Digital operation and maintenance method and system for power supply station, storage medium and program product

Abstract

The invention discloses a digital operation and maintenance method and system for a power supply station, a storage medium and a program product, and relates to the field of electric digital data processing. Determining an adjustment strategy of equipment operation parameters according to the meteorological level; reducing rated operation parameters and protection constant values of the equipment in different time periods according to the adjustment strategy; operating state parameters of the equipment are collected, and when it is detected that the operating state parameters exceed the adjusted rated operating parameters, the standby capacity is calculated; starting the standby equipment according to the standby capacity until the operation state parameters are reduced to be below the adjusted rated operation parameters; calculating a running state parameter difference value between the adjacent equipment, and determining a target adjusting quantity based on the running state parameter difference value when the running state parameter difference value exceeds a preset range; and adjusting the rated operation parameters of each device according to the target adjusting quantity, so that the difference value of the operation state parameters is maintained in a preset range. According to the invention, the operation reliability and the fault prediction accuracy of the power supply station equipment under the extreme weather condition are improved.

Description

Technical Field

[0001] The present application relates to the field of electrical digital data processing, and in particular to a digital operation and maintenance method, system, storage medium and program product for a power supply station. Background Art

[0002] With the rapid development of power systems and the advancement of smart grid construction, power stations, as a crucial distribution link in power systems, face a significant impact on the reliability and safety of power supply. Traditional power station maintenance relies primarily on manual inspections and record-keeping, which is not only inefficient but also prone to missed inspections and false positives, making it difficult to promptly identify and address equipment hazards. Furthermore, manually recorded data suffers from poor accuracy and difficulty in querying.

[0003] In related technologies, high-precision sensor networks can be deployed to collect equipment operation data in real time, combined with edge computing technology for data preprocessing and feature extraction, and deep learning algorithms can be used to establish equipment health status assessment models, thereby realizing intelligent identification of abnormal equipment conditions and accurate prediction of the probability of failure, greatly improving the intelligence level of power supply station operation and maintenance and the accuracy of fault warning.

[0004] However, under extreme weather conditions such as heavy rain and lightning, the system finds it difficult to quickly adapt to drastic fluctuations in equipment performance. The prediction accuracy of pre-trained fault prediction models drops significantly in such scenarios, and the system lacks a rapid response mechanism to short-term drastic changes in equipment performance caused by weather changes. This makes it difficult to adjust maintenance strategies and operating parameters in a timely manner when extreme weather occurs, increasing the risk of equipment failure and power outages. Summary of the Invention

[0005] The present application provides a digital operation and maintenance method, system, storage medium and program product for a power supply station, which are used to improve the operational reliability and fault prediction accuracy of power supply station equipment under extreme weather conditions.

[0006] In a first aspect, the present application provides a digital operation and maintenance method for a power supply station, which classifies the collected meteorological data within the power supply station area to obtain meteorological grade data, wherein the meteorological grade data includes a meteorological grade and a corresponding trigger threshold; Determine the adjustment strategy for equipment operating parameters based on the trigger threshold corresponding to the meteorological level; Reduce the rated operating parameters and protection settings of the equipment in different time periods according to the adjustment strategy. The rated operating parameters include rated voltage, rated current, and rated load. The protection settings include overcurrent protection settings, overvoltage protection settings, and temperature rise protection settings. Collecting the operating status parameters of the equipment, and calculating the spare capacity when it is detected that the operating status parameters exceed the adjusted rated operating parameters; Start the standby equipment according to the standby capacity until the operating parameters drop below the adjusted rated operating parameters; Calculating the difference in operating status parameters between adjacent devices, and when the difference in the operating status parameters exceeds a preset range, determining a target adjustment amount based on the difference in the operating status parameters; Adjust the rated operating parameters of each device according to the target adjustment amount so that the difference in operating status parameters remains within the preset range.

[0007] By adopting the above technical solution, a mechanism for associating meteorological conditions with equipment operating parameters is established by classifying meteorological data and setting trigger thresholds. On this basis, the rated operating parameters and protection settings of the equipment are reduced in different time periods according to the adjustment strategy, so that the equipment can maintain safe and stable operation under different meteorological conditions. When the equipment operating status parameters exceed the adjusted rated operating parameters, the system can promptly calculate the backup capacity and start the backup equipment to avoid overload operation of the equipment. By calculating the difference in operating status parameters between adjacent devices and dynamically adjusting them, the load distribution of each device is made more balanced, reducing equipment losses caused by load imbalance, and enabling the power supply station equipment to adaptively adjust its operating status according to the actual operating environment, thereby improving power supply reliability, reducing equipment failure rate, and increasing equipment service life and operating efficiency.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the meteorological data collected within the power supply station area is graded to obtain meteorological grade data, specifically including: Collect meteorological data within the power supply station area, including temperature, humidity, wind speed, precipitation, and lightning current density; Comparing the meteorological data with the preset equipment safety operation standard, when the data in the meteorological data exceeds the corresponding preset equipment safety operation standard, determining the influence coefficient of the corresponding data to be a first preset value, otherwise determining the influence coefficient of the data to be a second preset value; Determine the meteorological level according to the number of influence coefficients that are the first preset value, when the number of influence coefficients that are the first preset value is not greater than the first threshold, the meteorological level is a mild meteorological level, when the number of influence coefficients that are the first preset value is not greater than the second threshold and is greater than the first threshold, the meteorological level is a moderate meteorological level, and when the number of influence coefficients that are the first preset value is greater than the second threshold, the meteorological level is a severe meteorological level; The trigger threshold corresponding to each meteorological level is determined based on the historical equipment failure rate under each meteorological level.

[0009] By adopting the above technical solution, the impact coefficients of different meteorological factors are calculated by collecting multi-dimensional meteorological data such as temperature, humidity, wind speed, precipitation, and lightning current density, and comparing them with preset equipment safety operation standards. Based on the number of impact coefficients reaching the first preset value, meteorological conditions are divided into three levels: mild, moderate, and severe. The trigger threshold is determined based on historical equipment failure rates, accurately quantifying the impact of different meteorological factors on equipment operation and making the meteorological level classification more scientific and reasonable. At the same time, by analyzing historical failure data to determine the trigger threshold, the meteorological level is correlated with the actual equipment operation status, which can better prevent equipment failures caused by meteorological factors.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, determining an adjustment strategy for device operating parameters based on a trigger threshold corresponding to a weather level specifically includes: Determine the adjustment ratio of equipment operating parameters according to the trigger threshold in the meteorological level; Calculate the target operating parameter value and the corresponding protection setting value according to the adjustment ratio. The protection setting value includes the overcurrent protection setting value, the overvoltage protection setting value and the temperature rise protection setting value; Divide the adjustment process from the rated operating parameter value to the target operating parameter value into multiple time periods, and calculate the operating parameter adjustment amount in each time period; Generate an adjustment strategy for the equipment operating parameters, which includes the adjustment ratio for each time period, the target operating parameter value, the corresponding protection setting value, and the operating parameter adjustment amount.

[0011] By adopting the above technical solution, the adjustment ratio of the equipment operating parameters is determined based on the trigger threshold corresponding to the meteorological level. By calculating the target operating parameter value and the protection setting value, and dividing the adjustment process into multiple time periods, a complete adjustment strategy is generated, including the adjustment ratio, target parameter value, and adjustment amount for each time period. This gradual parameter adjustment method avoids the impact of sudden parameter changes on the equipment, allowing the equipment to smoothly transition to the new operating state. By synchronously adjusting the operating parameters and protection setting values, the safety of the equipment during the adjustment process is ensured, the reliability of the protection device is maintained, the stress-induced loss of the equipment is reduced, and the stability of the equipment adjustment process is improved.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, when it is detected that the operating state parameter exceeds the adjusted rated operating parameter, calculating the backup capacity specifically includes: The adjusted rated operating parameters are used as the upper limit of equipment operation; Calculate the difference between the operating status parameter and the upper limit of the equipment operation; Calculate the total capacity required for the current load based on the difference; Calculate the actual available capacity of the currently running equipment; The difference between the total capacity and the actual available capacity is determined as the spare capacity.

[0013] By adopting this technical solution, the adjusted rated operating parameters are used as the upper limit for equipment operation. The difference between the operating status parameters and the upper limit is calculated, and the required total capacity is calculated in combination with the current load demand. The backup capacity is then determined by comparing it with the actual available capacity, making the timing of backup equipment activation more accurate. By calculating load demand and available capacity in real time, the system can promptly identify insufficient equipment capacity and ensure that backup equipment is put into operation at the most appropriate time, avoiding equipment overload or excessive backup capacity allocation, and improving the efficiency and reliability of the power supply system.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, when the difference in the operating state parameter exceeds a preset range, determining the target adjustment amount based on the difference in the operating state parameter specifically includes: Calculate the deviation based on the difference in operating status parameters and the adjustment ratio; The product of the deviation amount and the adjusted rated operating parameter is determined as the target adjustment amount.

[0015] By adopting this technical solution, the deviation is calculated by combining the difference in operating parameters and the adjustment ratio. The target adjustment value is then multiplied by the deviation and the adjusted rated operating parameters. This accurately quantifies the degree of imbalance in the operating conditions of adjacent devices. The introduction of the target adjustment value provides specific numerical guidance for the precise adjustment of device operating parameters, avoiding over- or under-adjustment. The system can promptly respond to changes in device operating conditions, promote balanced load distribution across devices, reduce local overloads caused by uneven load distribution between devices, and improve the overall operational stability and reliability of the power supply system.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after adjusting the rated operating parameters of each device according to the target adjustment amount so that the difference in the operating status parameters is maintained within a preset range, the method further includes: Calculate the difference in runtime between adjacent devices; Count the temperature rise rate and load fluctuation range of each device; Determine the equipment switching timing based on the difference in operating time, temperature rise rate, and load fluctuation amplitude; When a device switching opportunity is detected, the corresponding device is marked as a device to be switched; The equipment to be switched is operated in rotation according to the spare capacity.

[0017] By employing this technical solution, the system calculates the difference in operating time between adjacent devices and determines the timing of device switching based on the temperature rise rate and load fluctuation. This allows the system to comprehensively assess the operating status of devices from multiple dimensions. When the system detects a switching opportunity, it marks the corresponding device as a candidate for switching and, in conjunction with spare capacity, rotates the device to prevent prolonged high-load operation and reduce the risk of excessive wear. By rationally allocating device operating time, the system achieves dynamic load balancing, extending the device's service life while improving the efficiency and reliability of the power supply system.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, rotating the devices to be switched according to the spare capacity specifically includes: Record the cumulative operating time and fault occurrence period of the equipment to be switched; Calculate the load utilization rate corresponding to the fault occurrence period; Calculate the equipment wear coefficient based on the accumulated operating time and load utilization; Prioritize the devices to be switched based on the wear coefficient; A rotation operation schedule is generated according to the priority sorting and spare capacity, and rotation operation is performed according to the rotation operation schedule. The rotation operation schedule includes a switching time point, a switching sequence and a transition adjustment parameter.

[0019] By adopting the above technical solution, the cumulative operating time and fault occurrence period of the equipment to be switched are recorded, and the load utilization rate corresponding to the fault occurrence period is calculated, thereby calculating the equipment wear coefficient. Based on the wear coefficient, the equipment to be switched is prioritized, and a rotation operation schedule containing switching time points, switching sequences, and transition adjustment parameters is generated based on the priority ranking and spare capacity. This enables the system to perform orderly equipment rotation, making the equipment usage intensity more balanced, avoiding the problem of accelerated aging of individual equipment due to excessive use, achieving a reasonable distribution of equipment load, improving equipment usage efficiency, reducing maintenance costs, and ensuring the long-term stable operation of the power supply system.

[0020] In the second aspect, an embodiment of the present application provides a digital operation and maintenance system for a power supply station, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions, which, when executed on a system, enables the system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer program product, which, when executed on a system, enables the system to execute the method described in any possible implementation manner in the first aspect.

[0023] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. The present application provides a digital operation and maintenance method for power supply stations. By classifying meteorological data and setting trigger thresholds, a mechanism for associating meteorological conditions with equipment operating parameters is established. On this basis, the rated operating parameters and protection settings of the equipment are reduced in different time periods according to the adjustment strategy, so that the equipment can maintain safe and stable operation under different meteorological conditions. When the equipment operating status parameters exceed the adjusted rated operating parameters, the system can calculate the backup capacity and start the backup equipment in time to avoid overload operation of the equipment. By calculating the difference in operating status parameters between adjacent devices and dynamically adjusting them, the load distribution of each device is made more balanced, reducing equipment losses caused by load imbalance, and enabling the power supply station equipment to adaptively adjust its operating status according to the actual operating environment, thereby improving power supply reliability, reducing equipment failure rate, and improving equipment service life and operating efficiency.

[0024] 2. This application provides a digital operation and maintenance method for power supply stations. By calculating the difference in operating time between adjacent devices and combining the temperature rise change rate and load fluctuation amplitude to determine the equipment switching timing, the system can comprehensively evaluate the operating status of the equipment from multiple dimensions. When the system detects the switching timing, it marks the corresponding equipment as a device to be switched, and rotates it in combination with the spare capacity. This can prevent the equipment from being in a high-load operating state for a long time and reduce the risk of excessive wear of the equipment. By reasonably allocating the equipment operating time, the system achieves a dynamic balance of the equipment load, extends the service life of the equipment, and improves the operating efficiency and reliability of the power supply system.

[0025] 3. This application provides a digital operation and maintenance method for a power supply station, which records the cumulative operating time and fault occurrence period of the equipment to be switched, and calculates the load utilization rate corresponding to the fault occurrence period, thereby calculating the equipment wear coefficient. The equipment to be switched is prioritized based on the wear coefficient, and a rotation operation schedule containing switching time points, switching sequences, and transition adjustment parameters is generated according to the priority ranking and spare capacity, so that the system can perform orderly equipment rotation, which can make the equipment usage intensity more balanced, avoid the problem of accelerated aging of individual equipment due to excessive use, realize the reasonable distribution of equipment load, improve the equipment utilization efficiency, reduce maintenance costs, and ensure the long-term stable operation of the power supply system. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a digital operation and maintenance method for a power supply station in an embodiment of the present application.

[0027] Figure 2 It is a flow chart of a rotation operation method based on the operating status of the equipment in an embodiment of the present application.

[0028] Figure 3 This is a schematic diagram of the physical device structure of a digital operation and maintenance system for a power supply station provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and appended claims of this application, the singular expressions "a," "an," "said," "above," "the," and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in this application refers to any or all possible combinations comprising one or more of the listed items.

[0030] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0031] The following uses an embodiment and combines Figure 1 , a digital operation and maintenance method for a power supply station in an embodiment of the present application is described: See also Figure 1 , which is a flow chart of a digital operation and maintenance method for a power station in an embodiment of the present application.

[0032] S101, classifying the collected meteorological data within the power supply station area; The system classifies the meteorological data collected in the power supply station area into grades to obtain meteorological grade data, which includes meteorological grades and corresponding trigger thresholds. Specifically: meteorological data in the power supply station area is collected, and the meteorological data includes temperature, humidity, wind speed, precipitation and lightning current density data; the meteorological data is compared with the preset equipment safety operation standards. When the data in the meteorological data exceeds the corresponding preset equipment safety operation standards, the influence coefficient of the corresponding data is determined to be the first preset value, otherwise the influence coefficient of the data is determined to be the second preset value; the meteorological grade is determined according to the number of influence coefficients with the first preset value. When the number of influence coefficients with the first preset value is not greater than the first threshold, the meteorological grade is a mild meteorological grade. When the number of influence coefficients with the first preset value is not greater than the second threshold and is greater than the first threshold, the meteorological grade is a moderate meteorological grade. When the number of influence coefficients with the first preset value is greater than the second threshold, the meteorological grade is a severe meteorological grade. The trigger threshold corresponding to each meteorological grade is determined according to the historical equipment failure rate under each meteorological grade.

[0033] This step analyzes and classifies the meteorological data collected within the power station area. The system can collect multi-dimensional meteorological data such as temperature, humidity, wind speed, precipitation, and lightning current density in the power station area in real time through various meteorological monitoring equipment and sensors. After obtaining the meteorological data, the system compares the meteorological data with the preset equipment safety operation standards to determine whether the various meteorological parameters exceed the threshold range for normal operation of the equipment. Meteorological parameters that exceed the threshold can be assigned a higher impact coefficient, while those that do not exceed the threshold can be assigned a lower impact coefficient. The system can also set multiple impact coefficient levels to more finely assess the impact of meteorological conditions.

[0034] Based on the impact coefficients of meteorological parameters, the system can classify weather conditions into different levels, such as mild, moderate, and severe. Each level corresponds to a certain range of impact coefficient thresholds. Furthermore, the system analyzes historical data to calculate the probability of equipment failure under each weather level. This determines the trigger threshold for each weather level. When weather conditions reach that level, equipment failure is likely, requiring timely adjustment of operating parameters.

[0035] S102. Determine an adjustment strategy for equipment operating parameters based on a trigger threshold corresponding to the weather level; The system determines the adjustment strategy of the equipment operating parameters according to the trigger threshold corresponding to the meteorological level. Specifically: the adjustment ratio of the equipment operating parameters is determined according to the trigger threshold in the meteorological level; the target operating parameter value and the corresponding protection setting are calculated according to the adjustment ratio, and the protection setting includes the overcurrent protection setting, the overvoltage protection setting and the temperature rise protection setting; the adjustment process from the rated operating parameter value to the target operating parameter value is divided into multiple time periods, and the operating parameter adjustment amount in each time period is calculated; the adjustment strategy of the equipment operating parameters is generated, and the adjustment strategy includes the adjustment ratio of each time period, the target operating parameter value and the corresponding protection setting and operating parameter adjustment amount.

[0036] This step develops a strategy for adjusting device operating parameters based on the weather level and trigger thresholds determined in the previous step. Based on the potential impact of different weather levels, the system needs to reduce device operating loads to mitigate failure risks. The trigger thresholds serve as a basis for determining whether to initiate adjustments.

[0037] The system establishes a mapping table between weather levels and adjustment ratios for equipment operating parameters. The adjustment ratios are then calculated based on the current weather level. The target operating parameter values are then calculated by multiplying the equipment's rated voltage, current, load, and other operating parameters by the adjustment ratios. Simultaneously, the thresholds for overcurrent, overvoltage, and temperature rise protection settings must be adjusted accordingly to match the reduced operating level.

[0038] Considering the potential risks associated with sudden changes in equipment operating parameters, the system can adopt a gradual adjustment strategy. This involves dividing the adjustment process into multiple time periods, adjusting the parameters by a specific amount within each period. Ultimately, the target value is reached through multiple small adjustments. The system must plan the parameter adjustments for each time period. The adjustment strategy must clearly define the timing, the phased adjustment ratios, the target parameter values, and the corresponding protection settings.

[0039] S103. Reduce the rated operating parameters and protection settings of the equipment in different time periods according to the adjustment strategy; The system reduces the rated operating parameters and protection settings of the equipment in different time periods according to the adjustment strategy. The rated operating parameters include rated voltage, rated current and rated load, and the protection settings include overcurrent protection settings, overvoltage protection settings and temperature rise protection settings.

[0040] This step implements the device operating parameter adjustment strategy developed in the previous step. The system must strictly follow the schedule and adjustment range specified in the adjustment strategy, gradually reducing key operating parameters such as the device's rated voltage, rated current, and rated load. Simultaneously, the trigger thresholds for protections such as overcurrent, overvoltage, and temperature rise are adjusted accordingly. This ensures that while operating intensity is reduced, protective actions are commensurate with the reduction, preventing premature or late triggering and rendering the system ineffective.

[0041] Parameter writing and protection setting value modification can be accomplished remotely through the device's communication interface or a fieldbus gateway. To ensure controllability during the adjustment process, the system also monitors the operating status of each device in real time, obtains the current value of each parameter, compares it with the target value of the adjustment strategy, and monitors the adjustment progress. It can also fine-tune the strategy if necessary.

[0042] The entire adjustment process must adhere to certain rules, such as the adjustment sequence for different types of equipment, coordination between related devices, and the rationality of adjustment frequency and step size. For example, for multiple transformers in a cascade relationship, the adjustment sequence must be from top to bottom, with the voltage level on the upstream side lowered first. The generators and transformers within the unit must also be adjusted in sync to avoid mismatches that can lead to overloads and other problems.

[0043] S104, collecting operating status parameters of the equipment, and calculating the backup capacity when it is detected that the operating status parameters exceed the adjusted rated operating parameters; The system collects the operating status parameters of the equipment. When it detects that the operating status parameters exceed the adjusted rated operating parameters, it calculates the spare capacity. Specifically: the adjusted rated operating parameters are used as the upper limit of the equipment operation; the difference between the operating status parameters and the upper limit of the equipment operation is calculated; the total capacity required for the current load is calculated based on the difference; the actual available capacity of the currently operating equipment is calculated; and the difference between the total capacity and the actual available capacity is determined as the spare capacity.

[0044] This step involves monitoring the actual operating status of the equipment after adjusting its operating parameters, determining whether it is overloaded, and then determining the required backup capacity. The system continuously collects the equipment's real-time operating parameters, including voltage, current, active power, and reactive power, through telemetry or IoT devices. The measured operating parameters are compared with the adjusted rated limits to determine if any are exceeded. If the actual operating parameters exceed the adjusted rated values, this indicates that the current load has exceeded the equipment's derated transmission capacity, necessitating the deployment of backup equipment.

[0045] The system needs to calculate the required reserve capacity. The difference between the measured operating parameters and the adjusted rated values can be used as the excess load to estimate the total capacity required for the current load. Furthermore, the system needs to understand the actual available capacity of the currently operating equipment—that is, the maximum power that equipment such as transformers and lines can actually deliver, taking into account the adjusted rated values. The difference between the two phases represents the required backup capacity from the reserve equipment.

[0046] S105, starting the standby equipment according to the standby capacity until the operating state parameters drop below the adjusted rated operating parameters; This step involves activating backup equipment based on the calculated required reserve capacity to support equipment that has exceeded its adjusted rating, restoring it to a safe operating level. The system selects the appropriate transformers, generators, and lines from the backup equipment resource pool based on the required reserve capacity and issues a start-up command to bring them into operation.

[0047] The integration of backup equipment requires coordination with the primary equipment. For example, when a backup line is connected in parallel with the primary line, its reactive power output must be controlled and its power factor adjusted to ensure a reasonable reactive power distribution with the primary line, rather than simply adding active power. The system also needs to select the backup equipment's integration method and operating point based on the different types of parameters exceeding the rated values of the primary equipment, precisely meeting the capacity gap requirements of the primary equipment.

[0048] As backup equipment continues to be added, operating parameters should gradually decline. The system monitors the changing trends of each device's operating parameters in real time. When it observes a steady decline below the adjusted rated value, it can determine that the backup capacity has met demand and cease adding backup equipment. At the same time, the system can also consider decommissioning previously added backup equipment that is no longer needed to optimize backup resource allocation and improve utilization efficiency.

[0049] S106, calculating the difference in operating status parameters between adjacent devices, and when the difference in operating status parameters exceeds a preset range, determining a target adjustment amount based on the difference in operating status parameters; The system calculates the difference in operating status parameters between adjacent devices. When the difference in operating status parameters exceeds a preset range, the target adjustment amount is determined based on the difference in operating status parameters. Specifically: the deviation amount is calculated based on the difference in operating status parameters and the adjustment ratio; the product of the deviation amount and the adjusted rated operating parameter is determined as the target adjustment amount.

[0050] This step involves comparing and analyzing the operating parameters of adjacent devices to assess their compatibility and determine whether their operating levels need to be adjusted accordingly. In complex power grids, adjacent devices often interact with each other in terms of power flow, voltage, and load. Excessive parameter differences between adjacent devices can cause one device on one side to exceed its normal operating range, increasing the risk of failure. Therefore, it is necessary to calculate the parameter differences between adjacent devices in real time to determine whether they are within the acceptable range.

[0051] The system can pre-set reasonable ranges for the differences in various device parameters, such as bus voltage difference, active power difference between adjacent lines, and current load matching of associated transformers. Only when the actual operating parameter difference exceeds the preset range is a significant mismatch between devices considered, requiring adjustment of device parameters to eliminate it.

[0052] The magnitude of the adjustment can be calculated based on two factors: the parameter difference and the adjustment ratio. A larger difference indicates a larger adjustment, while the adjustment ratio reflects the direction and sensitivity of the parameter change. Statistical analysis of historical data can establish a correspondence between various parameter differences and adjustment ratios. When a parameter difference occurs, a table is used to determine the corresponding adjustment ratio, which is then multiplied by the difference to determine the absolute magnitude of the adjustment. This adjustment serves as the basis for executing subsequent control commands.

[0053] S107. Adjust the rated operating parameters of each device according to the target adjustment amount so that the difference in the operating status parameters is maintained within a preset range.

[0054] This step applies the device parameter adjustments calculated in the previous step to restore the matching of operating parameters between adjacent devices to a reasonable level. The system adjusts key operating parameters of the devices accordingly, adjusting them based on the value and direction of the adjustments. These adjustments can include rated voltage, rated current, active power, reactive power, and other parameters. The specific parameters to be adjusted depend on the primary issues and influencing mechanisms of the mismatch.

[0055] Device parameter adjustments are achieved by issuing control commands to the device via a fieldbus gateway or communication protocol interface. To ensure a smooth adjustment process and avoid secondary failures caused by drastic parameter fluctuations, the system can adopt a gradual adjustment strategy, spreading the entire adjustment over a period of time and issuing only small adjustments at a time. After the device completes the adjustment, the system needs to obtain feedback on the device's execution of the adjustment command, remeasure the operating parameter difference, verify the adjustment results, and perform the next round of parameter fine-tuning as needed.

[0056] Through multiple rounds of adjustments, the differences in the operating parameters of adjacent devices are continuously converged and eventually stabilized within a preset reasonable range, achieving the control goal of device parameter matching. This process may require iterative optimization over multiple control cycles.

[0057] Furthermore, during parameter adjustment, multiple devices may experience simultaneous mismatches. The system must prioritize adjustments for each device to prevent cross-adjustments from compromising control effectiveness. For example, for substations connected by a single line, priority should be given to adjusting the bus voltage of the substation closest to the power source to minimize mismatches. By rationally adjusting device parameters, consistent device operating conditions and overall grid balance can be achieved.

[0058] In the above embodiment, by classifying meteorological data and setting trigger thresholds, a mechanism for associating meteorological conditions with equipment operating parameters is established. On this basis, the rated operating parameters and protection settings of the equipment are reduced in different time periods according to the adjustment strategy, so that the equipment can maintain safe and stable operation under different meteorological conditions. When the equipment operating status parameters exceed the adjusted rated operating parameters, the system can calculate the backup capacity and start the backup equipment in a timely manner to avoid overload operation of the equipment. By calculating the difference in operating status parameters between adjacent devices and dynamically adjusting them, the load distribution of each device is made more balanced, reducing equipment losses caused by load imbalance, and enabling the power supply equipment to adaptively adjust its operating status according to the actual operating environment, thereby improving power supply reliability, reducing equipment failure rate, and improving equipment service life and operating efficiency.

[0059] The above embodiment realizes the intelligent operation and maintenance of power supply equipment by means of meteorological data classification, operating parameter adjustment and standby equipment startup. In order to further improve the reliability and economy of equipment operation, the present application also provides a rotation operation method based on the equipment operation status. This method establishes a scientific equipment switching mechanism by monitoring key parameters such as equipment operation time, temperature rise and load fluctuation, and realizes the balanced distribution of equipment load and effective extension of service life. Figure 2 , a rotation operation method based on the operating status of the device in an embodiment of the present application is described: See also Figure 2 , which is a flow chart of a rotation operation method based on the operating status of the equipment in an embodiment of the present application.

[0060] S201, calculating the difference in operating time between adjacent devices; This step is the process of comparing the cumulative operating time of adjacent devices to evaluate whether there are significant differences in their usage intensity and degree of wear. In actual power station operation, multiple devices with the same function are often put into use in turn, but due to factors such as scheduling strategies and fault conditions, the actual operating time of each device may not be balanced. If individual devices are in an overtime service state for a long time, their reliability and remaining life will be affected, which is not conducive to the safe and economic operation of the entire equipment. Therefore, it is necessary to collect real-time statistics on the operating time data of the equipment and calculate the operating time difference between key devices as one of the bases for determining whether to switch equipment.

[0061] The system can obtain equipment operating time data in a variety of ways. One method is to directly read the accumulated operating hours using the equipment's own operating recorder. Another method is to set up an operating clock in the equipment operating status monitoring system to record the equipment's start and stop times, then add up the operating hours to obtain the total operating time. Furthermore, for equipment that has undergone maintenance or status changes, it is necessary to review maintenance records and deduct any downtime to ensure the accuracy of the operating time data.

[0062] For critical primary devices, the system can incorporate the runtime data of each backup device when calculating runtime differentials, taking into account the switchover frequency and cumulative runtime differences between the primary and backup devices. This helps balance backup device utilization efficiency and balance when making rotational decisions.

[0063] S202, calculating the temperature rise change rate and load fluctuation amplitude of each device; This step analyzes the changing characteristics of key parameters during equipment operation to assess the degree of operating condition deterioration and load adaptability. Equipment temperature rise and load fluctuations are key factors affecting reliability and service life. Excessive temperature rise degrades insulation performance, while severe load fluctuations can cause overvoltage and mechanical stress. The combined effects of these factors accelerate insulation aging and mechanical wear, posing a threat to equipment safety. Therefore, it is necessary to conduct long-term tracking and statistical analysis of temperature rise and load fluctuations for each device to understand their patterns and impact, providing data support for determining switching timing.

[0064] The system uses online monitoring devices to collect real-time characteristic parameters such as the equipment's top oil temperature, core temperature, and winding temperature. Using time series analysis methods such as sliding average and ARIMA, the rate of change of the equipment's temperature rise—the average level of temperature increase per unit time—can be calculated. This metric directly reflects the rate of decline in the equipment's heat dissipation capacity. The system also analyzes the causes of temperature changes and the equipment's inherent thermal stability margin, taking into account operating parameters such as ambient temperature, load current, and air cooling system.

[0065] To assess the level of load fluctuation experienced by equipment, the system can perform statistical analysis on load monitoring variables such as current and active power, generating key indicators such as load variation frequency, peak-to-valley difference, and rate of change. These indicators reflect the impact of load fluctuations on equipment. The system can also incorporate spectrum analysis to examine the energy distribution of the load across different frequency components, further characterizing the dynamic characteristics of the load.

[0066] S203, determining the equipment switching timing according to the difference in operating time, the temperature rise rate, and the load fluctuation amplitude; This step comprehensively considers the equipment's operating time, temperature rise characteristics, and load fluctuations to assess its overall health and determine the optimal timing for rotational operation. Single indicators like operating time, temperature rise, and load alone are insufficient to fully reflect the equipment's status. Only through integrated analysis can we accurately determine whether a device urgently needs a rotation. The system requires a scientific multi-parameter fusion mechanism, assigning appropriate weights to each indicator to form a comprehensive evaluation model for equipment status.

[0067] In specific implementation, the system must first non-dimensionalize each indicator to eliminate differences in numerical magnitude. Common data normalization methods such as range normalization and Z-score can be used. Furthermore, multi-metric decision-making methods such as weighted averaging, PCA, and fuzzy comprehensive evaluation can be used to integrate each indicator into a comprehensive health index. A higher index indicates a more urgent need for device replacement.

[0068] Considering the importance of the rationality of indicator weights to evaluation results, the system can employ methods such as the Analytic Hierarchy Process (AHP) and the Entropy Weight Method to dynamically adjust weight parameters based on the strength of associations and the degree of conflict between indicators. Machine learning algorithms can also be used to mine association rules from massive amounts of historical operational data and adaptively determine the importance of each parameter.

[0069] Based on an assessment of the overall health of the device, the system further determines a specific time window for device switching. A health index threshold can be set; when a device's index falls below this value, it is considered urgent for the device to switch. Setting this threshold requires a balance between device reliability and switching costs. A high threshold can lead to frequent switching, while a low threshold can cause the device to exceed its service life. Furthermore, the switching time must take into account the coordination of device status to avoid excessive spare capacity usage caused by multiple devices switching simultaneously.

[0070] S204: When a device switching opportunity is detected, the corresponding device is marked as a device to be switched; This step involves preparing for a switchover after the system determines that a device meets the switchover conditions. The system separates the devices eligible for switchover from the currently running set of devices, creating a list of devices to be switched, which serves as an index for subsequent switchover operations. Device switchover marking is a prerequisite for device rotation and requires adherence to a strict workflow to ensure traceability of switchover instructions and consistency of device status.

[0071] In practice, the system adds a switch flag status bit to each device in the device database. Once a device's overall health index falls below the switch threshold, its switch flag is set to true, and the device ID, switch time, and other information are recorded in the pending switch list.

[0072] Once a device is marked as ready for switching, the system needs to take a series of supporting measures, such as suspending non-essential control actions, strengthening equipment parameter monitoring, and confirming the readiness of backup equipment, to clear obstacles for a smooth switch.

[0073] It's worth noting that due to the dispersion of field devices and the complexity of communication, the process of changing a device's handover flag may result in anomalies such as signal delays and command mismatches. To ensure consistency between the flag state and the device's physical state, the system synchronizes and verifies handover signaling through mechanisms such as time verification and CRC. A time window is set for flag confirmation. If a device's readiness confirmation is not received within this window, the flag is considered a failure, and the handover process must be reinitiated.

[0074] If the health level of the device to be switched reverses after being marked and re-exceeds the switching threshold, the system can temporarily suspend the switching process for that device. However, this recurrence should be recorded, the cause analyzed, and any blind spots or shortcomings in the decision-making mechanism reviewed. Avoid frequent changes in markings that could cause repeated starts and stops of the device.

[0075] S205: Rotate the equipment to be switched according to the spare capacity.

[0076] The system rotates the equipment to be switched according to the spare capacity, specifically including: recording the cumulative operating time and fault occurrence period of the equipment to be switched; counting the load utilization rate corresponding to the fault occurrence period; calculating the equipment wear coefficient based on the cumulative operating time and load utilization rate; prioritizing the equipment to be switched based on the wear coefficient; generating a rotation operation schedule based on the priority ranking and spare capacity, and performing rotation operation according to the rotation operation schedule, which includes switching time points, switching sequences and transition adjustment parameters.

[0077] During implementation, the system first needs to record the cumulative operating time and historical fault conditions of each device to be switched. This data can be collected through the device's own sensors and monitoring systems, or obtained from production management systems such as MES and ERP. The time, frequency, and duration of the faults must be recorded in detail. Furthermore, to assess the load intensity borne by the equipment at the time of the fault, data such as process parameters and output during the fault period must be collected to calculate the load utilization rate.

[0078] Next, the system needs to calculate the wear coefficient of each device based on the above data to quantify the current health level of the device. The wear coefficient calculation formula is as follows: W = a × T + b × L Where W represents the wear coefficient, T represents the cumulative operating time, L represents the load utilization rate, and a and b are weight coefficients. This formula accounts for the impact of both operating time and load intensity on equipment wear. Weight coefficients a and b can be pre-set based on factors such as equipment type, material, and historical experience, or can be fitted from historical data using algorithms such as machine learning. The cumulative operating time T can be directly calculated by accumulating operating records.

[0079] With each device's wear coefficient, the system can prioritize all devices to be replaced. A higher wear coefficient indicates a device has been operating longer or is under higher load, posing a greater risk to continued use and should be replaced first. Therefore, devices can be prioritized for replacement simply by wear coefficient, from highest to lowest. Of course, if a device exhibits other signs of failure, such as abnormal temperature or vibration parameters, its priority should also be increased.

[0080] Finally, the system needs to comprehensively consider equipment priorities and actual production needs to develop a switching schedule. The switching schedule should include the time point of each switch, the order of switching in and out of equipment, and the transition adjustment parameters during the switching process. Among them, the determination of the switching time point needs to consider factors such as the startup time of the backup equipment and the safety margin of the switching process to avoid production interruptions or quality fluctuations. The switching sequence needs to take into account the processing capacity of the backup equipment based on the equipment priority to ensure that the total production capacity after the switch meets the production indicators. The transition adjustment parameters are designed to ensure the continuity of process parameters before and after the switch, such as the gradual change rate of temperature, pressure, flow, etc., to reduce product quality and equipment loss. These adjustment parameters can be preset according to the process flow and equipment characteristics, or they can be obtained through simulation optimization or field experience summary.

[0081] It's important to note that during the actual switchover, the system should also monitor equipment operating status and product quality in real time, dynamically optimizing and adjusting the switchover plan based on this feedback. For example, if a backup device experiences an anomaly after the switchover, it may be necessary to prematurely terminate its operation and activate the next device. If production indicators fluctuate significantly, the switchover schedule may need to be slowed down or transition parameters adjusted. This requires a certain degree of flexibility and real-time optimization capabilities in the rotational operation schedule to adapt to complex and changing production environments.

[0082] In the above embodiment, by calculating the difference in operating time between adjacent devices and combining the temperature rise rate and load fluctuation amplitude to determine the device switching timing, the system can comprehensively evaluate the device's operating status from multiple dimensions. When the system detects the switching opportunity, it marks the corresponding device as a device to be switched and rotates it in conjunction with spare capacity. This prevents the device from operating at high load for a long time and reduces the risk of excessive wear. By rationally allocating device operating time, the system achieves dynamic balance of device loads, extending the device's service life while improving the operating efficiency and reliability of the power supply system.

[0083] The following describes the system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the physical device structure of a digital operation and maintenance system for a power supply station provided in an embodiment of the present application.

[0084] It should be noted that Figure 3 The structure of the system shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0085] like Figure 3 As shown, the system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes, such as the methods described in the above embodiments, based on programs stored in a read-only memory (ROM) 302 or programs loaded from a storage unit 308 into a random access memory (RAM) 303. RAM 303 also stores various programs and data required for system operation. CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to bus 304.

[0086] The following components are connected to the I / O interface 305: an input section 306 including a camera, infrared sensor, and the like; an output section 307 including a liquid crystal display (LCD) and speakers; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is installed in the drive 310 as needed, so that computer programs read from the media can be installed in the storage section 308 as needed.

[0087] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 309 and / or installed from removable media 311. When executed by the central processing unit (CPU) 301, the computer program performs the various functions defined in the present invention.

[0088] It should be noted that the computer-readable medium described in the embodiments of the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium may include a data signal transmitted in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take any of a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0089] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0090] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the system described in the above embodiments, or may exist independently and not incorporated into the system. The storage medium carries one or more computer programs, and when executed by a processor of a system, the system implements the methods provided in the above embodiments.

[0091] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0092] As used in the above embodiments, the term “when…” may be interpreted as “if…” or “after…” or “in response to determining…” or “in response to detecting…”, depending on the context. Similarly, the phrases “upon determining…” or “if (stated condition or event) is detected” may be interpreted as “if determining…” or “in response to determining…” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0093] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, hard disk, tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive).

[0094] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A digital operation and maintenance method for a power supply station, characterized in that: include: Classifying the collected meteorological data within the power supply station area to obtain meteorological grade data, wherein the meteorological grade data includes a meteorological grade and a corresponding trigger threshold; Determining an adjustment strategy for equipment operating parameters based on a trigger threshold corresponding to the meteorological level; According to the adjustment strategy, the rated operating parameters and protection settings of the equipment are reduced in different time periods, wherein the rated operating parameters include the rated voltage, rated current and rated load, and the protection settings include the overcurrent protection setting, the overvoltage protection setting and the temperature rise protection setting; collecting operating status parameters of the equipment, and calculating the standby capacity when it is detected that the operating status parameters exceed the adjusted rated operating parameters; starting the standby equipment according to the standby capacity until the operating state parameter drops below the adjusted rated operating parameter; Calculating a difference in operating state parameters between adjacent devices, and determining a target adjustment amount based on the difference in operating state parameters when the difference in operating state parameters exceeds a preset range; The rated operating parameters of each of the devices are adjusted according to the target adjustment amount so that the difference in the operating status parameters is maintained within the preset range.

2. The method according to claim 1, characterized in that The meteorological data collected in the power supply station area is classified into different levels to obtain meteorological level data, specifically including: Collect meteorological data within the power supply station area, including temperature, humidity, wind speed, precipitation, and lightning current density data; Comparing the meteorological data with a preset equipment safety operation standard, and when data in the meteorological data exceeds the corresponding preset equipment safety operation standard, determining the influence coefficient of the corresponding data to be a first preset value; otherwise, determining the influence coefficient of the data to be a second preset value; Determining a meteorological level according to the number of the influence coefficients being the first preset value, when the number of the influence coefficients being the first preset value is not greater than a first threshold, the meteorological level is a mild meteorological level; when the number of the influence coefficients being the first preset value is not greater than a second threshold and is greater than the first threshold, the meteorological level is a moderate meteorological level; when the number of the influence coefficients being the first preset value is greater than the second threshold, the meteorological level is a severe meteorological level; The trigger threshold corresponding to each meteorological level is determined according to the historical equipment failure rate under each meteorological level.

3. The method according to claim 1, characterized in that The determining of an adjustment strategy for equipment operating parameters according to a trigger threshold corresponding to the weather level specifically includes: determining an adjustment ratio of an equipment operating parameter according to a trigger threshold in the meteorological level; Calculate the target operating parameter value and the corresponding protection setting value according to the adjustment ratio, wherein the protection setting value includes an overcurrent protection setting value, an overvoltage protection setting value, and a temperature rise protection setting value; Dividing the adjustment process from the rated operating parameter value to the target operating parameter value into a plurality of time periods, and calculating the operating parameter adjustment amount in each of the time periods; An adjustment strategy for the equipment operating parameters is generated, wherein the adjustment strategy includes the adjustment ratio for each of the time periods, the target operating parameter value and the corresponding protection setting and the operating parameter adjustment amount.

4. The method according to claim 1, wherein When it is detected that the operating state parameter exceeds the adjusted rated operating parameter, calculating the backup capacity specifically includes: The adjusted rated operating parameters are used as the upper limit of equipment operation; Calculating the difference between the operating state parameter and the upper limit of the equipment operation; Calculating the total capacity required by the current load based on the difference; Calculate the actual available capacity of the currently running equipment; The difference between the total capacity and the actual available capacity is determined as the spare capacity.

5. The method according to claim 1, wherein When the difference in the operating state parameter exceeds a preset range, determining a target adjustment amount based on the difference in the operating state parameter specifically includes: Calculating a deviation amount according to the operating state parameter difference and the adjustment ratio; A product of the deviation and the adjusted setpoint operating parameter is determined as a target manipulated variable.

6. The method according to claim 1, characterized in that After adjusting the rated operating parameters of each of the devices according to the target adjustment amount so that the difference in the operating status parameters is maintained within the preset range, the method further includes: Calculating the difference in operating time between adjacent devices; Counting the temperature rise rate and load fluctuation amplitude of each of the equipment; Determining a device switching timing based on the operating time difference, the temperature rise rate, and the load fluctuation amplitude; When the device switching opportunity is detected, the corresponding device is marked as a device to be switched; The devices to be switched are operated in rotation according to the spare capacity.

7. The method according to claim 6, characterized in that The rotating operation of the devices to be switched according to the spare capacity specifically includes: Record the cumulative operating time and fault occurrence period of the device to be switched; Counting the load utilization rate corresponding to the fault occurrence period; Calculating a device wear coefficient based on the accumulated operating time and the load utilization rate; Prioritizing the devices to be switched based on the wear coefficients; A rotation operation schedule is generated according to the priority ranking and the spare capacity, and rotation operation is performed according to the rotation operation schedule. The rotation operation schedule includes a switching time point, a switching sequence, and a transition adjustment parameter.

8. A digital operation and maintenance system for a power supply station, characterized in that: The system comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the system to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a system, the system is caused to perform the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a system, the system is caused to perform the method according to any one of claims 1 to 7.

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