Electric service power supply management system based on remote monitoring

Abstract

The invention discloses an electric service power supply management system based on remote monitoring, and relates to the technical field of power supply monitoring management. The information acquisition module is used for acquiring information of power supply equipment to obtain equipment information; through the set health assessment method, the health condition of the target equipment can be assessed according to the operation information of the target equipment, the hidden fault is judged by analyzing and identifying the operation parameters of the target equipment to obtain the health condition, and before the health condition assessment process, the power supply equipment is classified, so that the power supply equipment is classified. The information of different target categories is stored in different information bases to improve the information processing efficiency, the discharge strategy of the target equipment is adjusted according to the health condition of the target equipment through a set strategy output method to obtain a target strategy, related equipment is processed in advance according to potential risks, and the risk of the related equipment is reduced. Therefore, the operation of the target equipment is optimized and adjusted, the service life of the target equipment is prolonged by managing the target equipment, and the risk of sudden power failure is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply monitoring and management, and in particular to an electric power supply management system based on remote monitoring. Background Art

[0002] Electrical power refers to the dedicated power supply used in railway or rail transit systems to ensure the normal operation of railway maintenance equipment such as electrical services, namely communications, signaling, and control. It usually includes DC power supply, backup power supply and distribution equipment. In order to ensure that critical communication and signaling equipment can operate stably in various operating and emergency situations, electrical power management is often required.

[0003] Patent publication number CN116707142A describes a railway signal power remote monitoring system based on wireless communication, comprising the following components: a remote control center, wireless communication base stations, power monitoring terminals, power supply monitoring nodes, and mobile shared terminals; the remote control center is used to receive monitoring data from each distributed monitoring terminal; the wireless communication base stations are used to receive and transmit communication connections between each terminal and the center; the power monitoring terminals are used to monitor the health status of the signal power in real time and control and adjust the signal power based on the monitoring results; the power supply monitoring nodes are used to monitor the signal equipment and transmission lines supplied by the signal power in real time; and the mobile shared terminals are used to provide communication services to operation and maintenance personnel. The present invention significantly improves the monitoring range and monitoring capabilities of the signal power through an intelligent monitoring system, thereby improving the accuracy of remote monitoring of the signal power.

[0004] Some power supply equipment in the substation may have "hidden faults" (such as intermittent voltage fluctuations and capacity decay in the early stages of battery aging). These faults are not easy to be captured in time, resulting in the system being normal on the surface but potential risks accumulating. The remote monitoring methods in the existing technology have the disadvantage of being unable to solve the accumulation of potential risks. During operation, the existing monitoring is difficult to analyze and identify changes in the health status of power supply equipment caused by hidden faults such as "life decay" and "performance edge degradation". It is not possible to handle related equipment in advance according to the accumulation of potential risks, which is not conducive to improving management efficiency. The lack of perception of the potential risk accumulation process leads to hidden dangers not being discovered and handled in time, and equipment maintenance still remains in the post-fault repair mode, missing the opportunity to intervene in advance, extend equipment life, and reduce the risk of sudden power outages. Therefore, the present invention is proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide an electric power management system based on remote monitoring to solve the problems raised in the above background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an electric power management system based on remote monitoring, comprising:

[0007] Information acquisition module: obtains information of the power supply device to obtain device information, obtains real-time operating parameters and past operating parameters of the power supply device to obtain real-time parameters and past parameters;

[0008] Information processing module: Based on the device information, the device is classified according to the usage scenario and type to obtain classification information. The classification information includes several target categories, and the target category includes the device information corresponding to the target category;

[0009] Data processing module: performs accuracy verification on real-time parameters under different target categories through verification methods to obtain verification parameters and difference items;

[0010] Data classification module: Based on the number of target categories, the same number of information libraries are established to store verification parameters and previous parameters;

[0011] Status assessment module: determines the device whose health status needs to be assessed to obtain the target device, selects the corresponding information library based on the target device to obtain the target library, evaluates the health status of the target device using the health assessment method based on the target device and the target library to obtain the assessment result, and establishes a directory table to store the target device and its assessment results;

[0012] Strategy formulation module: updates the discharge strategy of the target device through the strategy output method based on the catalog table to obtain the target strategy;

[0013] Policy output module: Feeds back the target policy to the target device, and the target device operates according to the target policy;

[0014] Feedback update module: Based on the information base, the information in the information base and the directory table is regularly iterated through the update method to obtain the updated information base and directory table.

[0015] Furthermore, the health assessment method includes: presetting target factors, establishing a health assessment range based on the target factors and target categories to obtain a health grade assessment standard, obtaining the life grade of the target equipment through a joint analysis method based on the health grade assessment standard, establishing the correlation between the life grade and the target equipment, and the life grade is the assessment result.

[0016] Furthermore, the process of establishing a health assessment range based on target factors and target categories to obtain a health grade assessment standard is as follows: determining the target factors, obtaining the normal working range information of the target factors to obtain the normal range information, the normal range information is the first life grade, presetting an added value, adding the added value to the normal range information to obtain the second life grade, adding the added value to the range information of the second life grade to obtain the third life grade, integrating the first life grade, the second life grade and the third life grade to obtain the target life grade, establishing an association between the target factors and the target life grade, and integrating all target factors, target life grades and associations to obtain a health grade assessment standard.

[0017] Furthermore, the joint analysis method includes: splitting the health level assessment standard to obtain several target factors, target life levels and correlation relationships, extracting the parameters corresponding to the target factors from the real-time parameters and past parameters of the target equipment to obtain real-time selected parameters and past selected parameters, when the real-time selected parameters and the past selected parameters are single, judging the inclusion relationship between the real-time selected parameters and the target life level to obtain the real-time life level, judging the inclusion relationship between the past selected parameters and the target life level to obtain the past life level, when the real-time selected parameters and the past selected parameters are multiple parameters, obtaining the real-time life level and the past life level through a deep division method based on the real-time selected parameters and the past selected parameters in combination with the target life level, obtaining the generation time difference of the real-time parameters and the past parameters to obtain the time difference, obtaining the life change trend based on the past life level, the real-time life level and the time difference, obtaining the life level of the target equipment based on the real-time life level, and integrating the life change trend and the life level to obtain the evaluation result.

[0018] Furthermore, the depth division method includes: assigning weights to target factors based on the impact of the target factors on the life of the target equipment to obtain target weights, judging the inclusion relationship between real-time selected parameters and target life levels to obtain several first sub-life levels, obtaining real-time life levels based on the target weights and several first sub-life levels, judging the inclusion relationship between previously selected parameters and the target life levels to obtain several second sub-life levels, and obtaining past life levels based on the target weights and several second sub-life levels.

[0019] Furthermore, the strategy output method includes: obtaining the work tasks of the target device to obtain task requirements, judging the number of target devices, when the number of target devices is multiple, extracting the evaluation results of the target devices in the catalog table to obtain the target life level, sorting the target devices from best to worst based on the target life level to obtain a sorting result, presetting the task threshold of the worst target device in the target life level, when the work tasks of the same target device exceed the task threshold, removing the task threshold from the task requirements of the worst-level target device and adding it to the optimal target device to obtain the target strategy of the target device, when the number of target devices is single and the target life level feedback of the target device is the worst level, extracting the task requirements, target devices and their target life levels to generate feedback information.

[0020] Furthermore, the verification method includes: determining the usage scenario of the real-time parameter to obtain the environmental parameter, judging whether there is a strong fluctuation in the environmental parameter to obtain a judgment result, presetting a verification threshold based on the judgment result and the equipment operation status, obtaining the change of the real-time parameter to obtain a change value, judging the size of the verification threshold and the change value to obtain a verification result, when the change value is greater than the verification threshold, the real-time parameter is a difference item, and when the change value is less than the verification threshold, the real-time parameter is a verification parameter.

[0021] Furthermore, the update method includes: presetting an update time point, re-evaluating the health status of the target device based on the update time point to obtain a re-evaluation result, overwriting the evaluation result in the catalog table based on the re-evaluation result to obtain an updated catalog table, and after the re-evaluation result of the target device is generated, presetting a time node, eliminating the previous parameters and real-time parameters in the information library before the time node to obtain an updated information library.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] This electric power management system based on remote monitoring can evaluate the health status of the target equipment according to the operating information of the target equipment through the set health assessment method, judge the hidden faults by analyzing and identifying the operating parameters of the target equipment to obtain the health status, and classify the power equipment before the health status assessment process. Information of different target categories is stored in different information databases to improve information processing efficiency. The discharge strategy of the target equipment is adjusted according to the health status of the target equipment through the set strategy output method to obtain the target strategy. The relevant equipment is processed in advance according to the potential risks to achieve the effect of optimizing and adjusting the operation of the target equipment. The target equipment is managed to extend the service life of the target equipment and reduce the risk of sudden power outages.

[0024] At the same time, the real-time parameters are verified through the set verification method to improve the accuracy of the real-time parameters obtained, and it is also helpful to judge whether the corresponding sensors are operating normally, so as to timely discover the sensors that produce errors and improve the overall operation efficiency. The number of information databases is consistent with the target category. A single information database only stores the verification parameters and previous parameters under one target category to improve the efficiency of subsequent data processing and the efficiency of health status assessment. Through the set joint analysis method, the target devices with single target factors and multiple target factors are processed separately to facilitate more accurate judgment of the health status of the target devices.

[0025] At the same time, through the set depth division method, when there are multiple target factors to grade the health status of the target device, the weighting method is adopted, and different weights are given to the target factors according to the degree of influence on the health status of the target device, so as to improve the accuracy of the evaluation. Through the set update method, the information in the information base and directory table can be iteratively updated in real time according to the update time point to improve the real-time nature of the information in the information base and directory table, reduce the processing volume of subsequent information search and information processing, improve the response speed of the system, and help improve the operating efficiency of the health assessment method. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the upper half structure of the present invention;

[0027] Figure 2 It is a schematic diagram of the lower half structure of the present invention;

[0028] Figure 3 Schematic diagram of the target library structure obtained in the present invention;

[0029] Figure 4 This is a schematic diagram of the health assessment level structure of the present invention. DETAILED DESCRIPTION

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0031] Electric power management is the process or system for monitoring, regulating, maintaining, and optimizing electric power. This includes monitoring power status, controlling power supply parameters, providing fault warnings, and performing maintenance scheduling. The goal is to ensure high power reliability and stability and reduce operational risks caused by failures. Railway signaling, communications, locomotives, and onboard equipment require stable power supply support. The electric power management system enables real-time monitoring and scheduling of substations, catenary power supplies, and battery packs through remote monitoring. Remote monitoring of the electric power system enables real-time collection of parameters such as power quality, battery voltage, and temperature within the substation, as well as fault warnings.

[0032] like Figure 1-Figure 4 As shown, the present invention provides a technical solution: an electric power management system based on remote monitoring, comprising:

[0033] Information acquisition module: obtains information of the power supply device to obtain device information, obtains real-time operating parameters and past operating parameters of the power supply device to obtain real-time parameters and past parameters;

[0034] It should be noted that device information includes device name information, device manual information and device application scenario information. The real-time operating parameters and past operating parameters of the power supply equipment are obtained through corresponding sensors. Specific parameters may include temperature, vibration, insulation resistance or leakage current, etc.

[0035] Information processing module: Based on the device information, the device is classified according to the usage scenario and type to obtain classification information. The classification information includes several target categories, and the target category includes the device information corresponding to the target category;

[0036] It should be noted that the devices are classified according to the specific working scenarios of the devices in the device information and the categories to which they belong. The target category is a specific name category that contains several pieces of device information. The category definition is the target category obtained by combining the specific usage scenario and the device category.

[0037] Example 1:

[0038] In the electrical power supply equipment used in the system, the power supply equipment information is obtained to obtain the equipment information. In the work log of the equipment information, the data of the monitoring equipment operation is obtained to obtain the real-time parameters and past parameters. The equipment is classified according to the usage scenario and type of the equipment, and several information libraries corresponding to the target categories are established to store the real-time parameters and past parameters generated under the target category. A node for sending and receiving information is established to obtain the user's address information, which includes but is not limited to email and telephone number, and the generated evaluation results and feedback information are fed back to the user through the node.

[0039] Data processing module: performs accuracy verification on real-time parameters under different target categories through verification methods to obtain verification parameters and difference items;

[0040] It should be noted that the real-time parameters are verified through the set verification method to improve the accuracy of the obtained real-time parameters. At the same time, it is helpful to determine whether the corresponding sensors are operating normally, facilitate timely detection of erroneous sensors, and improve overall operating efficiency.

[0041] Data classification module: Based on the number of target categories, the same number of information libraries are established to store verification parameters and previous parameters;

[0042] It should be noted that the number of information repositories is consistent with the target categories, and a single information repository only stores verification parameters and previous parameters under one target category to improve the efficiency of subsequent data processing and the efficiency of health status assessment.

[0043] Status assessment module: determines the device whose health status needs to be assessed to obtain the target device, selects the corresponding information library based on the target device to obtain the target library, evaluates the health status of the target device using the health assessment method based on the target device and the target library to obtain the assessment result, and establishes a directory table to store the target device and its assessment results;

[0044] It should be noted that the process of determining the device that needs to be evaluated for health status to obtain the target device is to determine the device that needs to be evaluated for health status according to the use requirements. Specifically, during the use process, the corresponding device can be determined by random selection or targeted selection to obtain the target device. The target device is the power supply device in the electric power supply. Based on the target device, the corresponding information library is selected to obtain the target library. Figure 3 As shown, the information library corresponds to the target category, that is, the target library is obtained by selecting the information library corresponding to the target category according to the target category of the target device. Through the set health assessment method, the health status of the target device can be assessed according to the operating information of the target device, so that the subsequent strategy output method can output the corresponding discharge strategy, so as to adjust the target device and achieve the effect of extending the service life of the target device.

[0045] Strategy formulation module: updates the discharge strategy of the target device through the strategy output method based on the catalog table to obtain the target strategy;

[0046] It should be noted that the target strategy is obtained by adjusting the discharge strategy of the target device according to the health status of the target device through the set strategy output method, so as to optimize and adjust the operation of the target device and manage the target device to extend the service life of the target device.

[0047] Policy output module: Feeds back the target policy to the target device, and the target device operates according to the target policy;

[0048] It should be noted that the process of feeding back the target strategy to the target device is to overwrite the original discharge strategy with the target strategy, and the target device operates according to the target strategy.

[0049] Feedback update module: Based on the information base, the information in the information base and the directory table is regularly iterated through the update method to obtain the updated information base and directory table.

[0050] It should be noted that by setting the update method, the information in the information base and directory table can be updated and iterated at a fixed time to achieve the purpose of streamlining the information base and target table, and improve the efficiency and accuracy of subsequent health status assessment and policy output.

[0051] like Figure 1 As shown, the health assessment method includes: presetting target factors, establishing a health assessment range based on the target factors and target categories to obtain a health grade assessment standard, obtaining the life grade of the target equipment through a joint analysis method based on the health grade assessment standard, establishing the correlation between the life grade and the target equipment, and the life grade is the assessment result.

[0052] It should be noted that the target factors are determined based on actual usage requirements. Specific target factors are operating data that can reflect the health status of the target equipment. Specific target factors include temperature, vibration, etc. More specifically, when the target equipment is a transformer, oil temperature can be selected as the target factor. Health level assessment standards are formulated based on the target factors and target categories. The life level of the target equipment is obtained through the set joint analysis method. The assessment results include the specific life level, target equipment, and correlation.

[0053] like Figure 4 As shown, the process of establishing a health assessment range based on target factors and target categories to obtain a health grade assessment standard is as follows: determining the target factors, obtaining the normal working range information of the target factors to obtain the normal range information, the normal range information is the first life grade, presetting an added value, adding the added value to the normal range information to obtain the second life grade, adding the added value to the range information of the second life grade to obtain the third life grade, integrating the first life grade, the second life grade and the third life grade to obtain the target life grade, establishing an association between the target factors and the target life grade, and integrating all target factors, target life grades and associations to obtain a health grade assessment standard.

[0054] It should be noted that determining the target factor is to determine a specific factor. For example, determine the oil temperature as the target factor, obtain the normal working range information of the target factor to obtain the normal range information, that is, obtain the target factor range information of the target factor in the target device under normal working conditions. The added value is determined according to actual use, and the specific unit changes with the change of the target factor. The specific set value is determined according to actual use. There are two boundary values ​​in the normal range information. The added value is added to one of the boundary values ​​in the normal range information to obtain the second life level with the boundary value, and so on. Figure 4 As shown, a single level life level in a specific health level assessment standard may include multiple types, such as the first life level, the second life level, the third life level, the fourth life level... the Nth life level, etc. The specific number is determined according to actual usage. The more precise the level life level division is, the more accurate the subsequent processing process will be.

[0055] Example 2:

[0056] More specifically, when the target device is a transformer, oil temperature (or winding temperature) can be selected as the target factor. Distribution transformers are commonly used power equipment in power systems. Common faults are often related to winding overheating, insulation aging, and abnormal oil temperature. Monitoring oil temperature or winding temperature is very effective for judging equipment health. Key single factor recommendation: oil temperature (or winding temperature). Oil temperature is an important indicator reflecting the internal operating status of the transformer. Continuously high oil temperature will accelerate the aging of insulation materials and shorten its life. Equipment manufacturers and industry standards usually give a safe operating range for oil temperature. Specific threshold design examples (refer to IEC standards and engineering experience). Oil temperature (℃) health status description: When the oil temperature is <65℃, it means that the normal equipment is operating stably and has a normal life. When the oil temperature is between 65℃ and 75℃, it means that the temperature has begun to rise and needs attention. When the oil temperature is between 75℃ and 85℃, it means sub-health and overtemperature and needs to be reduced or inspected. When the oil temperature is 85℃ When the oil temperature is between 95°C and 95°C, it indicates a high temperature alarm and may pose a hidden danger. When the oil temperature exceeds 95°C, it indicates a danger and the machine should be shut down immediately for processing. An example of a health status judgment rule is as follows: oil temperature < 65°C, healthy status = normal; 65°C ≤ oil temperature < 75°C, healthy status = slightly elevated; 75°C ≤ oil temperature < 85°C, healthy status = sub-healthy; 85°C ≤ oil temperature < 95°C, healthy status = warning; oil temperature > 95°C, healthy status = dangerous. Based on the above ranges, the corresponding first life level, second life level, third life level, fourth life level, and fifth life level can be generated. The specific acquisition method is through real-time monitoring, using oil temperature sensors to collect temperature data, and updating it in seconds or minutes. At the same time, the above thresholds can be adjusted according to the manufacturer's manual or historical operating data. Maintenance decisions can also be added: when the temperature reaches the "sub-healthy" level or above, an inspection or load reduction is arranged. When it exceeds the "warning" level, an alarm and emergency strategy are initiated.

[0057] The joint analysis method includes: splitting the health level assessment standard to obtain several target factors, target life levels and correlation relationships, extracting the parameters corresponding to the target factors from the real-time parameters and past parameters of the target equipment to obtain real-time selected parameters and past selected parameters, when there is a single parameter in the real-time selected parameters and the past selected parameters, judging the inclusion relationship between the real-time selected parameters and the target life level to obtain the real-time life level, judging the inclusion relationship between the past selected parameters and the target life level to obtain the past life level, when there are multiple parameters in the real-time selected parameters and the past selected parameters, obtaining the real-time life level and the past life level through a deep partitioning method based on the real-time selected parameters and the past selected parameters in combination with the target life level, obtaining the generation time difference of the real-time parameters and the past parameters to obtain the time difference, obtaining the life change trend based on the past life level, the real-time life level and the time difference, obtaining the life level of the target equipment based on the real-time life level, and integrating the life change trend and the life level to obtain the assessment result.

[0058] It should be noted that, through the set joint analysis method, the target devices for selecting a single target factor and multiple target factors are processed separately, so as to more accurately judge the health status of the target device. The process of determining the inclusion relationship between the real-time selected parameters and the target life level to obtain the real-time life level is to determine which level of life level the real-time selected parameters specifically meet in the target life level, that is, to determine the inclusion relationship between the real-time selected parameters and multiple levels in the target life level. When the real-time selected parameters are found, the real-time life level can be obtained. The life change trend indicator is used to determine the aging degree of the target device and reflect the changes in the health status of the target device from the interval time. Specifically, the real-time selected parameters generated by the target devices that are all operating under normal conditions can be selected for evaluation. When the real-time selected parameters are used for evaluation, the life change trend indicator is more accurate, which is beneficial to indirectly reflect whether the target device needs maintenance, achieve the effect of monitoring and managing the target device, and help extend the service life of the target device. The time difference is a specific value, which is the difference between the real-time parameter generation time and the previous parameter generation time.

[0059] The deep division method includes: assigning weights to target factors based on the impact of target factors on the life of target equipment to obtain target weights, judging the inclusion relationship between real-time selected parameters and target life levels to obtain several first sub-life levels, obtaining real-time life levels based on the target weights and several first sub-life levels, judging the inclusion relationship between previously selected parameters and target life levels to obtain several second sub-life levels, and obtaining previous life levels based on the target weights and several second sub-life levels.

[0060] It should be noted that, through the set depth division method, when there are multiple target factors to grade the health status of the target device, the weighting method is adopted. Different weights are assigned to the target factors according to the degree of influence of the health status of the target device. The specific weight assignment is determined according to the actual usage. Specifically, the degree of influence reflecting the health status of the target device can be ranked, and the corresponding weight is assigned according to the ranking. The specific weight value is determined by the degree of influence. The specific real-time life level and past life level are obtained by combining the level life levels of multiple target factors.

[0061] Example 3:

[0062] When there are two target factors, namely factor 1 and factor 2, factor 1: first life level (assuming the level value is 1), factor 2: second life level (assuming the level value is 2), they are weighted according to their impact on the health status of the target equipment, with weights of 0.7 and 0.3 respectively. The level value represents the quantitative index of the life level (the smaller the number, the better the life level, usually 1 is excellent and 2 is suboptimal). The final life level value is calculated according to the weighted average method: Lfinal = 0.7 × 1 + 0.3 × 2 = 0.7 + 0.6 =1.3Lfinal=0.7×1+0.3×2=0.7+0.6=1.3. Specifically, the life level is a discrete classification, with only integer levels 1, 2, 3..., and the result is obtained by directly rounding off as the first life level, or the division interval is set according to the definition. For example, the level interval corresponds to the life level, the value in [1,1.5) is level 1, the value in [1.5,2.5) is level 2, and the value in [2.5,3.5) is level 3. In this case, 1.3 falls in [1,1.5) and still belongs to the first life level.

[0063] like Figure 2 As shown, the strategy output method includes: obtaining the work tasks of the target device to obtain the task requirements, judging the number of target devices, when the number of target devices is multiple, extracting the evaluation results of the target devices in the catalog table to obtain the target life level, sorting the target devices from best to worst based on the target life levels to obtain the sorting results, presetting the task threshold of the worst target device in the target life level, when the work tasks of the same target device exceed the task threshold, removing the task threshold from the task requirements of the worst-level target device and adding it to the optimal target device to obtain the target strategy of the target device, when the number of target devices is single and the target life level feedback of the target device is the worst level, extracting the task requirements, the target device and its target life level to generate feedback information.

[0064] It should be noted that the process of obtaining the work tasks of the target equipment to obtain the task requirements can be obtained by obtaining the work needs of the target equipment, and the target strategy can be obtained by adjusting the corresponding discharge strategy of the target equipment according to the number of target devices through the set policy output method. Based on the target strategy, the workload of the target equipment with low health status can be reduced to extend the service life and stability of the target equipment with low health status, reduce the probability of sudden power outages caused by potential risk accumulation, and extend the power consumption experience. The task threshold is formulated according to the target equipment in the corresponding life level. The task threshold is a specific discharge work task, etc. By generating feedback information, the single target device with poor health status can be fed back to the user in time, reminding the user to deal with it in time, so as to improve the stability of the power supply.

[0065] Example 4:

[0066] Use the sorting to get the "good and bad" of the equipment life level. For equipment with a low life level (i.e., poor health and high risk), adjust the discharge strategy to slow down its loss; for "healthy" equipment, the discharge load can be appropriately increased to share the overall working pressure and extend the life of the early warning equipment; the goal is to intelligently distribute the load and discharge time to avoid overload and early retirement of low-life equipment and ensure power supply continuity; specific steps and operating instructions: clarify the life level according to the sorting, determine the current life level of each device (such as 1 is the best and 5 is the worst), classify and group the equipment into "high life group" (higher level) and "low life group" (lower level), and adjust the discharge parameters for the low-life group equipment: reduce the discharge depth, shorten the discharge time, and reduce the discharge power For long-life equipment, the discharge depth and time are appropriately increased. Dynamic load distribution dynamically adjusts the load distribution ratio based on the remaining life and health level. Monitoring feedback monitors device status in real time, dynamically adjusts the discharge plan, and provides maintenance warnings to plan maintenance or replacement for extremely low-life equipment in advance to avoid sudden power outages. Example of discharge strategy adjustment: Life level depth of discharge (DoD), discharge power, and discharge frequency. Levels 1-2 (healthy) fully utilize and share the load. Levels 3-4 (sub-healthy) reduce the load to protect the equipment and prevent further deterioration. Level 5 (dangerous) shallow discharge and low power to mitigate risks. A mapping table between life level and discharge parameters can be established to facilitate automatic program call. Discharge strategies can be adjusted based on environmental conditions (temperature, humidity, etc.) to improve applicability. Machine learning is used to optimize load distribution. Strategies are dynamically optimized based on device status and historical discharge impacts. Tier thresholds and event triggers are set, such as automatically switching discharge modes at the critical life level. This fully extends the effective use time of low-life equipment, reduces premature power outages caused by accelerated aging due to excessive discharge, distributes the load, improves overall system reliability and availability, and reduces maintenance and replacement costs.

[0067] like Figure 1 As shown, the verification method includes: determining the usage scenario of the real-time parameter to obtain the environmental parameter, judging whether there is a strong fluctuation in the environmental parameter to obtain a judgment result, presetting a verification threshold based on the judgment result and the equipment operation status, obtaining the change of the real-time parameter to obtain a change value, judging the size of the verification threshold and the change value to obtain a verification result, when the change value is greater than the verification threshold, the real-time parameter is a difference item, and when the change value is less than the verification threshold, the real-time parameter is a verification parameter.

[0068] It should be noted that the process of determining the usage scenario of the real-time parameters to obtain the environmental parameters is to obtain the environmental parameters of the sensor that generates the real-time parameters, and to determine whether there are strong fluctuations in the environmental parameters to obtain the judgment results. This process is to determine whether there are large fluctuations in the environmental parameters in the environment. The verification threshold is preset based on the judgment results and the equipment operation status. The verification threshold is preset based on whether there are large fluctuations in the environmental parameters fed back by the judgment results and the equipment operation status. The specific setting process determines whether there is a deviation in the sensor reading based on the environmental parameters. When there is a deviation, the deviation is accommodated and the normal value of the parameter during equipment operation is combined to obtain the verification threshold. The verification threshold is a range value. The verification threshold is used to determine whether the obtained real-time parameters are consistent with the actual situation. When the real-time parameters do not meet the verification threshold, it means that the acquisition of the real-time parameters is obviously inconsistent with the actual situation. By setting the verification method, the accuracy of data acquisition can be improved, thereby improving the assessment accuracy of the health assessment method.

[0069] like Figure 2 As shown, the update method includes: presetting an update time point, re-evaluating the health status of the target device based on the update time point to obtain a re-evaluation result, overwriting the evaluation result in the catalog table based on the re-evaluation result to obtain an updated catalog table, and after the re-evaluation result of the target device is generated, presetting a time node, eliminating the previous parameters and real-time parameters in the information library before the time node to obtain an updated information library.

[0070] It should be noted that, by setting the update method, the information in the information base and the directory table can be iteratively updated in real time according to the update time point, so as to improve the real-time nature of the information in the information base and the directory table, reduce the processing volume of subsequent information search and information processing, improve the response speed of the system, and help improve the operating efficiency of the health assessment method. The update time point is specific time information, which is determined according to actual usage. It can be set to update weekly or daily, etc.

[0071] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is limited by the accompanying embodiments and their equivalents.

Claims

1. An electric power management system based on remote monitoring, comprising: Information acquisition module: obtains information of the power supply device to obtain device information, obtains real-time operating parameters and past operating parameters of the power supply device to obtain real-time parameters and past parameters; Information processing module: Based on the device information, the device is classified according to the usage scenario and type to obtain classification information. The classification information includes several target categories, and the target category includes the device information corresponding to the target category; The invention is characterized by comprising: Data processing module: performs accuracy verification on real-time parameters under different target categories through verification methods to obtain verification parameters and difference items; Data classification module: Based on the number of target categories, the same number of information libraries are established to store verification parameters and previous parameters; Status assessment module: determines the device whose health status needs to be assessed to obtain the target device, selects the corresponding information library based on the target device to obtain the target library, evaluates the health status of the target device using the health assessment method based on the target device and the target library to obtain the assessment result, and establishes a directory table to store the target device and its assessment results; Strategy formulation module: updates the discharge strategy of the target device through the strategy output method based on the catalog table to obtain the target strategy; Policy output module: Feeds back the target policy to the target device, and the target device operates according to the target policy; Feedback update module: Based on the information base, the information in the information base and the directory table is regularly iterated through the update method to obtain the updated information base and directory table.

2. The remote monitoring-based power management system according to claim 1, characterized in that: The health assessment method includes: presetting target factors, establishing a health assessment range based on the target factors and target categories to obtain a health grade assessment standard, obtaining the life grade of the target equipment through a joint analysis method based on the health grade assessment standard, establishing the correlation between the life grade and the target equipment, and the life grade is the assessment result.

3. The remote monitoring-based power management system for electric services according to claim 2, characterized in that: The process of establishing a health assessment range based on target factors and target categories to obtain a health grade assessment standard is as follows: determining the target factors, obtaining the normal working range information of the target factors to obtain the normal range information, the normal range information is the first life grade, presetting an added value, adding the added value to the normal range information to obtain the second life grade, adding the added value to the range information of the second life grade to obtain the third life grade, integrating the first life grade, the second life grade and the third life grade to obtain the target life grade, establishing a correlation between the target factors and the target life grade, and integrating all target factors, target life grades and correlations to obtain the health grade assessment standard.

4. The remote monitoring-based power management system according to claim 2, characterized in that: The joint analysis method includes: splitting the health level assessment standard to obtain several target factors, target life levels and correlation relationships, extracting parameters corresponding to the target factors from the real-time parameters and past parameters of the target equipment to obtain real-time selected parameters and past selected parameters, when there is a single parameter in the real-time selected parameters and the past selected parameters, judging the inclusion relationship between the real-time selected parameters and the target life level to obtain the real-time life level, judging the inclusion relationship between the past selected parameters and the target life level to obtain the past life level, when there are multiple parameters in the real-time selected parameters and the past selected parameters, obtaining the real-time life level and the past life level through a deep partitioning method based on the real-time selected parameters and the past selected parameters in combination with the target life level, obtaining the generation time difference between the real-time parameters and the past parameters to obtain the time difference, obtaining the life change trend based on the past life level, the real-time life level and the time difference, obtaining the life level of the target equipment based on the real-time life level, and integrating the life change trend and the life level to obtain the assessment result.

5. The remote monitoring-based power management system for electric services according to claim 4, characterized in that: The depth division method includes: assigning weights to target factors based on the impact of the target factors on the life of the target equipment to obtain target weights, judging the inclusion relationship between real-time selected parameters and target life levels to obtain several first sub-life levels, obtaining real-time life levels based on the target weights and several first sub-life levels, judging the inclusion relationship between previously selected parameters and the target life level to obtain several second sub-life levels, and obtaining past life levels based on the target weights and several second sub-life levels.

6. The remote monitoring-based power management system for electric services according to claim 1, characterized in that: The strategy output method includes: obtaining the work tasks of the target device to obtain the task requirements, judging the number of target devices, when the number of target devices is multiple, extracting the evaluation results of the target devices in the catalog table to obtain the target life level, sorting the target devices from best to worst based on the target life levels to obtain the sorting results, presetting the task threshold of the worst target device in the target life level, when the work tasks of the same target device exceed the task threshold, removing the task threshold from the task requirements of the worst-level target device and adding it to the optimal target device to obtain the target strategy of the target device, when the number of target devices is single and the target life level feedback of the target device is the worst level, extracting the task requirements, the target device and its target life level to generate feedback information.

7. The remote monitoring-based power management system for electric services according to claim 1, characterized in that: The verification method includes: determining the usage scenario of the real-time parameter to obtain the environmental parameter, judging whether there is strong fluctuation in the environmental parameter to obtain a judgment result, presetting a verification threshold based on the judgment result and the equipment operation status, obtaining the change of the real-time parameter to obtain a change value, judging the size of the verification threshold and the change value to obtain a verification result, when the change value is greater than the verification threshold, the real-time parameter is a difference item, and when the change value is less than the verification threshold, the real-time parameter is a verification parameter.

8. The remote monitoring-based power management system for electric services according to claim 1, characterized in that: The update method includes: presetting an update time point, re-evaluating the health status of the target device based on the update time point to obtain a re-evaluation result, overwriting the evaluation result in the catalog table based on the re-evaluation result to obtain an updated catalog table, and after the re-evaluation result of the target device is generated, presetting a time node, eliminating previous parameters and real-time parameters in the information library located before the time node to obtain an updated information library.

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