deviation threshold range of the state parameter, the state parameter is recorded as a matching parameter; Count the number of matching parameters of each monitoring component, calculate the ratio of the number of matching parameters to the number of state parameters, and determine whether it is less than the set operation matching pass ratio; The operating state of the monitoring component with a judgment result of yes is recorded as abnormal, and the operating state of the monitoring component with a judgment result of no is recorded as normal.

6. A wind power generation equipment operating status monitoring system as claimed in claim 1, characterized in that: The determining whether the tracking setting of the target device needs to be adjusted includes: Extract the total power generation recorded at each tracking and the meteorological parameters corresponding to each power generation day from the tracking monitoring log of the target device; Extract the equipment parameters of the target equipment from the database, combine the equipment parameters and meteorological parameters, calculate the expected power generation of the target equipment on each power generation day during each tracking, and sum them up to obtain the total expected power generation of each tracking; The tracking order in which the difference between the total estimated power generation and the total recorded power generation is within the set range is recorded as stable tracking, the number of stable tracking is counted and compared with the number of tracking, and the ratio is recorded as the power generation efficiency consistency; The power generation efficiency matching degree of the target device is less than the set power generation efficiency matching degree, which is defined as judgment condition 1; The existence of a compliance degree of each monitoring component reaching the standard that is less than a set value is defined as judgment condition 2; If any one of the judgment conditions 1 and 2 is met, it will be needed as the judgment result. If neither the judgment condition 1 nor the judgment condition 2 is met, it will not be needed as the judgment result.

7. A wind power generation equipment operating status monitoring system as claimed in claim 6, characterized in that: The confirmation, regulation and monitoring component comprises: If judgment condition 1 is met, all monitoring components are used as control monitoring components; If only condition 2 is met, the monitoring component whose operation standard change compliance degree is less than the set reference operation standard change compliance degree will be used as the control monitoring component.

8. A wind power generation equipment operating status monitoring system as claimed in claim 6, characterized in that: The step of confirming the control tracking frequency of the control monitoring component includes: If only judgment condition 1 is met, the absolute value of the difference between the power generation efficiency consistency of the control monitoring component and the set power generation efficiency consistency is used as the evaluation variable 1, which is recorded as ,Will As a regulatory factor, ; If judgment condition 1 and judgment condition 2 are both met, the absolute value of the difference between the compliance degree of the monitored component and its set value is used as evaluation variable 2, which is recorded as , will As a regulatory factor, , to set the control factor , The value is or , ; The tracking frequency of the control monitoring component corresponding to the current setting is recorded as ,Will As a control tracking frequency.

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