A method, device, equipment and storage medium for monitoring operation of power distribution cabinet

Abstract

The present application provides a method, device, equipment and storage medium for monitoring the operation of a distribution cabinet, and relates to the field of distribution cabinet monitoring technology, including: performing long-term continuous monitoring of a target distribution cabinet according to a preset electrical parameter set to obtain multiple monitoring electrical parameter sets; traversing multiple monitoring electrical parameter sets to perform comprehensive analysis of distribution cabinet operation fluctuations and determine operation fluctuation factors; performing long-term temperature monitoring of multiple key equipment of the target distribution cabinet; performing analysis based on multiple monitoring temperature sets, and determining a temperature field dynamic monitoring scheme for multiple key equipment according to the temperature fluctuations of different key equipment; matching the electrical parameter monitoring cycle of the target distribution cabinet based on the operation fluctuation factor; and performing operation monitoring of the target distribution cabinet according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring scheme. The present application solves the technical problem of low monitoring accuracy caused by insufficient flexibility of the monitoring scheme in the prior art, and improves the accuracy of distribution cabinet operation monitoring.

Description

Technical Field

[0001] The present application relates to the technical field of power distribution cabinet monitoring, and in particular to a method, device, equipment and storage medium for monitoring the operation of a power distribution cabinet. Background Art

[0002] In modern power systems, distribution cabinets, as key components, undertake the important task of distributing and controlling electric energy. Their stable operation directly affects the power supply quality and grid security.

[0003] The current distribution cabinet operation monitoring method mainly relies on manual regular inspections combined with simple automated monitoring methods. Although it can guarantee the basic operation of the equipment to a certain extent, it has obvious limitations. On the one hand, this type of monitoring method focuses on the instantaneous value or short-term trend of electrical parameters. The monitoring cycle is usually a fixed time interval, ignoring the deep mining potential of long-term time series data. It is difficult to make dynamic adjustments according to actual operating conditions, resulting in low sensitivity to operating fluctuations and inability to warn of potential risks in advance. On the other hand, in terms of temperature monitoring, static standards are generally adopted, which fail to fully consider the working characteristics and temperature distribution differences of key equipment, making abnormal temperature signals easy to be ignored, increasing the probability of sudden equipment failure. Summary of the invention

[0004] The present application provides a method, device, equipment and storage medium for monitoring the operation of a distribution cabinet, which solves the technical problems that the existing distribution cabinet operation monitoring technology mostly adopts static solutions and short-term monitoring, and lacks personalized monitoring of key equipment, resulting in low monitoring accuracy and difficulty in timely warning of equipment failures. The application achieves the technical effect of improving the accuracy of distribution cabinet operation monitoring and thus improving the stability and safety of distribution cabinet operation.

[0005] In view of the above problems, on the one hand, the present application provides a method for monitoring the operation of a distribution cabinet, the method comprising: performing long-term continuous monitoring of a target distribution cabinet according to a preset electrical parameter set to obtain multiple monitoring electrical parameter sets; traversing the multiple monitoring electrical parameter sets to perform a comprehensive analysis of the operation fluctuations of the distribution cabinet to determine the operation fluctuation factor; extracting multiple key equipment of the target distribution cabinet, performing long-term temperature monitoring of the multiple key equipment to obtain multiple monitoring temperature sets; performing analysis based on the multiple monitoring temperature sets, and determining a dynamic temperature field monitoring scheme for the multiple key equipment according to the temperature fluctuations of different key equipment; matching the electrical parameter monitoring cycle of the target distribution cabinet based on the operation fluctuation factor; and performing operation monitoring on the target distribution cabinet according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring scheme.

[0006] On the other hand, the present application also provides a distribution cabinet operation monitoring device, which includes: a continuous monitoring module, which is used to perform long-term continuous monitoring of the target distribution cabinet according to a preset electrical parameter set to obtain multiple monitoring electrical parameter sets; a fluctuation analysis module, which is used to traverse the multiple monitoring electrical parameter sets to perform a comprehensive analysis of the distribution cabinet operation fluctuations and determine the operation fluctuation factors; a temperature monitoring module, which is used to extract multiple key devices of the target distribution cabinet, perform long-term temperature monitoring of the multiple key devices, and obtain multiple monitoring temperature sets; a monitoring scheme determination module, which is used to perform analysis based on the multiple monitoring temperature sets, and determine the temperature field dynamic monitoring scheme of the multiple key devices according to the temperature fluctuations of different key devices; a monitoring cycle matching module, which is used to match the electrical parameter monitoring cycle of the target distribution cabinet based on the operation fluctuation factors; an operation monitoring module, which is used to perform operation monitoring of the target distribution cabinet according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring scheme.

[0007] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps in the method for monitoring the operation of a distribution cabinet as described in any one of the above claims are implemented.

[0008] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in any one of the above-mentioned methods for monitoring the operation of a distribution cabinet are implemented.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] According to the preset electrical parameter set, the target distribution cabinet is continuously monitored over a long period of time to obtain multiple monitoring electrical parameter sets, providing data support for subsequent fluctuation analysis. The multiple monitoring electrical parameter sets are traversed to conduct a comprehensive analysis of the distribution cabinet operation fluctuations, quantify the fluctuation characteristics, and determine the operation fluctuation factors to identify the fluctuations and operation characteristics of the distribution cabinet in the long-term operation, and find out potential abnormal factors. Extract multiple key equipment of the target distribution cabinet, perform long-term temperature monitoring on the multiple key equipment, and obtain multiple monitoring temperature sets; analyze based on the multiple monitoring temperature sets, and formulate a temperature field dynamic monitoring plan for the key equipment according to the temperature fluctuations of different key equipment, so as to more accurately capture potential faults caused by temperature changes. Match the electrical parameter monitoring cycle of the target distribution cabinet based on the operation fluctuation factor, so that the monitoring cycle can be flexibly adjusted according to the actual situation of the equipment, thereby enhancing the timeliness of monitoring. Comprehensive operation monitoring of the target distribution cabinet is performed according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring plan.

[0011] In summary, this application realizes more intelligent and comprehensive real-time monitoring of the distribution cabinet through the above steps. Through long-term monitoring and fluctuation analysis of electrical parameters and key equipment temperature, the monitoring cycle and temperature field dynamic monitoring plan are determined, thereby optimizing monitoring resources, ensuring that key equipment is always within the key monitoring range, and avoiding monitoring blind spots. This technical solution significantly improves the flexibility and accuracy of distribution cabinet operation monitoring, improves the stability and safety of distribution cabinet operation, and thus enhances the reliability and stability of the power system.

[0012] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic diagram of a flow chart of a method for monitoring the operation of a power distribution cabinet provided in an embodiment of the present application;

[0014] Figure 2 A schematic diagram of a flow chart of determining an operation fluctuation factor in a method for monitoring operation of a power distribution cabinet provided in an embodiment of the present application;

[0015] Figure 3 A schematic diagram of the structure of a power distribution cabinet operation monitoring device provided in an embodiment of the present application;

[0016] Figure 4 A schematic diagram of the structure of a computer device provided in an embodiment of the present application.

[0017] Explanation of the accompanying drawings: continuous monitoring module 10, fluctuation analysis module 20, temperature monitoring module 30, monitoring scheme determination module 40, monitoring cycle matching module 50, operation monitoring module 60, bus 300, receiver 301, processor 302, transmitter 303, memory 304, bus interface 305. DETAILED DESCRIPTION

[0018] The embodiments of the present application provide a method, device, equipment and storage medium for monitoring the operation of a distribution cabinet, thereby solving the technical problems that the existing distribution cabinet operation monitoring technology mostly adopts static solutions and short-term monitoring, and lacks personalized monitoring of key equipment, resulting in low monitoring accuracy and difficulty in timely warning of equipment failures. The technical effect of improving the accuracy of distribution cabinet operation monitoring and thus enhancing the stability and safety of distribution cabinet operation is achieved.

[0019] Embodiment 1, as Figure 1 As shown, an embodiment of the present application provides a method for monitoring the operation of a distribution cabinet, the method comprising:

[0020] Step S1: Perform long-term continuous monitoring of the target power distribution cabinet according to a preset electrical parameter set to obtain multiple monitoring electrical parameter sets.

[0021] Specifically, the preset electrical parameter set refers to a set of electrical parameters set before monitoring, usually including voltage, current, power, power factor, etc. These parameters reflect the electrical operation status of the distribution cabinet. The monitored electrical parameter set refers to the electrical data set recorded and formed during the continuous monitoring process.

[0022] First, a set of electrical parameters is selected from the key electrical status indicators in the distribution cabinet as the preset electrical parameter set. Real-time data collection is performed through sensors installed in the distribution cabinet, such as voltage sensors, current transformers, etc., and the collected data is recorded continuously for a long time through the data acquisition device. Multiple monitoring electrical parameter sets are summarized to provide basic data support for subsequent fluctuation analysis.

[0023] Step S2: traverse the plurality of monitoring electrical parameter sets to conduct a comprehensive analysis of the operation fluctuations of the power distribution cabinet and determine the operation fluctuation factor.

[0024] Specifically, the operation fluctuation factor refers to the key indicator reflecting the operation fluctuation of the distribution cabinet obtained by data analysis, which can be a drastic change or abnormal pattern of certain electrical parameters.

[0025] Traverse all the recorded electrical parameter sets and use data processing tools or software (such as the data processing library Pandas in Python) to analyze the parameter data at each time point one by one. Through data comparison, trend analysis, etc., identify abnormal operating fluctuations of each electrical parameter, such as obvious fluctuations in current or unstable voltage in certain time periods, and generate corresponding operating fluctuation factors. For example, if the current in the distribution cabinet suddenly increases by 10% within a certain period of time, this will be calculated as an abnormal operating fluctuation factor.

[0026] Step S3: extract multiple key devices of the target power distribution cabinet, perform long-term temperature monitoring on the multiple key devices, and obtain multiple monitoring temperature sets.

[0027] Specifically, key equipment refers to the core components in the power distribution cabinet, including circuit breakers, contactors, transformers, busbars, cable connectors, etc. The monitoring temperature set is a data set formed by the temperature data of key equipment at different time points.

[0028] Temperature sensors are installed on key equipment in the power distribution cabinet. The temperature of each key equipment is continuously monitored by the temperature sensors. The temperature data of each key equipment monitored is aggregated to generate a monitoring temperature set. The temperature sensor can be a thermocouple or an infrared thermometer. For example, the circuit breaker is one of the components that is prone to overheating. Temperature sensors are installed around it, and its temperature value is recorded every hour by a data recording device to form a set containing the temperature data of the circuit breaker at different time points.

[0029] Step S4: Analyze the multiple monitoring temperature sets and determine the temperature field dynamic monitoring schemes for the multiple key devices according to the temperature fluctuations of different key devices.

[0030] Specifically, the temperature field dynamic monitoring scheme is a monitoring strategy formulated based on the temperature change characteristics of key equipment. Use data analysis tools (such as Excel, Pandas library in Python) to process the temperature data in the multiple monitoring temperature sets obtained in step S3 to identify the trends and patterns of temperature changes. For example, the temperature of a circuit breaker may rise during a high-load period, while the temperature of a transformer may slowly drop after the load is reduced. Based on the temperature data analysis results corresponding to each key device, a corresponding dynamic monitoring strategy is formulated according to the characteristics of different devices. For example, for equipment with drastic temperature fluctuations, such as circuit breakers, the monitoring frequency can be increased and set to data collection once a minute to ensure that temperature changes can be captured in real time. For equipment with slower temperature changes, the monitoring interval can be extended.

[0031] By analyzing temperature fluctuations, corresponding monitoring plans can be formulated according to the needs of different equipment, and the frequency and focus of temperature monitoring can be dynamically adjusted, so that equipment can receive more intensive attention during high-risk periods, so that timely responses can be made when the temperature is abnormal, reducing the risk of equipment overheating or failure.

[0032] Step S5: matching the electrical parameter monitoring period of the target power distribution cabinet based on the operation fluctuation factor.

[0033] Specifically, the monitoring cycle refers to the time interval for monitoring the electrical parameters of the distribution cabinet, that is, how often data is collected and analyzed. The monitoring cycle of electrical parameters can be adjusted by analyzing the operating fluctuation factors of the distribution cabinet. When the fluctuation factor is large, the monitoring cycle is shortened and the collection frequency is increased to ensure that the detailed changes during the fluctuation period can be captured in real time. When the fluctuation factor is small, it indicates that the equipment is running smoothly. The monitoring cycle can be extended to reduce unnecessary data collection, thereby saving system resources. For example, if the analysis shows that the fluctuation factor is high during high-load periods, the monitoring cycle can be shortened and the original hourly data collection can be adjusted to every 15 minutes. During stable operation periods, the monitoring cycle can be relatively extended. This way of dynamically adjusting the monitoring cycle can ensure that more monitoring data is obtained at critical moments, so that abnormal situations can be discovered more quickly.

[0034] Step S6: monitoring the operation of the target power distribution cabinet according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring scheme.

[0035] Specifically, the real-time data acquisition system of the power distribution cabinet monitors the electrical parameters and key equipment temperatures of the power distribution cabinet in real time according to the electrical parameter monitoring cycle and temperature field dynamic monitoring scheme determined above to ensure the safe and stable operation of the power distribution cabinet. The electrical parameter monitoring cycle is dynamically adjusted according to the operating fluctuation factor to ensure that electrical parameter anomalies receive timely attention; the temperature field monitoring scheme performs intensive monitoring based on equipment temperature fluctuations, and invests more monitoring resources in abnormal equipment. For example, electrical parameter data is frequently collected according to high-load periods, and more intensive temperature monitoring is performed for equipment that is prone to overheating. When electrical parameter fluctuations are abnormal or the temperature of key equipment is abnormal, an alarm is issued to prompt maintenance personnel to conduct inspections.

[0036] Combining the electrical parameter monitoring cycle and temperature field dynamic monitoring solution to monitor the operation of the distribution cabinet not only improves the monitoring accuracy, but also prevents faults in a timely manner to ensure the safety and reliability of the distribution cabinet operation.

[0037] Furthermore, the preset electrical parameter set described in step S1 of the embodiment of the present application includes voltage, current, power, power factor and frequency.

[0038] Specifically, the voltage, current, power, power factor and frequency data are collected in real time through sensors and monitoring equipment installed on the distribution cabinet. For example, the voltage sensor measures the voltage value in the circuit, the current transformer measures the current value, the power meter calculates the real-time power and power factor, and the frequency meter measures the frequency of the current or voltage. By continuously monitoring these parameters over a long period of time, a large amount of data can be accumulated to provide a basis for the subsequent analysis of the operating status of the distribution cabinet.

[0039] Further, such as Figure 2 As shown, step S2 of the embodiment of the present application also includes:

[0040] Calculate the fluctuation variance of the multiple monitoring electrical parameter sets respectively to obtain multiple fluctuation coefficients; divide the multiple fluctuation coefficients by the sum of the multiple fluctuation coefficients respectively, and multiply the ratio by a preset search step to obtain multiple parameter search steps; perform densely distributed parameter screening on the multiple monitoring electrical parameter sets based on the multiple parameter search steps to obtain multiple densely distributed parameter sets; calculate the fluctuation variance of the multiple densely distributed parameter sets, and perform mean calculation on the calculation results to obtain the operation fluctuation factor.

[0041] Specifically, for each set of monitored electrical parameters obtained in step S1, the square average of the deviations of each data in the set from its average value is calculated to obtain the fluctuation variance, which reflects the degree of fluctuation of each set of electrical parameters over time. The larger the fluctuation variance, the greater the fluctuation amplitude of the data. The obtained fluctuation variance is recorded as the fluctuation coefficient corresponding to each set of monitored data.

[0042] To make different volatility coefficients comparable, each volatility coefficient is divided by the sum of all volatility coefficients to get the proportion of each parameter relative to the overall volatility. These proportion values ​​are then multiplied by a preset search step to get the parameter search step for each parameter. The step size determines the level of precision when screening densely distributed parameters. The smaller the step size, the finer the screening, which can more accurately reflect the operating fluctuations within certain specific time periods. The preset search step size is a predefined value used to determine the search precision during the screening of densely distributed parameters.

[0043] According to the parameter search step of each parameter, the corresponding monitoring electrical parameter set is divided, the number of data points in each interval is counted, and the interval with the densest data points is selected to form a densely distributed parameter set. These sets can be regarded as electrical parameter sets under relatively stable operating conditions, which can represent the operating fluctuations of the distribution cabinet in a relatively short period of time. The above-mentioned parameter dense distribution screening operation is performed on each monitoring electrical parameter set to obtain multiple densely distributed parameter sets, and the fluctuation variance of all densely distributed parameter sets is calculated, that is, the square average of the deviation of each data in the set from its average value. Then, the average value of all fluctuation variances is calculated and recorded as the operating fluctuation factor. This factor provides a quantitative basis for dynamically adjusting the monitoring period of the distribution cabinet to ensure that the fluctuations of electrical parameters can be captured in time during the monitoring period, so as to more accurately monitor the operating status of the distribution cabinet.

[0044] Further, based on the multiple parameter search step sizes, the multiple monitored electrical parameter sets are screened for dense distribution of parameters to obtain multiple dense distribution parameter sets, and further includes:

[0045] Determine multiple electrical parameter means of the multiple monitored electrical parameter sets, use the multiple electrical parameter means as multiple screening starting circle centers, and use the multiple parameter search steps as radii to determine multiple starting densely distributed parameter sets, wherein the starting densely distributed parameter is a monitored electrical parameter whose difference with an electrical parameter mean is within the corresponding parameter search step; count multiple starting screening quantities of the multiple starting densely distributed parameter sets; iterate the multiple screening starting circle centers in the multiple monitored electrical parameter sets based on the multiple parameter search steps to determine multiple screening iteration circle centers and multiple iterative densely distributed parameter sets; count multiple iterative screening quantities of the multiple iterative densely distributed parameter sets, and compare the multiple iterative screening quantities with the multiple starting screening quantities to determine whether to update the multiple screening starting circle centers, and after multiple updates until the screening is stopped, use the multiple iterative densely distributed parameter sets corresponding to the maximum screening quantity values ​​as multiple densely distributed parameter sets.

[0046] Furthermore, when the screening amount difference between the multiple iterative screening amounts and the multiple initial screening amounts is less than or equal to a preset screening amount difference, the screening is stopped.

[0047] Specifically, the parameter dense distribution screening process must first calculate the electrical parameter mean corresponding to each monitored electrical parameter set, including voltage mean, current mean, power mean, power factor mean, frequency mean, etc. Take each electrical parameter mean as the initial center point, and use the corresponding electrical parameter search step as the radius to screen in the monitored electrical parameter set, and screen out the monitored electrical parameter values ​​whose difference with the electrical parameter mean is less than the corresponding electrical parameter search step, and summarize these screened data into the corresponding starting dense distribution parameter set. For example, taking a current parameter set as an example, the current mean is 50A, and the search step is 5A, then all current values ​​in the range of 45A to 55A are screened out as the starting dense distribution current parameters.

[0048] The number of parameters in each starting densely distributed parameter set is counted and recorded as the starting screening amount. The starting screening amount reflects the distribution density of each parameter near its mean value and is used to evaluate the density of parameters captured during the initial screening. Next, the starting screening circle center is moved with the parameter search step length as the moving distance, and multiple starting screening circle centers are iterated. During the iteration process, for each new circle center position, the densely distributed parameter set is re-determined according to the same steps above.

[0049] After each iteration, the number of data points in each new set of densely distributed parameters is counted and recorded as the iterative screening amount. The iterative screening amount is compared with the starting screening amount. If the iterative screening amount is greater than the starting screening amount, the screening starting circle center is updated to the current iterative circle center, and the iterative screening amount becomes the new starting screening amount. Otherwise, it is not updated.

[0050] After each iteration, the difference between the iterative screening amount and the initial screening amount is calculated. When the difference between the iterative screening amount and the initial screening amount is less than or equal to the preset screening amount difference, it means that the screening amount change is stable at this time, that is, the screening process has converged, and the screening process can be stopped. The iterative dense distribution parameter set corresponding to the maximum screening amount is used as the final dense distribution parameter set. These sets contain the areas with the densest parameter values, which correspond to the key features or potential problems in the operation of the distribution cabinet.

[0051] Exemplarily, for a voltage monitoring electrical parameter set of a distribution cabinet, the voltage mean is first calculated to be 120V, and the parameter search step is 2V. With 120V as the starting center, the initial dense distribution set is screened, which contains 100 data points, that is, the initial screening amount is 100. At the beginning of the iteration, the center of the circle is moved to 122V, and it is found that it contains 110 data points, so the center of the circle is updated to 122V, and the new starting screening amount is 110. Continue to iterate to 124V, which contains 105 data points, which is less than the new starting screening amount, but does not meet the stop condition (the preset screening amount difference is 5), and continue to iterate and screen. When the center of the circle moves to 126V, the screening amount is 104, which is less than the new starting screening amount and the difference is less than or equal to the preset screening amount difference 5, and the screening stops. Finally, the dense distribution set (110 data points) at the center position of 122V is determined as a dense distribution parameter set.

[0052] Through the above iterative process, it is possible to more accurately locate areas where parameters are densely distributed, providing more accurate data support for subsequent calculations of operating fluctuation factors, thereby improving the sensitivity and accuracy of the monitoring system.

[0053] Furthermore, step S4 of the embodiment of the present application also includes:

[0054] Perform fluctuation analysis on the multiple monitoring temperature sets to determine multiple temperature fluctuation coefficients; screen the multiple monitoring temperature sets according to the benchmark temperature tolerance range to extract multiple out-of-range monitoring temperature sets; determine multiple temperature anomaly coefficients of the multiple key equipment based on the multiple out-of-range monitoring temperature sets; determine the temperature field dynamic monitoring plan based on the multiple temperature fluctuation coefficients and the multiple temperature anomaly coefficients.

[0055] Specifically, the temperature fluctuation coefficient is a coefficient calculated through fluctuation analysis, which is used to measure the degree of temperature fluctuation of key equipment. The larger the fluctuation coefficient, the more drastic the temperature change. The reference temperature tolerance range is the temperature fluctuation range allowed for normal operation of the equipment, which is set according to the equipment performance of each key equipment in the power distribution cabinet. The out-of-range monitoring temperature set refers to the data set in which the equipment temperature exceeds the reference temperature tolerance range, indicating that these temperature values ​​are abnormal or require special attention. The temperature anomaly coefficient is a coefficient calculated based on the out-of-range data, which is used to measure the severity of temperature anomalies. The higher the anomaly coefficient, the more obvious or frequent the temperature anomaly of the equipment is.

[0056] Perform fluctuation analysis on the monitoring temperature set of each key device and calculate the temperature fluctuation coefficient of each device. The calculation process refers to the electrical parameter fluctuation coefficient in step S2. According to the set reference temperature tolerance range, screen the monitoring temperature set of each key device, extract data that exceeds the reference temperature tolerance range, and summarize it into the out-of-range monitoring temperature set.

[0057] Analyze the data in each super-interval monitoring temperature set, quantify the frequency and degree of the equipment temperature exceeding the reference temperature range, and calculate the temperature anomaly coefficient corresponding to each key device. The data analysis process can calculate the abnormal frequency ratio or abnormal temperature difference integral of the data in each super-interval monitoring temperature set as the temperature anomaly coefficient. Among them, the abnormal frequency ratio is the ratio of the number of times the equipment temperature data exceeds the reference temperature range (upper and lower limits) to the total number of monitoring data points. The higher the abnormal frequency ratio, the more frequently the equipment is in an abnormal temperature state. The abnormal temperature difference integral is the sum of the temperature differences of the equipment temperature data exceeding the reference temperature range. The larger the abnormal temperature difference integral value, the more serious the deviation of the abnormal temperature, and the risk of overheating or overcooling of the equipment. According to the calculated temperature fluctuation coefficient and temperature anomaly coefficient of each key device, a corresponding temperature field dynamic monitoring plan is formulated for each key device.

[0058] Through all the above steps, the temperature monitoring strategy can be dynamically adjusted according to the actual operation of key equipment, thereby improving the pertinence and effectiveness of operation monitoring.

[0059] Further, determining the temperature field dynamic monitoring scheme based on the multiple temperature fluctuation coefficients and the multiple temperature anomaly coefficients also includes:

[0060] Based on the multiple temperature fluctuation coefficients and the multiple temperature anomaly coefficients, multiple abnormal key equipment are determined; according to the number of the multiple abnormal key equipment and the multiple key equipment, the abnormal ratio is obtained, and the dynamic monitoring constraint conditions of the abnormal key equipment are determined based on the abnormal ratio, wherein the dynamic monitoring constraint conditions of the abnormal key equipment are that the number of abnormal key equipment must be greater than or equal to the abnormal ratio during each dynamic monitoring; the multiple key equipment are randomly extracted according to the preset synchronous temperature monitoring equipment quantity to obtain multiple first dynamic monitoring key equipment sets; it is judged whether the multiple first dynamic monitoring key equipment sets meet the dynamic monitoring constraint conditions of the abnormal key equipment, and if so, the first dynamic monitoring key equipment is used as the temperature field dynamic monitoring scheme.

[0061] Specifically, the dynamic monitoring constraint is a restriction set in the dynamic monitoring to ensure that a certain number of abnormal critical devices must be included each time the dynamic monitoring is performed. The number of simultaneous temperature monitoring devices refers to the number of devices that perform temperature monitoring simultaneously during each dynamic monitoring process.

[0062] Based on the temperature fluctuation coefficient and the temperature anomaly coefficient, identify the key devices that exceed the preset threshold or behave abnormally and mark them as abnormal key devices. Calculate the ratio of the number of abnormal key devices to the total number of key devices and record it as the abnormal ratio, which reflects the proportion of abnormal devices in the power distribution cabinet.

[0063] During each dynamic monitoring, the number of abnormal key devices among the monitored devices must reach or exceed the abnormal ratio, and this condition is set as the dynamic monitoring constraint condition for abnormal key devices. This condition is set to ensure that monitoring resources are allocated to abnormal devices first, thereby improving the efficiency and pertinence of operation monitoring.

[0064] According to the preset number of synchronous temperature monitoring devices, randomly select devices from all key devices for monitoring to form the first dynamic monitoring key device set. Determine whether the number of abnormal key devices in the randomly selected devices reaches or exceeds the abnormal ratio. If not, re-randomly select. If satisfied, the device set that meets the conditions is implemented as the temperature field dynamic monitoring plan.

[0065] For example, a power distribution cabinet has 50 key devices. After temperature fluctuation and anomaly analysis, 10 devices are marked as abnormal key devices, and the abnormal ratio is (10 / 50) × 100% = 20%. The set number of synchronous monitoring devices is 10, and the dynamic monitoring constraint is that at least 20% of the devices are abnormal key devices. First, 10 devices are randomly selected from the 50 devices for monitoring. Among the 10 devices selected for the first time, 3 are abnormal key devices, and the abnormal ratio is 30%, which exceeds the abnormal ratio of 20%. Then the selected devices meet the dynamic monitoring constraint. These 10 devices are used as the final set of dynamic monitoring key devices, and their temperature field is monitored in subsequent monitoring cycles.

[0066] Through the above steps, a dynamic temperature field monitoring plan is formulated to balance resources while ensuring that abnormal key equipment accounts for a sufficient proportion in the monitoring, thereby increasing attention to abnormal equipment, reducing the risk of missed detection, and making operation monitoring more efficient and reliable.

[0067] In summary, the method for monitoring the operation of a power distribution cabinet provided in the embodiment of the present application has the following technical effects:

[0068] According to the preset electrical parameter set, the target distribution cabinet is continuously monitored over a long period of time to obtain multiple monitoring electrical parameter sets, providing data support for subsequent fluctuation analysis. The multiple monitoring electrical parameter sets are traversed to conduct a comprehensive analysis of the distribution cabinet operation fluctuations, and the fluctuation characteristics are quantified by calculating the fluctuation variance and dense distribution screening, and the operation fluctuation factor is determined to identify the fluctuations and operation characteristics of the distribution cabinet in the long-term operation, find out the potential abnormal factors, and improve the sensitivity to the fluctuation of the equipment operation status. Extract multiple key equipment of the target distribution cabinet, perform long-term temperature monitoring on the multiple key equipment, and obtain multiple monitoring temperature sets; analyze based on the multiple monitoring temperature sets, according to the temperature fluctuations of different key equipment, extract temperature abnormal equipment through fluctuation analysis and abnormal screening, calculate the temperature fluctuation coefficient and abnormal coefficient, perform temperature abnormality analysis on the equipment, and formulate a temperature field dynamic monitoring plan for key equipment. Through the temperature field dynamic monitoring plan, resources can be concentrated to focus on monitoring abnormal equipment, while reducing the monitoring burden on normal equipment, more accurately capturing potential faults caused by temperature changes, and improving the efficiency and accuracy of operation monitoring. The electrical parameter monitoring cycle of the target power distribution cabinet is matched based on the operation fluctuation factor, so that the monitoring cycle can be flexibly adjusted according to the actual situation of the equipment, thereby optimizing the monitoring resources. The target power distribution cabinet is fully monitored according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring scheme.

[0069] Overall, the embodiment of the present application realizes more intelligent and comprehensive real-time monitoring of the distribution cabinet. Through long-term monitoring and fluctuation analysis of electrical parameters and key equipment temperature, the monitoring cycle and temperature field dynamic monitoring plan are determined, thereby optimizing monitoring resources, ensuring that key equipment is always within the key monitoring range, and avoiding monitoring blind spots. This method significantly improves the flexibility and accuracy of distribution cabinet operation monitoring, improves the stability and safety of distribution cabinet operation, and thus enhances the reliability and stability of the power system.

[0070] Embodiment 2, as Figure 3 As shown, an embodiment of the present application provides a distribution cabinet operation monitoring device, the device comprising:

[0071] The continuous monitoring module 10 is used to perform long-term continuous monitoring of the target power distribution cabinet according to a preset electrical parameter set to obtain multiple monitoring electrical parameter sets.

[0072] The fluctuation analysis module 20 is used to traverse the multiple monitoring electrical parameter sets to perform comprehensive analysis on the operation fluctuations of the distribution cabinet and determine the operation fluctuation factors.

[0073] The temperature monitoring module 30 is used to extract multiple key devices of the target power distribution cabinet, perform long-term temperature monitoring on the multiple key devices, and obtain multiple monitoring temperature sets.

[0074] The monitoring scheme determination module 40 is used to analyze the multiple monitoring temperature sets and determine the temperature field dynamic monitoring scheme of the multiple key devices according to the temperature fluctuation of different key devices.

[0075] The monitoring cycle matching module 50 is used to match the electrical parameter monitoring cycle of the target power distribution cabinet based on the operation fluctuation factor.

[0076] The operation monitoring module 60 is used to monitor the operation of the target power distribution cabinet according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring solution.

[0077] Furthermore, the preset electrical parameter set in the continuous monitoring module 10 of the embodiment of the present application includes voltage, current, power, power factor and frequency.

[0078] Furthermore, the fluctuation analysis module 20 of the embodiment of the present application is also used to perform the following steps:

[0079] Calculate the fluctuation variance of the multiple monitoring electrical parameter sets respectively to obtain multiple fluctuation coefficients; divide the multiple fluctuation coefficients by the sum of the multiple fluctuation coefficients respectively, and multiply the ratio by a preset search step to obtain multiple parameter search steps; perform densely distributed parameter screening on the multiple monitoring electrical parameter sets based on the multiple parameter search steps to obtain multiple densely distributed parameter sets; calculate the fluctuation variance of the multiple densely distributed parameter sets, and perform mean calculation on the calculation results to obtain the operation fluctuation factor.

[0080] Furthermore, the fluctuation analysis module 20 of the embodiment of the present application is also used to perform the following steps:

[0081] Determine multiple electrical parameter means of the multiple monitored electrical parameter sets, use the multiple electrical parameter means as multiple screening starting circle centers, and use the multiple parameter search steps as radii to determine multiple starting densely distributed parameter sets, wherein the starting densely distributed parameter is a monitored electrical parameter whose difference with an electrical parameter mean is within the corresponding parameter search step; count multiple starting screening quantities of the multiple starting densely distributed parameter sets; iterate the multiple screening starting circle centers in the multiple monitored electrical parameter sets based on the multiple parameter search steps to determine multiple screening iteration circle centers and multiple iterative densely distributed parameter sets; count multiple iterative screening quantities of the multiple iterative densely distributed parameter sets, and compare the multiple iterative screening quantities with the multiple starting screening quantities to determine whether to update the multiple screening starting circle centers, and after multiple updates until the screening is stopped, use the multiple iterative densely distributed parameter sets corresponding to the maximum screening quantity values ​​as multiple densely distributed parameter sets.

[0082] Furthermore, the fluctuation analysis module 20 of the embodiment of the present application is also used to perform the following steps:

[0083] When the screening amount difference between the multiple iterative screening amounts and the multiple initial screening amounts is less than or equal to the preset screening amount difference, the screening is stopped.

[0084] Furthermore, the monitoring scheme determination module 40 of the embodiment of the present application is also used to perform the following steps:

[0085] Perform fluctuation analysis on the multiple monitoring temperature sets to determine multiple temperature fluctuation coefficients; screen the multiple monitoring temperature sets according to the benchmark temperature tolerance range to extract multiple out-of-range monitoring temperature sets; determine multiple temperature anomaly coefficients of the multiple key equipment based on the multiple out-of-range monitoring temperature sets; determine the temperature field dynamic monitoring plan based on the multiple temperature fluctuation coefficients and the multiple temperature anomaly coefficients.

[0086] Furthermore, the monitoring scheme determination module 40 of the embodiment of the present application is also used to perform the following steps:

[0087] Based on the multiple temperature fluctuation coefficients and the multiple temperature anomaly coefficients, multiple abnormal key equipment are determined; according to the number of the multiple abnormal key equipment and the multiple key equipment, the abnormal ratio is obtained, and the dynamic monitoring constraint conditions of the abnormal key equipment are determined based on the abnormal ratio, wherein the dynamic monitoring constraint conditions of the abnormal key equipment are that the number of abnormal key equipment must be greater than or equal to the abnormal ratio during each dynamic monitoring; the multiple key equipment are randomly extracted according to the preset synchronous temperature monitoring equipment quantity to obtain multiple first dynamic monitoring key equipment sets; it is judged whether the multiple first dynamic monitoring key equipment sets meet the dynamic monitoring constraint conditions of the abnormal key equipment, and if so, the first dynamic monitoring key equipment is used as the temperature field dynamic monitoring scheme.

[0088] Through the above-mentioned detailed description of a distribution cabinet operation monitoring method in this specification, technical personnel in this field can clearly understand a distribution cabinet operation monitoring device in this embodiment. For the device disclosed in Example 2, since it corresponds to the method disclosed in Example 1 and has corresponding functional modules and beneficial effects, the relevant parts can be referred to the method part description.

[0089] Embodiment 3, based on the same inventive concept of a method for monitoring the operation of a distribution cabinet in the aforementioned embodiment 1, as Figure 4 As shown, the present application also provides a computer device, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the steps of the method described in any one of the above-mentioned embodiment one.

[0090] exist Figure 3 In the embodiment, the bus architecture is represented by bus 300, which may include any number of interconnected buses and bridges, and bus 300 connects various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same element, namely a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 may be used to store data used by processor 302 when performing operations.

[0091] In addition, the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned distribution cabinet operation monitoring method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0092] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring the operation of a power distribution cabinet, characterized in that: The method comprises: Perform long-term continuous monitoring of the target power distribution cabinet according to a preset electrical parameter set to obtain multiple monitoring electrical parameter sets; Traversing the plurality of monitoring electrical parameter sets to conduct a comprehensive analysis of the operation fluctuations of the power distribution cabinet and determine the operation fluctuation factor; Extracting multiple key devices of the target power distribution cabinet, performing long-term temperature monitoring on the multiple key devices, and obtaining multiple monitoring temperature sets; Analyzing the multiple monitoring temperature sets, and determining a dynamic temperature field monitoring scheme for the multiple key devices according to temperature fluctuations of different key devices; Matching an electrical parameter monitoring period of the target power distribution cabinet based on the operation fluctuation factor; Performing operation monitoring on the target power distribution cabinet according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring scheme; The plurality of monitoring electrical parameter sets are traversed to perform a comprehensive analysis of the operation fluctuation of the power distribution cabinet to determine the operation fluctuation factor, including: Calculating the fluctuation variances of the plurality of monitored electrical parameter sets respectively to obtain a plurality of fluctuation coefficients; Respectively dividing the plurality of fluctuation coefficients by the sum of the plurality of fluctuation coefficients, and multiplying the ratio by a preset search step length to obtain a plurality of parameter search step lengths; Performing parameter dense distribution screening on the multiple monitored electrical parameter sets based on the multiple parameter search step sizes to obtain multiple dense distribution parameter sets; Calculating the fluctuation variance of the plurality of densely distributed parameter sets, and performing mean calculation on the calculation results to obtain the operation fluctuation factor; Based on the analysis of the multiple monitoring temperature sets, according to the temperature fluctuations of different key devices, a dynamic temperature field monitoring scheme for the multiple key devices is determined, including: Performing fluctuation analysis on the plurality of monitored temperature sets to determine a plurality of temperature fluctuation coefficients; Screening the plurality of monitoring temperature sets according to the reference temperature tolerance interval to extract a plurality of super-interval monitoring temperature sets; Determine a plurality of temperature anomaly coefficients of the plurality of key devices based on the plurality of super-interval monitoring temperature sets; The temperature field dynamic monitoring scheme is determined based on the multiple temperature fluctuation coefficients and the multiple temperature anomaly coefficients.

2. A method for monitoring the operation of a power distribution cabinet according to claim 1, characterized in that: The preset electrical parameter set includes voltage, current, power, power factor and frequency.

3. A method for monitoring the operation of a power distribution cabinet according to claim 1, characterized in that: Based on the multiple parameter search steps, the multiple monitoring electrical parameter sets are screened for dense distribution of parameters to obtain multiple dense distribution parameter sets, including: Determine multiple electrical parameter means of the multiple monitored electrical parameter sets, use the multiple electrical parameter means as multiple screening starting circle centers, and use the multiple parameter search step lengths as radii to determine multiple starting densely distributed parameter sets, wherein the starting densely distributed parameters are monitored electrical parameters whose differences from an electrical parameter mean value are within the corresponding parameter search step length; Counting a plurality of initial screening quantities of the plurality of initial dense distribution parameter sets; Iterating the multiple screening starting circle centers in the multiple monitoring electrical parameter sets based on the multiple parameter search step sizes to determine multiple screening iteration circle centers and multiple iterative dense distribution parameter sets; The multiple iterative screening amounts of the multiple iterative densely distributed parameter sets are counted, and the sizes of the multiple iterative screening amounts and the multiple starting screening amounts are compared to determine whether to update the multiple screening starting circle centers. After multiple updates, until the screening is stopped, the multiple iterative densely distributed parameter sets corresponding to the maximum screening amount are used as multiple densely distributed parameter sets.

4. A method for monitoring the operation of a power distribution cabinet according to claim 3, characterized in that: When the screening amount difference between the multiple iterative screening amounts and the multiple initial screening amounts is less than or equal to the preset screening amount difference, the screening is stopped.

5. A method for monitoring the operation of a power distribution cabinet according to claim 1, characterized in that: Determining the temperature field dynamic monitoring scheme based on the multiple temperature fluctuation coefficients and the multiple temperature anomaly coefficients includes: determining a plurality of abnormal key devices based on the plurality of temperature fluctuation coefficients and the plurality of temperature anomaly coefficients; According to the number of the plurality of abnormal key devices and the plurality of key devices, an abnormal ratio is obtained, and based on the abnormal ratio, a dynamic monitoring constraint condition of the abnormal key devices is determined, wherein the dynamic monitoring constraint condition of the abnormal key devices is that the number of the abnormal key devices must be greater than or equal to the abnormal ratio during each dynamic monitoring; Randomly extract the multiple key devices according to the preset synchronous temperature monitoring device quantity to obtain multiple first dynamic monitoring key device sets; It is determined whether the plurality of first dynamic monitoring key equipment sets meet the abnormal key equipment dynamic monitoring constraint conditions. If so, the first dynamic monitoring key equipment is used as a temperature field dynamic monitoring solution.

6. A distribution cabinet operation monitoring device, characterized in that: The device is used to execute a method for monitoring the operation of a power distribution cabinet according to any one of claims 1 to 5, comprising: A continuous monitoring module, which is used to perform long-term continuous monitoring of the target power distribution cabinet according to a preset electrical parameter set to obtain multiple monitoring electrical parameter sets; A fluctuation analysis module, the fluctuation analysis module is used to traverse the multiple monitoring electrical parameter sets to perform a comprehensive analysis of the operation fluctuations of the distribution cabinet and determine the operation fluctuation factor; A temperature monitoring module, wherein the temperature monitoring module is used to extract multiple key devices of the target power distribution cabinet, perform long-term temperature monitoring on the multiple key devices, and obtain multiple monitoring temperature sets; A monitoring scheme determination module, the monitoring scheme determination module is used to analyze the multiple monitoring temperature sets and determine the temperature field dynamic monitoring scheme of the multiple key devices according to the temperature fluctuation of different key devices; A monitoring cycle matching module, the monitoring cycle matching module is used to match the electrical parameter monitoring cycle of the target power distribution cabinet based on the operation fluctuation factor; An operation monitoring module, wherein the operation monitoring module is used to perform operation monitoring on the target power distribution cabinet according to the electrical parameter monitoring cycle and the temperature field dynamic monitoring scheme.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of a method for monitoring the operation of a power distribution cabinet described in any one of claims 1-5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for monitoring the operation of a distribution cabinet as described in any one of claims 1 to 5 are implemented.

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