Station power supply safety evaluation method and device

Abstract

The invention discloses a station power supply safety evaluation method and device, and the method comprises the steps: building a safety evaluation benchmark through collecting voltage and current parameters, protection device configuration information and a switchgear operation period, recognizing an insulation degradation hidden danger region based on the safety evaluation benchmark, and carrying out the cumulative impact evaluation to generate a risk level distribution diagram; performing time sequence verification on the configuration information of the protection device and the operation period of the switch equipment to generate a protection matching margin; carrying out hidden danger correlation analysis on the risk level distribution map and the protection cooperation allowance to determine an evaluation key node, and constructing a grading evaluation index set according to redundancy configuration adequacy; dividing the grading evaluation index set into a real-time detection index and a period detection index, tracking the degradation trend of the period detection index, and feeding back a degradation offset coefficient to the real-time detection index to realize self-adaptive adjustment; and determining an evaluation execution area according to the risk partitions, identifying critical risk nodes through critical state detection, generating a station power supply safety evaluation report, and providing decision support for operation and maintenance management.

Description

Technical Field

[0001] This invention relates to the field of power system operation and maintenance technology, and in particular to a method and device for evaluating the safety of station power supplies. Background Technology

[0002] The substation auxiliary power supply system plays a crucial role in supplying power to relay protection, monitoring equipment, and communication devices. Its operational reliability directly affects the safe and stable operation of the substation. The auxiliary power supply involves various types of equipment, including auxiliary transformers, low-voltage distribution cabinets, feeder circuits, protection devices, and switchgear. These devices are electrically connected and have protection coordination relationships. An abnormality in any link may trigger a cascading failure.

[0003] The existing operation and maintenance management methods for station power supplies have the following shortcomings: First, equipment condition monitoring and protection configuration verification are independent of each other, making it difficult to detect the compound risks caused by the superposition of insulation aging and improper coordination of protection levels; second, the testing standards use fixed thresholds, which cannot be dynamically adjusted according to the equipment deterioration trend, making it difficult to detect some slowly deteriorating hidden dangers in a timely manner; third, the evaluation scope and testing frequency lack specificity, with the same testing strategy used for high-risk and low-risk areas, resulting in unreasonable allocation of testing resources. Therefore, a method is urgently needed to solve at least one of the above problems. Summary of the Invention

[0004] This invention discloses a method and device for safety evaluation of station power supplies. It aims to comprehensively collect the operating parameters and protection configuration information of station power supplies, establish a correlation evaluation benchmark between equipment status and protection coordination, conduct a comprehensive and accurate joint assessment of insulation degradation hazards and protection coordination margins, reveal the intrinsic relationship between risk level and redundancy configuration, and ultimately form a dynamic evaluation mechanism of adaptive adjustment and zoned execution, providing comprehensive and reliable decision support for station power supply operation and maintenance management and hazard prevention.

[0005] The first aspect of this invention proposes a method for evaluating the safety of station power supplies, comprising the following steps: The data acquisition station uses power supply voltage and current parameters, protection device configuration information, and switching equipment operation cycles to correlate and match the voltage and current parameters with the protection device configuration information to construct a safety evaluation benchmark. The safety assessment benchmark identifies areas with potential insulation degradation, and the cumulative impact of these areas is assessed to generate a risk level distribution map. The configuration information of the protection device is then time-sequentially verified with the operating cycle of the switchgear to generate a protection coordination margin. A hazard correlation analysis is performed on the risk level distribution map and the protection coordination margin to determine the key evaluation nodes. Based on the key evaluation nodes, the redundancy configuration adequacy is evaluated to generate redundancy levels. A graded evaluation index set is constructed based on the redundancy levels. The graded evaluation index set is divided into real-time detection indexes and periodic detection indexes according to detection priority. The degradation trend of the periodic detection index is tracked to obtain the degradation offset coefficient. The degradation offset coefficient is fed back to the real-time detection index for threshold correction to generate adaptive detection indexes. Evaluation coordination parameters are generated according to the collaborative configuration of the adaptive detection indexes and the periodic detection indexes. Based on the evaluation collaboration parameters and the risk level distribution map, the evaluation execution area is determined, critical state detection is performed in the evaluation execution area to identify critical risk nodes, and a station power supply safety evaluation report is generated based on the critical risk nodes.

[0006] A second aspect of the present invention provides a station power supply safety evaluation device, comprising: The data acquisition module is used to collect the voltage and current parameters of the power supply, the configuration information of the protection device, and the operation cycle of the switching equipment. It also associates and matches the voltage and current parameters with the configuration information of the protection device to construct a safety evaluation benchmark. The risk identification module is used to identify areas with potential insulation degradation hazards through the safety evaluation benchmark, perform cumulative impact assessment on the areas with potential insulation degradation hazards to generate a risk level distribution map, and perform time-series verification between the protection device configuration information and the operation cycle of the switchgear to generate protection coordination margin. The indicator construction module is used to perform hidden danger correlation analysis on the risk level distribution map and the protection coordination margin to determine the key evaluation nodes, evaluate the redundancy configuration adequacy based on the key evaluation nodes to generate redundancy levels, and construct a graded evaluation indicator set according to the redundancy levels. An adaptive correction module is used to distinguish the graded evaluation index set according to the detection priority to generate real-time detection indexes and periodic detection indexes, track the degradation trend of the periodic detection indexes to obtain degradation offset coefficients, feed the degradation offset coefficients back to the real-time detection indexes for threshold correction to generate adaptive detection indexes, and generate evaluation coordination parameters based on the collaborative configuration of the adaptive detection indexes and the periodic detection indexes. The report generation module is used to determine the evaluation execution area based on the evaluation collaboration parameters and the risk level distribution map, perform critical state detection in the evaluation execution area to identify critical risk nodes, and generate a station power supply safety evaluation report based on the critical risk nodes.

[0007] The beneficial effects of this invention are reflected in the following points: First, by establishing a safety evaluation benchmark through correlation and matching of voltage and current parameters with protection device configuration information, and based on this benchmark, identifying potential areas of insulation degradation and verifying the protection level coordination status to generate protection coordination margins, an organic combination of equipment status monitoring and protection configuration verification is achieved. This enables the discovery of compound risks formed by the superposition of insulation degradation and improper protection coordination, improving the comprehensiveness of risk identification. Second, by superimposing and analyzing the risk level distribution map and protection coordination margins, key evaluation nodes are determined. The redundancy level of each node is assessed based on the redundancy of the power supply path and the redundancy of the protection configuration. Based on this, a hierarchical evaluation index set is constructed to configure differentiated evaluation indicators for nodes with different redundancy levels. This allows high-risk nodes with insufficient redundancy to be subject to stricter testing standards, achieving a rational allocation of evaluation resources. Finally, by tracking historical data of periodic detection indicators, the degradation acceleration trend is identified, the degradation trend is quantified into a degradation offset coefficient, and fed back to the real-time detection indicators for threshold correction to generate adaptive detection indicators. Based on the adaptive detection indicators and periodic detection indicators, evaluation coordination parameters are generated, enabling the detection standards to adaptively adjust with changes in equipment status. Based on the evaluation coordination parameters and risk level distribution map, the evaluation execution area is determined, and critical state detection is performed to identify critical risk nodes. This allows for timely warnings and generation of station power supply safety evaluation reports when the equipment status approaches the threshold, improving the timeliness of hazard discovery. Attached Figure Description

[0008] The accompanying drawings illustrate specific examples of the technical solutions described in this invention and, together with the detailed embodiments, form part of the specification, serving to explain the technical solutions, principles, and effects of this invention.

[0009] Figure 1 This is a flowchart illustrating a method for evaluating the safety of station power supplies according to the present invention.

[0010] Figure 2 This is a structural block diagram of a station power supply safety evaluation device according to the present invention. Detailed Implementation

[0011] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0012] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0013] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0014] The technical solutions of the embodiments of this application are described below.

[0015] like Figure 1 As shown, this embodiment of the invention provides a method for evaluating the safety of station power supplies, including the following steps S110-S150: In step S110, the data acquisition station uses power supply voltage and current parameters, protection device configuration information, and switching equipment operation cycle to correlate and match the voltage and current parameters with the protection device configuration information to construct a safety evaluation benchmark.

[0016] Specifically, the system collects station power supply voltage and current parameters, protection device configuration information, and switching equipment operation cycles. A power quality monitoring terminal is installed on the low-voltage side of the station transformer. This terminal collects real-time RMS values ​​of three-phase voltage and current, voltage harmonic content, and power factor, with a sampling frequency set to once per second. Voltage and current parameters include A-phase voltage, B-phase voltage, C-phase voltage, A-phase current, B-phase current, C-phase current, harmonic components, and the rated voltage of the station transformer. When the station load changes, the voltage and current parameters exhibit corresponding fluctuations. Voltage deviations within ±7% of the rated voltage are considered normal fluctuations; deviations exceeding this range are marked as abnormal fluctuations in the voltage and current parameters. The system reads the setting values ​​and configuration parameters of each protection device within the station via a communication interface. Protection device configuration information includes overcurrent protection setting current, instantaneous overcurrent protection setting current, overcurrent protection operating time limit, and instantaneous overcurrent protection operating time limit. The overcurrent protection action time limit of the low-voltage side protection device of the main transformer is usually set to 0.5 seconds, and the overcurrent protection action time limit of the feeder protection device is set to 0.3 seconds. The time limit parameters in the protection device configuration information are set according to the principle of upper and lower level coordination. The setting parameters of each feeder protection device are stored separately in the protection device configuration information according to the protection type. The operation time and operation type of each circuit breaker in the station are recorded. The operation cycle of the switching equipment includes the opening and closing times of the circuit breaker. The typical opening time of the circuit breaker is 40-60 milliseconds, and the closing time is 60-80 milliseconds. The operation time and duration of each circuit breaker are recorded in the switching equipment operation cycle in chronological order. The switching equipment operation cycle is stored in the form of a timestamp and operation type lookup table. At the same time, the topology information of the station power supply is read. The topology information includes the correspondence between each monitoring point and physical equipment and the single-line diagram of the station power supply. The single-line diagram stores the topology location and connection relationship of each device in graphical data format.

[0017] A safety evaluation benchmark is constructed by correlating and matching voltage and current parameters with protection device configuration information. The effective values ​​of the three-phase voltages in the voltage and current parameters are compared with the rated voltages, and the voltage deviation percentage of each phase is calculated as ΔU = (U_actual - U_rated) / U_rated × 100%, where U_actual is the actual voltage and U_rated is the rated voltage. The effective values ​​of the three-phase currents in the voltage and current parameters are compared with the overcurrent protection setting current in the protection device configuration information, and the current margin coefficient K_I = I_set / I_actual is calculated, where K_I is the current margin coefficient, I_set is the overcurrent protection setting current in the protection device configuration information, and I_actual is the actual operating current in the voltage and current parameters. When K_I is less than 1.3, the protection margin is considered insufficient; when K_I is between 1.3 and 2.0, the protection margin is considered normal; and when K_I is greater than 2.0, the protection margin is considered sufficient. Simultaneously, the instantaneous overcurrent protection capability is verified by referring to the instantaneous overcurrent protection setting current in the protection device configuration information. The allowable range of voltage deviation percentage, the grading standard of current margin coefficient, and the instantaneous overcurrent protection margin are integrated into a safety evaluation benchmark. The safety evaluation benchmark stores each evaluation indicator and its corresponding threshold range in tabular form. In the safety evaluation benchmark, the voltage deviation limit is set to ±7%, the insufficient current margin threshold is set to 1.3, and the sufficient current margin threshold is set to 2.0.

[0018] Step S120: Identify potential insulation degradation areas through safety assessment benchmarks, conduct cumulative impact assessments on potential insulation degradation areas to generate risk level distribution maps, and perform timing verification between protection device configuration information and switchgear operation cycles to generate protection coordination margins.

[0019] In some embodiments, identifying potential insulation degradation areas using the safety assessment benchmark includes: generating abnormal fluctuation features by detecting abnormal fluctuations based on the safety assessment benchmark; determining suspected degradation areas by statistically analyzing the duration of the abnormal fluctuation features; generating degradation classification identifiers by assessing the degradation rate of the suspected degradation areas; and locating potential insulation degradation areas using the degradation classification identifiers.

[0020] Abnormal fluctuation characteristics are generated based on safety assessment benchmarks. The real-time voltage values ​​at each monitoring point of the substation power supply are compared with the voltage deviation limit of ±7% in the safety assessment benchmark. When the real-time voltage deviates from the rated voltage by more than the limit specified in the safety assessment benchmark, the voltage deviation amplitude and the time of occurrence are recorded. For example, in a substation, the No. 2 feeder experienced increased ground leakage current due to insulation aging at the cable joint. The safety assessment benchmark detected that the feeder voltage frequently deviated from the rated value during peak load periods. The real-time current values ​​at each monitoring point are compared with the current margin threshold of 1.3 in the safety assessment benchmark. When the current margin coefficient is lower than the specified threshold, the current exceedance amplitude and the time of occurrence are recorded. The number of abnormal occurrences, peak abnormal amplitude, and abnormal fluctuation frequency at each monitoring point within the detection period are statistically analyzed. The abnormal fluctuation frequency is the number of abnormal occurrences per unit time. In the past 4 hours, the No. 2 feeder experienced 12 voltage exceedances due to insulation deterioration, with an abnormal fluctuation frequency of 3 times / hour, far exceeding the normal feeder frequency of 0.5 times / hour. The number of anomalies, peak values ​​of anomalies, frequency of anomalies, and corresponding time information of each monitoring point are integrated into anomaly fluctuation characteristics. The anomaly fluctuation characteristics record the values ​​of each anomaly indicator using the monitoring point number as an index. Monitoring points with more than 5 anomalies or peak values ​​of anomalies exceeding the threshold by 30% are marked as key monitoring targets.

[0021] The duration of abnormal fluctuations was statistically analyzed to identify areas suspected of degradation. For each monitoring point marked as a key area of ​​concern in the abnormal fluctuation characteristics, the duration of its abnormal state was statistically analyzed. When the abnormal state of a monitoring point in the abnormal fluctuation characteristics lasted for more than 30 minutes, the duration of that monitoring point was added to the list of suspected degradation. For example, the abnormal voltage state of feeder No. 2 lasted from 10:25 AM to 11:15 AM, a continuous 50 minutes, and did not return to normal during this period. On-site infrared thermography revealed that the temperature of the cable joint of this feeder was significantly higher than that of adjacent joints, initially indicating that the joint insulation aging led to increased contact resistance. The frequency variation trend of abnormal fluctuations at each monitoring point in the abnormal fluctuation characteristics was analyzed. When the abnormal fluctuation frequency showed an increasing trend and the growth rate exceeded 10% / hour, even if the duration did not reach 30 minutes, the monitoring point was added to the list of suspected degradation. This situation usually corresponds to an early sign of accelerated aging of the insulation material. In a switchgear, the insulator's abnormal frequency in the abnormal fluctuation characteristics continuously increased due to moisture absorption during the rainy season. Monitoring points whose duration exceeds the threshold and monitoring points with increasing abnormal frequency are merged and deduplicated to form a suspected degradation area. The suspected degradation area includes the monitoring point number of each suspected point, the duration of the abnormality and the corresponding time series data of the abnormal amplitude. The suspected points in the suspected degradation area are sorted from longest to shortest abnormal duration to facilitate the determination of the treatment priority.

[0022] Degradation rate assessment is performed on suspected deterioration areas to generate degradation classification labels. For each suspected point in the suspected degradation area, the rate of change of its abnormal amplitude over time is calculated. The time-series data of the abnormal amplitude of each suspected point in the suspected degradation area over the past 24 hours are read, and a linear regression method is used to fit the trend line of the abnormal amplitude change; the slope of the trend line is the degradation rate. When the degradation rate of a suspected point in the suspected degradation area is greater than 0.5% / hour, it is judged as rapid degradation and marked as level one. This situation usually corresponds to a precursor to serious faults such as cable joint breakdown or busbar insulator flashover. For example, after a thunderstorm, water ingress was found in a feeder cable joint at a substation; the degradation rate of this joint in the suspected degradation area rose sharply to 0.8% / hour, which was judged as level one degradation and required immediate power outage. When the degradation rate is between 0.1% and 0.5% / hour, it is judged as slow degradation and marked as level two. This usually corresponds to natural aging of the insulation material or slight moisture absorption. A cable that has been in operation for more than 15 years has a stable degradation rate of 0.2% / hour due to natural aging of the insulation layer. When the degradation rate is less than 0.1% / hour, it is judged as a stable anomaly and marked as level three. The degradation rate values ​​and corresponding degradation levels of each suspected point in the suspected degradation area are integrated into a degradation classification identifier. The degradation classification identifier records the degradation rate and degradation level using the suspected point number as an index. Level one degradation points must be dealt with within 24 hours, level two degradation points must be dealt with within 72 hours, and level three degradation points are included in the regular inspection plan.

[0023] Areas with potential insulation degradation are located using degradation grading markers. Suspected points with degradation levels of 1 and 2 are screened from the degradation grading markers, as these areas correspond to areas with a clear risk of insulation degradation. The monitoring point numbers of the 1 and 2 degradation points in the degradation grading markers are read, and their physical locations within the station power supply topology are queried based on these numbers. A degradation point with the number "1-LV-CB3" in the degradation grading markers corresponds to the location of the cable joint at the outlet of feeder circuit breaker No. 3 on the low-voltage side of station transformer No. 1. The physical location information of each degradation point in the degradation grading markers is correlated with its degradation level and degradation rate. A degradation point located at a cable joint is considered a joint degradation; a degradation point located at a busbar connection is considered a busbar degradation; and a degradation point located inside a switchgear is considered internal cabinet degradation. "1-LV-CB3" was confirmed as a cable joint degradation upon on-site inspection, with slight discharge marks visible on the joint's exterior. The physical location, type, level, and rate of each deterioration point are summarized to form an insulation deterioration hazard area. The insulation deterioration hazard area is grouped and stored according to the deterioration level. The first-level deterioration points in the insulation deterioration hazard area are grouped separately and placed at the top of the list so that maintenance personnel can prioritize their repair.

[0024] A cumulative impact assessment is conducted on areas with potential insulation degradation to generate a risk level distribution map. For each degradation point in the potential insulation degradation area, its impact range on adjacent equipment and power supply circuits is calculated. The impact range of a rapid degradation point in the potential insulation degradation area is set to all feeder circuits of the busbar section where that point is located. In a certain substation, due to the continuous ambient humidity exceeding 85% during the rainy season, condensation appeared on the surface of the busbar post insulators on the low-voltage side of the No. 1 station service transformer, accompanied by a slight discharge sound. This rapid degradation point is located in the middle section of the busbar and may affect the power supply safety of all 8 feeders supplied by this busbar. The impact range of a slow degradation point in the potential insulation degradation area is set to the single feeder circuit where that point is located. The cumulative risk value R_cum is calculated for each affected area as follows: R_cum = Σ(V_i × T_i × W_i), where V_i is the degradation rate of the i-th degradation point (in % / hour), T_i is the duration (in hours), and W_i is a weighting coefficient (dimensionless). Rapid degradation points have a weight of 1.5, and slow degradation points have a weight of 1.0. The cumulative risk value R_cum is expressed as a percentage, representing the weighted cumulative degradation degree of each degradation point. Based on the cumulative risk value, each area is divided into three levels: high risk, medium risk, and low risk. Areas with a cumulative risk value greater than 80 are marked as high risk, areas with a cumulative risk value between 40 and 80 are marked as medium risk, and areas with a cumulative risk value less than 40 are marked as low risk. The risk levels of each area are visualized and mapped according to the topological location of the station power supply to generate a risk level distribution map. The risk level distribution map uses the station power supply single-line map as the base map and overlays the risk level color blocks of each area. High-risk areas are displayed in red, medium-risk areas in yellow, and low-risk areas in green. The insulation of feeder No. 3 of a certain substation is gradually aging due to the cable intermediate joint being in a humid cable trench environment for a long time. Recent inspection found that the temperature at the joint was 15°C higher than that of a normal joint. The risk level distribution map shows that the feeder area is red and high-risk, requiring special attention.

[0025] In some embodiments, the step of performing a timing verification between the protection device configuration information and the switching equipment operation cycle to generate a protection coordination margin includes: extracting protection action time limit parameters from the protection device configuration information; performing a timing comparison between the protection action time limit parameters and the switching equipment operation cycle to generate a timing deviation value; performing a differential coordination verification based on the timing deviation value to generate a coordination validity identifier; and determining the protection coordination margin through the coordination validity identifier.

[0026] Extract protection action time parameters from the protection device configuration information. Read the setting parameters of each level of protection device in the protection device configuration information. The protection device configuration information includes three types of time parameters: overcurrent protection action time, instantaneous overcurrent protection action time, and backup protection action time. The overcurrent protection action time of the main transformer low-voltage side protection device in the protection device configuration information is usually set to 0.5 seconds, and the overcurrent protection action time of the feeder protection device is usually set to 0.3 seconds. In a certain substation, a short circuit was caused by a fault in the No. 6 feeder cable. Because the overcurrent protection of the No. 1 main transformer low-voltage side was set to 0.5 seconds and the No. 6 feeder protection was set to 0.3 seconds in the protection action time parameters, a 0.2-second difference was formed. After the fault occurred, the No. 6 feeder protection correctly operated and cleared the fault within 0.31 seconds, and the upstream main transformer protection did not operate, successfully avoiding a complete power outage of the substation. The overcurrent protection action time limit, instantaneous overcurrent protection action time limit, and backup protection action time limit of each level of protection device are recorded separately according to the protection level to form protection action time limit parameters. The protection action time limit parameters are stored with the protection device number as the index. In the protection action time limit parameters, the action time limit of the upper level protection should be greater than the action time limit of the lower level protection to meet the selectivity requirement, that is, when a fault occurs, the lower level protection will act first to clear the fault.

[0027] For example, the step of comparing the protection action time limit parameter with the switching equipment operation cycle to generate a timing deviation value includes: defining upper and lower limit intervals for the protection action time limit parameter to generate a valid time limit interval; matching and locating the switching equipment operation cycle with the valid time limit interval to generate a cycle matching position; quantifying the margin deviation based on the boundary interval between the cycle matching position and the valid time limit interval; and marking the margin deviation as insufficient margin to generate a timing deviation value.

[0028] The upper and lower limit ranges of the protection action time limit parameters are defined to generate a valid time limit range. The action time limit settings for each level of protection in the protection action time limit parameters are read. The typical action time limit for feeder protection in the protection action time limit parameters is 300 milliseconds. Based on the settings in the protection action time limit parameters, a 15% downward fluctuation is used as the lower limit, and a 15% upward fluctuation is used as the upper limit. The lower limit corresponds to the boundary of fast protection action, and the upper limit corresponds to the boundary of delayed protection action. The lower limit t_lower = t_set × 0.85 and the upper limit t_upper = t_set × 1.15 are calculated, where t_set is the setting value in the protection action time limit parameters. In the most recent periodic calibration, the measured action time of the protection device for feeder No. 3 in a certain substation was 285 milliseconds. The setting value for this protection in the protection action time limit parameters is 300 milliseconds. The corresponding valid time limit range has a lower limit of 255 milliseconds and an upper limit of 345 milliseconds. The measured value falls within the range, indicating that the protection performance is normal. The lower and upper time limits of each level of protection are paired to form a valid time limit interval. The lower and upper time limit values ​​are recorded using the protection device number as an index. The valid time limit interval represents the allowable fluctuation range of the action time of each level of protection. The actual action time of the protection falling within this interval is considered normal.

[0029] The switching equipment operation cycle is matched with the effective time interval to generate a cycle matching position. The opening time in the switching equipment operation cycle is compared with the lower and upper time limits of the effective time interval. When the circuit breaker opening time in the switching equipment operation cycle is less than the lower time limit of the effective time interval, the matching position is recorded as below the interval, indicating that the circuit breaker's operating speed is faster than the lower limit of the protection operation. The No. 3 feeder circuit breaker is a vacuum circuit breaker that was recently replaced in the last two years. The opening time, as tested on-site, is 52 milliseconds, which is less than the lower limit of the effective time interval (255 milliseconds), and is recorded as below the interval. This circuit breaker is in good condition, operates quickly, and coordinates well with the protection. When the circuit breaker opening time is between the lower and upper time limits, the matching position is recorded as inside the interval, indicating that the circuit breaker's operating time is within the allowable range of the protection. When the circuit breaker's tripping time exceeds the upper limit of the time limit, the matching position is recorded as "above the section," indicating that the circuit breaker's operating speed is slower than the protection's operating limit. A circuit breaker on feeder line 5 of a substation, having been in operation for over 12 years, experienced a tripping time extended to 380 milliseconds due to spring fatigue in the operating mechanism and wear on transmission components, exceeding the upper limit of the effective time interval by 345 milliseconds, requiring maintenance. The matching position information of each circuit breaker relative to its corresponding protection is integrated into a periodic matching position. The periodic matching position includes the tripping time of each circuit breaker and its position relative to the effective time interval. Circuit breakers with a matching position above the section in the periodic matching position have coordination risks and require priority maintenance.

[0030] The margin deviation is quantified based on the boundary interval between the periodic matching position and the effective time interval. For each circuit breaker's matching result at the periodic matching position, its distance from the effective time interval boundary is calculated. When the periodic matching position indicates the circuit breaker is below the interval, the lower boundary margin d_lower = t_lower - t_breaker is calculated, where t_lower is the lower limit of the effective time interval, and t_breaker is the circuit breaker's tripping time. The No. 3 feeder circuit breaker is a vacuum circuit breaker recently replaced within the last two years, with a good mechanism and rapid operation. The margin deviation calculation shows its lower boundary margin is 203 milliseconds, providing sufficient margin for the distance protection's lower limit to ensure rapid tripping in case of a fault. When the periodic matching position indicates the circuit breaker is inside the interval, the distances to the upper and lower boundaries are calculated separately, and the smaller value is taken as the margin. When the periodic matching position indicates that the circuit breaker is above the interval, the upper boundary over-limit is calculated as d_over = t_breaker - t_upper, where t_upper is the upper limit of the effective time interval. A negative over-limit indicates insufficient margin. The aforementioned old circuit breaker on feeder No. 5 has been in operation for over 12 years. Due to spring fatigue in the operating mechanism and wear of transmission components, the tripping time has been extended to 380 milliseconds. A margin deviation of -35 milliseconds indicates a risk in the coordination between this circuit breaker and the protection system. If a fault occurs, the tripping delay may cause the fault clearing time to exceed the protection setting range. The distance values ​​between each circuit breaker and the boundary of the effective time interval are integrated into the margin deviation, and the margin deviation is recorded using the circuit breaker number as an index.

[0031] A timing deviation value is generated by marking insufficient margins for early warning purposes. Circuit breakers with negative margin deviations are screened, as their timing coordination with the corresponding protection devices poses a risk. When the margin value of a circuit breaker in the margin deviation is less than -20 milliseconds, it is marked as severely insufficient and a Level 1 warning is set, indicating that the circuit breaker's tripping time has seriously exceeded the protection's allowable range and requires immediate repair or replacement. The aforementioned old circuit breaker on feeder No. 5, with a margin deviation of -35 milliseconds, was marked as a Level 1 warning; inspection revealed that its operating mechanism spring was fatigued and needed replacement. When the margin value in the margin deviation is between -20 milliseconds and 0, it is marked as slightly insufficient and a Level 2 warning is set. When the margin value is greater than 0 and less than 50 milliseconds, it is marked as critically insufficient and a Level 3 alert is set, reminding maintenance personnel to pay attention to the performance change trend of the circuit breaker. When the margin value is greater than 50 milliseconds, it is marked as sufficient margin and no warning is needed. The circuit breaker on feeder No. 3, with a margin of 203 milliseconds, is marked as having sufficient margin and is in good condition. The margin values ​​of each circuit breaker and the corresponding warning level in the margin deviation are integrated into the timing deviation value. The timing deviation value includes the margin value, warning level and corresponding upper and lower level protection action time limit parameters of each circuit breaker. For circuit breakers with level one warning in the timing deviation value, the matching of protection setting value and circuit breaker parameter must be checked immediately and maintenance should be arranged.

[0032] Based on the timing deviation value, a coordination verification is performed to generate a valid coordination identifier. The timing difference between adjacent protection devices is read from the timing deviation value, and the timing difference between the upper and lower level protection is calculated as Δt_step = t_upper - t_lower, where Δt_step is the timing difference, t_upper is the operating time of the upper level protection, and t_lower is the operating time of the lower level protection. The timing difference between the low-voltage side protection of the main transformer and the protection of feeder No. 3 is 500 - 300 = 200 milliseconds, which meets the coordination requirements. The timing difference between adjacent protection devices in the timing deviation value should meet the coordination requirement of 0.2-0.3 seconds. When the timing difference is less than 0.2 seconds, it is considered insufficient and there is a risk of over-level tripping, meaning that during a fault, the upper level protection may act before the lower level protection, leading to an expanded power outage area. In one substation, due to improper protection settings, the low-voltage side protection of the station service transformer acted first during a feeder fault, causing a complete power outage of the station. When the time difference between a pair of upstream and downstream protections in the timing deviation value is between 0.2 and 0.3 seconds, it is considered acceptable. When the time difference is greater than 0.3 seconds, it is considered too large and may affect the fault clearing speed. The timing difference verification results of each pair of upstream and downstream protections are integrated into a coordination validity identifier. The coordination validity identifier records the timing difference value and timing difference judgment result using the upstream and downstream protection device number pairs as indexes. Protection device pairs with insufficient timing differences in the coordination validity identifier need to have their settings adjusted to eliminate the risk of over-level tripping.

[0033] Protection coordination margin is determined by using effective coordination indicators. The number of protection device pairs with acceptable and excessively large level differences in the effective coordination indicators is counted; both are considered effective coordination. The coordination efficiency η is calculated as η = N_valid / N_total × 100%, where η is the coordination efficiency, N_valid is the number of effective coordination pairs in the effective coordination indicators, and N_total is the total number of protection device pairs. A substation has 9 pairs of hierarchical protection relationships, of which 8 pairs are effective coordination. However, due to an early setting error, the level difference between the low-voltage side protection of substation No. 2 and the feeder protection of No. 7 is only 0.15 seconds, which does not meet the 0.2-second coordination requirement, posing a risk of over-level tripping. This pair of protections is marked as having insufficient level difference in the effective coordination indicators, resulting in a coordination efficiency of 88.9%. When all protection device pairs in the effective coordination indicators are effective coordination, the overall protection coordination margin is considered sufficient. When the coordination efficiency is between 80% and 100%, the overall protection coordination margin is considered basically sufficient. In this substation, the coordination efficiency of 88.9% is considered basically sufficient, and the setting value of feeder 7 protection needs to be adjusted as soon as possible to eliminate the risk of cascading tripping. When the coordination efficiency is below 80%, the overall protection coordination margin is considered insufficient. The protection coordination margin is formed by summarizing the coordination efficiency, the specific level difference values ​​of each level of protection, and the overall coordination margin determination results. The protection coordination margin includes the overall coordination status and detailed coordination information of each level of protection.

[0034] Step S130: Conduct a hazard correlation analysis on the risk level distribution map and protection coordination margin to determine the key evaluation nodes. Based on the key evaluation nodes, assess the redundancy configuration adequacy to generate redundancy levels. Construct a graded evaluation index set based on the redundancy levels.

[0035] In some embodiments, the step of performing a hazard correlation analysis on the risk level distribution map and the protection coordination margin to determine key evaluation nodes includes: overlaying and mapping the risk level distribution map and the protection coordination margin to generate a risk margin correlation map; screening the risk margin correlation map for high-risk, low-margin areas to generate key areas of concern; performing power supply path uniqueness detection on the key areas of concern to generate a node priority list; and determining key evaluation nodes based on the node priority list.

[0036] A risk margin correlation diagram is generated by overlaying and mapping the risk level distribution map with the protection coordination margin. Based on the station power supply topology map of the risk level distribution map, the coordination status information of each node in the protection coordination margin is overlaid and marked to the corresponding position. The coordination margin value of the protection coordination margin for each area is overlaid on the color block of each area in the risk level distribution map, and the specific coordination margin in milliseconds is displayed in the form of a digital label. Due to the long service life of the cable and the high humidity of the laying environment, the insulation resistance monitoring of feeder No. 3 of a certain substation has shown a slow downward trend in the past six months. This area is marked as a yellow medium-risk color block in the risk level distribution map. The coordination margin of 145 milliseconds for this feeder is overlaid and marked in the protection coordination margin. This value indicates that there is a time margin of 145 milliseconds between the protection of feeder No. 3 and the upstream protection, which is still normal. A correlation judgment rule is set up so that when a certain area is classified as high-risk or medium-risk on the risk level distribution map and its protection coordination margin is less than 100 milliseconds, a red warning mark is added to the border of that area. For example, feeder No. 5 of a certain substation has a high risk of insulation degradation due to aging cable joints. Simultaneously, the circuit breaker on this feeder has a slow tripping time due to its long service life, resulting in a protection coordination margin of only 60 milliseconds. In the event of a short circuit fault, the delayed operation of the circuit breaker may lead to protection failure or cascading tripping of higher-level protection, expanding the power outage area. The superimposed topology map is then used to form a risk margin correlation map, which simultaneously displays the insulation risk level and protection coordination margin values ​​for each area.

[0037] The risk margin correlation diagram is used to filter high-risk, low-margin areas to generate key areas of concern. All areas marked with red warning signs in the risk margin correlation diagram are scanned; these areas simultaneously meet the dual conditions of high risk level and low margin. The risk level and margin values ​​of each red warning area in the risk margin correlation diagram are statistically analyzed, and the comprehensive risk index I_risk = W_r × R_level + W_m × (M_ref - M_margin) / M_ref is calculated, where I_risk is the comprehensive risk index, W_r is the risk level weight with a value of 0.6, R_level is the risk level value in the risk margin correlation diagram (3 for high risk, 2 for medium risk, and 1 for low risk), W_m is the margin weight with a value of 0.4, M_ref is the margin reference benchmark with a value of 100 milliseconds, and M_margin is the margin in milliseconds. Due to cable aging and overly tight protection settings, feeder No. 5 of a substation is classified as high-risk in the risk margin correlation diagram, with a coordination margin of only 60 milliseconds and a comprehensive risk index of 2.0, the highest in the entire substation, making it a key area of ​​concern. Areas with a comprehensive risk index greater than 1.5 are selected as key areas of concern. These key areas include their location number, comprehensive risk index, and corresponding power supply topology information, and are sorted from highest to lowest comprehensive risk index.

[0038] A node priority list is generated by detecting the uniqueness of power supply paths in key areas of concern. For each area within the key areas of concern, the uniqueness of its power supply path is checked. The power supply topology of the feeders in each area of ​​the key areas of concern is queried. If a feeder is powered only by a single station service transformer and lacks the ability to switch to other power sources, its power supply path is determined to be unique. For example, feeder No. 5 in the key areas of concern is powered only by station service transformer No. 1 and has no bus tie switch. If this feeder fails, power cannot be restored by switching power sources, so its power supply path is determined to be unique. If a feeder has the ability to switch to other power sources via a bus tie switch or an automatic backup power transfer device, its power supply path is determined to be non-unique. Feeder No. 3 can switch to station service transformer No. 2 via a bus tie switch. The uniqueness of the power supply path in each area of ​​the key areas of concern is marked. The priority of areas with unique power supply paths is increased by 50% based on the original comprehensive risk index, while the priority of areas with non-unique power supply paths remains unchanged. The adjusted priority values ​​are sorted from high to low to form a node priority list, which includes the location number of each node, the adjusted priority value, and the unique identifier of the power supply path. Nodes with unique power supply paths in the node priority list need to be evaluated first because they cannot switch to backup power in the event of a failure.

[0039] The key nodes for evaluation are determined based on the node priority list. The top 30% of nodes by priority value are selected from the list; these nodes require priority evaluation due to their high overall risk and poor power supply reliability. The location numbers and priority values ​​of the top 30% of nodes in the priority list are read. For a substation with 20 monitoring nodes, the top 6 nodes in the priority list are selected as key evaluation targets, with feeder No. 5 ranked first due to its unique power supply path and high insulation risk. The selected nodes are categorized and labeled according to the uniqueness of the power supply path in the priority list: critical nodes and important nodes. Nodes with unique power supply paths are labeled as critical nodes, while those with non-unique power supply paths are labeled as important nodes. The selected and categorized node information is summarized to form the key evaluation nodes. These key evaluation nodes include the location number, power supply path information, and corresponding protection configuration associations. Critical nodes require a higher frequency of testing during evaluation. Feeder No. 5, due to its unique power supply path, is labeled as a critical node and listed first in the list, requiring priority monitoring and maintenance.

[0040] Redundancy levels are generated based on the adequacy of redundancy configurations at key evaluation nodes. For each node in the key evaluation nodes, the redundancy level of its power supply path and protection configuration is assessed. The presence of backup power supply paths for each node is checked. A node is considered to have redundancy if its feeder has the capability to manually or automatically switch to a backup power source; otherwise, it is considered to lack redundancy. Feeder No. 3 in the key evaluation nodes can switch to power from the No. 2 substation transformer within 10 seconds via the bus tie switch, indicating redundancy. The protection configuration redundancy of each node in the key evaluation nodes is also checked. A node is considered to have sufficient protection redundancy if it has both primary and backup protection; otherwise, it is considered to have insufficient redundancy. Feeder No. 3 has two independent protection systems—overcurrent protection and instantaneous overcurrent protection—that serve as backups for each other, indicating sufficient protection redundancy. Based on the assessment results of combined power supply redundancy and protection redundancy, each node is classified into three levels: sufficient redundancy, basic redundancy, and insufficient redundancy. Nodes with both power supply redundancy and sufficient protection redundancy are classified as sufficient redundancy; nodes lacking either power supply or protection redundancy are classified as basic redundancy; and nodes lacking both power supply redundancy and protection redundancy are classified as insufficient redundancy. Feeder No. 5, lacking both backup power switching capability and equipped with only a single overcurrent protection, is classified as insufficient redundancy. The redundancy assessment results of each node are summarized to form a redundancy level, with the overall redundancy level recorded using the node number as an index.

[0041] A tiered evaluation index set is constructed based on redundancy levels. Different evaluation indexes are configured for nodes at different redundancy levels based on the differences in redundancy status of each node. The most stringent evaluation indexes are configured for nodes with insufficient redundancy, including a voltage deviation limit of ±5%, a current margin coefficient lower limit of 1.5, a harmonic distortion rate limit of 3%, and a protection action time deviation limit of ±10%. Feeder No. 5, being powered only by a single substation transformer and lacking bus tie-switching capability, and equipped with only a single overcurrent protection system without backup protection, is classified as insufficient redundancy. The above stringent indexes are applied, ensuring that any minor anomaly will trigger an alarm to detect potential problems before they escalate. Nodes with basic redundancy are configured with moderately stringent evaluation indexes, including a voltage deviation limit of ±7%, a current margin coefficient lower limit of 1.3, a harmonic distortion rate limit of 5%, and a protection action time deviation limit of ±15%. While Feeder No. 3 can switch to backup power via the bus tie-switching switch, the switching time is approximately 10 seconds, posing a risk of temporary power loss. Therefore, it is classified as basic redundancy and uses moderate indexes. Redundancy levels are configured with standard evaluation indicators for nodes with sufficient redundancy, including voltage deviation limits of ±10%, current margin coefficient lower limit of 1.2, harmonic distortion rate limits of 8%, and protection action time deviation limits of ±20%. Even in the event of anomalies, these nodes can ensure power supply safety through redundancy configuration. The evaluation indicators corresponding to each redundancy level are grouped and integrated into a hierarchical evaluation indicator set. This set contains three levels of indicator groups and their applicable node ranges. Each indicator in the hierarchical evaluation indicator set is labeled with its corresponding redundancy level and threshold value, facilitating automatic matching of the appropriate evaluation standard based on the node redundancy status during evaluation.

[0042] Step S140: The graded evaluation index set is divided into real-time detection index and periodic detection index according to the detection priority. The degradation trend of the periodic detection index is tracked to obtain the degradation offset coefficient. The degradation offset coefficient is fed back to the real-time detection index for threshold correction to generate adaptive detection index. Evaluation collaborative parameters are generated based on the collaborative configuration of adaptive detection index and periodic detection index.

[0043] Specifically, the graded evaluation index set is divided into real-time detection indicators and periodic detection indicators according to detection priority. The timeliness requirements and rate of change characteristics of each indicator in the graded evaluation index set are analyzed. Indicators requiring immediate response are classified as real-time detection indicators, while those with slow changes but capable of periodic detection are classified as periodic detection indicators. Voltage deviation and current margin coefficient in the graded evaluation index set are classified as real-time detection indicators due to their rapid change rate and direct impact on equipment safety. The sampling period for real-time detection indicators is set to 1 second. For example, during peak summer electricity consumption, a substation experienced a sudden increase in station load from 60% to 95% of its rated value within 30 seconds due to the concentrated start-up of air conditioners, causing the voltage to drop from 380V to 362V. Such rapid changes require real-time monitoring for timely detection. Harmonic distortion rate and protection action time deviation in the graded evaluation index set are classified as periodic detection indicators due to their relatively slow changes. The sampling period for periodic detection indicators is set to 1 hour. Changes in harmonic content are usually related to changes in load type and their evolution trend needs to be observed over a day or even longer period. The categorized indicators are organized into two subsets: real-time detection indicators and periodic detection indicators. The real-time detection indicators include voltage deviation threshold and current margin threshold and their corresponding sampling period of 1 second. The periodic detection indicators include harmonic distortion rate threshold and protection time limit deviation threshold and their corresponding sampling period of 1 hour. The periodic detection indicators are also associated with the historical sampling data storage path of the most recent 30 days in the historical database.

[0044] In some embodiments, the step of tracking the degradation trend of the periodic detection index to obtain the degradation offset coefficient includes: extracting continuous sampling data from the periodic detection index to generate a detection data curve; performing rate of change analysis on the detection data curve to determine the degradation rate; performing abrupt change detection on the degradation rate to generate a deviation amplitude; and determining the degradation offset coefficient based on the deviation amplitude.

[0045] Continuous sampling data was extracted from periodic detection indicators to generate detection data curves. Historical sampling data for the most recent 30 days of periodic detection indicators were read from the historical database. The sampling period for periodic detection indicators is 1 hour, totaling 720 sampling points over 30 days. The 720 sampled values ​​of harmonic distortion rate in the periodic detection indicators were arranged chronologically, and a time-series curve was plotted with the sampling time as the horizontal axis and the distortion rate value as the vertical axis. The load on feeder No. 3 of a substation mainly consists of office building air conditioners. As the use of inverter air conditioners gradually increased after the start of summer, the harmonic distortion rate curve showed a significant upward trend, fluctuating from 3.2% at the beginning of the month to 4.1% at the end of the month. Similarly, a time-series curve was plotted for the 720 sampled values ​​of protection action time deviation in the periodic detection indicators. The circuit breaker on feeder No. 5 of a substation has been in operation for over 12 years. Due to spring fatigue in the operating mechanism and wear of transmission components, its time deviation curve showed a gradual increase from 12 milliseconds at the beginning of the month to 18 milliseconds at the end of the month, reflecting a gradual decline in the performance of the circuit breaker mechanism. The time-series curves are smoothed to eliminate measurement noise using a 5-point moving average filtering method. The filtered curves more clearly show the overall trend. The smoothed time-series curves of each indicator are then aggregated to form the detection data curve, which stores the time-series data of each indicator using the indicator name as an index.

[0046] For example, the step of performing change rate analysis on the detection data curve to determine the degradation rate includes: performing segmented trend identification on the detection data curve to generate segmented change features; performing trend inflection point identification on the segmented change features to generate trend reversal indicators; filtering effective change segments based on the trend reversal indicators to generate an effective change set; and performing change gradient fusion on the effective change set to determine the degradation rate.

[0047] The detection data curve was segmented to identify trends and generate segmented change characteristics. The data curve was segmented according to a fixed time window, with each segment containing 120 sampling points over 5 days. The 30-day data was divided into 6 segments. Linear fitting was performed on each segment of the detection data curve, and the fitting slope and intercept were calculated. The segment slope characterizes the trend of the indicator within that time period. In the detection data curve, the slope of the first segment of the harmonic distortion rate curve was 0.01% / day, indicating a slow increase in harmonics during that period. The slope of the fifth segment suddenly increased to 0.06% / day. Reviewing the operation logs revealed that a high-power inverter cooling device in a data center server room was put into operation during this period. Its high-frequency switching power supply generated a large amount of 5th and 7th harmonics, injecting them into the station power supply and accelerating the deterioration of harmonics. Trends are categorized based on the sign and magnitude of the slope of each segment: segments with a slope greater than 0.03% / day are marked as rapidly rising; segments with a slope between 0 and 0.03% / day are marked as slowly rising; segments with a slope between -0.03% and 0 are marked as slowly declining; and segments with a slope less than -0.03% / day are marked as rapidly declining. The time range, fitted slope, and trend category of each segment are integrated into segment change features. These features record the start and end times and trend information of each segment, indexed by its segment number.

[0048] Trend inflection point identification is performed on segmented change characteristics to generate trend reversal markers. The trend categories of adjacent segments in the segmented change characteristics are compared to identify the segment boundaries where the trend reverses. When the trend category of a segment in the segmented change characteristics differs from the previous segment, the starting time of that segment is marked as a trend inflection point. In the segmented change characteristics, segment 3 shows a slow rise while segment 4 shows a rapid rise; the starting time of segment 4, day 16, is marked as a trend inflection point. Analysis reveals that this day coincided with local temperatures exceeding 35°C, all office building air conditioners being fully operational, and data center cooling load reaching peak levels. The simultaneous operation of numerous inverter devices led to accelerated harmonic deterioration. The positions of all trend inflection points in the segmented change characteristics and the type of trend change before and after each inflection point are statistically analyzed. When the trend changes from declining to rising before and after an inflection point, it is marked as a trough inflection point; when the trend changes from rising to declining before and after an inflection point, it is marked as a peak inflection point; and when the trend changes from slow to rapid before and after an inflection point, it is marked as an acceleration inflection point. The location and type information of each trend inflection point are summarized to form a trend reversal indicator. The trend reversal indicator records the time location and type of each inflection point using the inflection point number as an index. The appearance of an acceleration inflection point in the trend reversal indicator usually indicates that the equipment condition is rapidly deteriorating and needs to be taken seriously.

[0049] Effective change segments are generated by filtering effective change sets based on trend reversal indicators. Starting from each inflection point identified in the trend reversal indicators, effective change periods with a clear upward trend are selected. When there is an acceleration inflection point in the trend reversal indicators, all segments after that acceleration inflection point are considered effective change segments. These segments represent critical periods of rapid deterioration in equipment condition. Day 16 in the trend reversal indicators is the acceleration inflection point, and the data from day 16 to day 30 are used as effective change segments to calculate the recent true degradation rate. When there is a trough inflection point in the trend reversal indicators, the segments from the trough inflection point to the next peak inflection point are considered effective change segments. These segments represent the complete process of deterioration starting from the lowest point. When there is no obvious inflection point in the trend reversal indicators and the overall trend is monotonically upward, all 30 days of data are considered as effective change segments. For example, the No. 7 feeder cable of a certain substation, due to long-term thermal stress caused by long-term laying in a high-temperature trench, experienced continuous aging of the insulation layer, resulting in monotonous deterioration of relevant indicators without obvious inflection points. All 30 days of data were included in the effective change segments for analysis. The data from the selected effective change periods are extracted to form an effective change set. The effective change set includes the start and end times of the effective change periods, the number of data points, and the original sampled data within that period. Periods with irregular fluctuations or downward trends are excluded to ensure that the degradation rate calculated subsequently reflects the true deterioration trend.

[0050] The degradation rate is determined by gradient fusion of the effective change set. A linear regression analysis is performed on the data in the effective change set to fit a straight line representing the change in index values ​​over time within the effective change period. The fitting slope k_valid is calculated for the data in the effective change set; this slope represents the degradation rate within the effective change period. For example, the fitting slope for the harmonic distortion rate data from days 16 to 30 in the effective change set is 0.06% / day, indicating that harmonics deteriorate at a rate of 0.06% / day during this period. At this rate, the harmonic distortion rate will exceed the alarm threshold after one month. When the effective change set contains multiple discontinuous effective change segments, the fitting slope for each segment is calculated separately, and then a weighted average is taken according to the number of data points in each segment to obtain the comprehensive degradation rate k_fusion = Σ(k_i × n_i) / Σn_i, where k_fusion is the fused degradation rate, k_i is the fitting slope of the i-th effective change segment, and n_i is the number of data points in the i-th effective change segment. The degradation rate obtained from the fusion calculation is used as the final output. The degradation rate includes the fusion degradation rate value of various indicators and their corresponding stage rate data. The value in the degradation rate reflects the actual degradation speed of the equipment within the effective degradation period, excluding the interference of noise and fluctuations.

[0051] Abrupt changes in the degradation rate are detected to generate deviation amplitudes. The rate changes of various indicators in the degradation rate over different time periods are analyzed to identify any abrupt changes indicating accelerated degradation. The detection data curve is divided into three stages according to the time window: early stage (days 1-10), middle stage (days 11-20), and late stage (days 21-30), and the degradation rate for each stage is calculated. The difference between the late stage degradation rate and the early stage degradation rate is compared. When the late stage rate is more than 1.5 times that of the early stage rate, it is considered accelerated degradation. For example, feeder No. 4 of a substation supplies power to a newly built industrial park. In the early stage, there were few enterprises in the park, and the load was mainly for general lighting, resulting in a harmonic distortion rate degradation rate of only 0.02% / day. In the later stage, due to the commissioning of rectifier equipment from an electronics factory, a large amount of harmonic current was generated, and the degradation rate suddenly increased to 0.05% / day. The late stage rate being 2.5 times that of the early stage is considered accelerated degradation. Calculate the degradation acceleration factor A_ratio = V_late / V_early, where A_ratio is the acceleration factor, V_late is the later degradation rate, and V_early is the early degradation rate. Convert the acceleration factor to deviation amplitude D_amp = (A_ratio - 1) × 100%. A deviation amplitude of 150% for feeder 4 indicates a 150% acceleration in degradation rate, requiring immediate investigation of harmonic sources and consideration of installing filters. Summarize the deviation amplitudes of various indicators to form a deviation amplitude output. Record the acceleration factor and deviation amplitude percentage for each indicator, indexed by indicator name. Indicators with deviation amplitudes exceeding 100% indicate that the indicator is deteriorating rapidly and requires immediate attention.

[0052] The degradation offset coefficient is determined based on the deviation amplitude. The percentage of deviation amplitude for each indicator within the deviation amplitude is normalized, mapping deviation amplitudes of different orders of magnitude to an offset coefficient of a uniform scale. A normalization mapping rule is set, and the offset coefficient is calculated using the formula K_offset=min(D_amp / D_max,1), where K_offset is the offset coefficient, D_amp is the percentage of deviation amplitude in the deviation amplitude, and D_max is the set upper limit benchmark value for the deviation amplitude, taken as 200%. When the deviation amplitude is zero, the offset coefficient is zero, indicating that the degradation rate has not accelerated. When the deviation amplitude reaches the upper limit benchmark value, the offset coefficient is 1, indicating that the degradation rate has accelerated sharply. The deviation amplitude between zero and the upper limit is mapped to the corresponding offset coefficient in a linear proportion. The harmonic deviation amplitude of feeder No. 4, caused by the rectifier equipment in the electronics factory, reaches 150%. After normalization, the offset coefficient is 0.75, indicating that the degradation of this indicator is relatively severe, and the corresponding detection threshold needs to be tightened to provide timely warnings before further harmonic deterioration. A minimum effective value is set for the offset coefficient. When the offset coefficient calculated by normalization is lower than the minimum effective value, the minimum effective value is used to avoid the offset coefficient being too small, which would make subsequent threshold adjustments negligible and negligible, thus losing the meaning of adaptive adjustment. The normalized offset coefficients of each indicator are summarized to form the degradation offset coefficient. The degradation offset coefficient records the original deviation range and the normalized offset coefficient of each indicator, indexed by the indicator name. Indicators with higher offset coefficients in the degradation offset coefficient indicate that their degradation is accelerating. Subsequently, the thresholds of the corresponding real-time detection indicators should be tightened accordingly to achieve preventive maintenance.

[0053] In some embodiments, feeding back the degradation offset coefficient to the real-time detection index for threshold correction to generate an adaptive detection index includes: determining a threshold adjustment amount based on the degradation offset coefficient; adding the threshold adjustment amount to the original threshold of the real-time detection index to generate a correction threshold; applying an over-limit constraint to the correction threshold to generate a restricted correction threshold; and updating the real-time detection index using the restricted correction threshold to generate an adaptive detection index.

[0054] The threshold adjustment amount is determined based on the degradation offset coefficient. The offset coefficient values ​​of each indicator in the degradation offset coefficient are read, and the adjustment range of the corresponding real-time detection threshold is determined based on the magnitude of the offset coefficient. When the offset coefficient of harmonic distortion rate in the degradation offset coefficient is 0.75, it indicates that the harmonic deterioration rate is relatively fast, and the voltage deviation threshold needs to be tightened to provide early warning of voltage quality degradation caused by harmonics. The voltage deviation threshold adjustment amount is calculated as ΔT_v = T_v_original × K_offset × α = 7% × 0.75 × 0.5 = 2.625%, where T_v_original is the original voltage deviation threshold ±7%, K_offset is the offset coefficient of 0.75 in the degradation offset coefficient, and α is the adjustment sensitivity coefficient, taken as 0.5. When the offset coefficient of the protection time delay deviation in the deterioration offset coefficient is large, the current margin coefficient needs to be increased to increase the protection margin. The aforementioned No. 5 feeder circuit breaker, due to its long service life and deteriorating mechanical performance, has experienced a continuous increase in time delay deviation, resulting in an offset coefficient reaching 0.6. Therefore, the current margin requirement needs to be increased accordingly to ensure that the circuit breaker can still reliably isolate faults even with operating delays. The threshold adjustment amounts of various real-time monitoring indicators are summarized into a threshold adjustment amount list. The threshold adjustment amounts are recorded by index, using the indicator name as the index, recording the original threshold, offset coefficient, and calculated adjustment amount value for each indicator. Indicators with larger threshold adjustment amounts indicate that their associated periodic monitoring indicators are deteriorating rapidly.

[0055] The threshold adjustment is added to the original threshold of the real-time detection index to generate the correction threshold. The original thresholds of each index in the real-time detection index are read, and the corresponding adjustment amounts in the threshold adjustment are added together. For thresholds that need tightening, a subtraction operation is used. The original voltage deviation threshold in the real-time detection index is ±7%. After adding the adjustment amount of 2.625% in the threshold adjustment, the correction threshold is ±4.375%. Feeder No. 4 experiences rapid harmonic deterioration due to harmonic equipment from the electronics factory, so its voltage deviation correction threshold is tightened from ±7% to ±4.375%. Even slight voltage fluctuations can trigger an alarm, allowing maintenance personnel to promptly identify the harmonic source and take mitigation measures. For thresholds that need increasing, an addition operation is used. The original current margin coefficient threshold in the real-time detection index is 1.3. After adding the adjustment amount in the threshold adjustment, the correction threshold is 1.45. The result of the operation between the original thresholds and the adjustment amounts of each index forms the correction threshold. The correction threshold records the original threshold, adjustment amount, and corrected threshold value of each index using the index name as an index, reflecting the adaptive capability of dynamically adjusting the detection standards according to the equipment deterioration trend.

[0056] Limits are applied to the correction threshold to generate restricted correction thresholds. Boundary checks are performed on the threshold values ​​of each indicator within the correction threshold to ensure that the corrected threshold does not exceed the allowable adjustment range. The allowable adjustment range for the voltage deviation threshold is set to ±3% to ±10%. When the voltage deviation threshold in the correction threshold is less than ±3%, it is set to ±3% to avoid oversensitivity leading to frequent false alarms. When it is greater than ±10%, it is set to ±10% to ensure that serious anomalies are not missed. For example, feeder No. 6 of a substation suffered severe harmonic degradation and its offset coefficient reached 0.95. The calculated correction threshold was ±2.5%, which was constrained to ±3% because it was below the lower limit of ±3%. A reminder was issued to maintenance personnel, suggesting that the harmonic problem of this feeder be addressed as soon as possible. The allowable adjustment range for the current margin coefficient is set to 1.2 to 2.0. When the current margin coefficient in the correction threshold is greater than 2.0, it is set to 2.0; when it is less than 1.2, it is set to 1.2. The above constraints ensure that threshold adjustments are not too aggressive, leading to false alarms or missed alarms. The voltage deviation correction threshold for feeder 4, ±4.375%, remains unchanged within the allowable range. The thresholds after boundary constraints are formed into restricted correction thresholds. These restricted correction thresholds are recorded using the indicator name as an index, recording the threshold before and after the constraints, ensuring that threshold adjustments are made within a reasonable range.

[0057] Adaptive detection indicators are generated by updating real-time detection indicators using constrained correction thresholds. The threshold values ​​of each indicator in the constrained correction threshold are updated to the corresponding configuration items in the real-time detection indicators. The original voltage deviation threshold in the real-time detection indicators is replaced with the constrained threshold of voltage deviation in the constrained correction threshold; the voltage deviation threshold for feeder No. 4 is updated from ±7% to ±4.375%, making voltage monitoring of this feeder more sensitive and enabling earlier detection of voltage quality degradation caused by harmonics. The original current margin threshold in the real-time detection indicators is replaced with the constrained threshold of the current margin coefficient in the constrained correction threshold. The timestamp and reason for the threshold update are recorded, including the degradation offset coefficient value that triggered the update and the corresponding degradation status of the periodic detection indicators. The updated indicator configuration forms adaptive detection indicators. Adaptive detection indicators include the current effective threshold, threshold update history, and next planned update time for each indicator. Adaptive detection indicators recalculate and update thresholds every 7 days based on the latest degradation offset coefficient, achieving dynamic adjustment of detection standards according to changes in equipment status, ensuring the effectiveness and timeliness of the evaluation.

[0058] Evaluation coordination parameters are generated based on the collaborative configuration of adaptive detection indicators and periodic detection indicators. The real-time detection thresholds in the adaptive detection indicators and the detection cycles in the periodic detection indicators are integrated to form a unified detection parameter configuration table. The risk level and degradation trend characteristics of each monitoring node are analyzed, and differentiated detection parameter combinations are configured for nodes with different risk levels. High-risk nodes, due to rapid equipment deterioration, require more frequent periodic detection to promptly capture changes in degradation trends. Medium-risk nodes, with relatively stable equipment, can meet monitoring needs with conventional periodic detection. Low-risk nodes, with good equipment operation, can appropriately extend the periodic detection interval to reduce system resource consumption. The coordination between real-time detection thresholds and periodic detection cycles is optimized. When the real-time detection threshold in the adaptive detection indicators of a node tightens due to accelerated degradation, the corresponding periodic detection cycle also needs to be shortened to improve the timeliness of degradation trend tracking. For example, the circuit breaker of feeder No. 5 in a substation has experienced performance degradation due to its long service life, and the current margin threshold in the adaptive detection indicators has been tightened. Accordingly, the periodic detection cycle of this feeder is synchronously increased to continuously monitor the degradation trend of the circuit breaker performance. The integrated detection parameters are summarized to form evaluation collaboration parameters. The evaluation collaboration parameters record the real-time detection threshold, real-time detection cycle and periodic detection cycle corresponding to each level, indexed by risk level.

[0059] Step S150: Determine the evaluation execution area based on the evaluation collaboration parameters and risk level distribution map, perform critical state detection in the evaluation execution area to identify critical risk nodes, and generate a station power supply safety evaluation report based on the critical risk nodes.

[0060] In some embodiments, determining the assessment execution area based on the assessment collaboration parameters and the risk level distribution map includes: mapping the assessment collaboration parameters to the risk level distribution map to generate a parameter risk superposition distribution; dividing the parameter risk superposition distribution into regions to generate high, medium, and low risk partitions; identifying risk diffusion boundaries based on the high, medium, and low risk partitions to generate partition execution sequences; and defining the assessment execution area through the partition execution sequences.

[0061] The evaluation coordination parameters are mapped to the risk level distribution map to generate a parameter risk overlay distribution. Based on the station power supply topology map of the risk level distribution map, the various thresholds and detection cycle configuration information in the evaluation coordination parameters are mapped to regions according to the risk level. The voltage deviation threshold, current margin threshold, and detection cycle values ​​corresponding to that risk level in the evaluation coordination parameters are overlaid on the color blocks of each region in the risk level distribution map. The red high-risk areas in the risk level distribution map are overlaid with the voltage deviation threshold ±4%, current margin threshold 1.5, real-time detection cycle 1 second, and encrypted detection cycle 10 minutes. For example, the insulation of feeder No. 3 of a substation gradually aged due to the cable joint being in a damp cable trench environment for a long time. Recent inspections revealed that the temperature at the joint was 15°C higher than normal, and infrared imaging showed obvious hot spots. This feeder was classified as high-risk in the risk level distribution map. The yellow medium-risk areas in the risk level distribution map are overlaid with the voltage deviation threshold ±6%, current margin threshold 1.3, real-time detection cycle 1 second, and regular detection cycle 1 hour. The topology map after superimposing parameters is used to form a parameter risk superimposed distribution. The parameter risk superimposed distribution displays the risk level of each area and the corresponding detection parameter configuration. High-risk areas in the parameter risk superimposed distribution are highlighted with a red background and a thick border to facilitate maintenance personnel to quickly locate key areas of concern.

[0062] The parameter risk overlay distribution is divided into high, medium, and low risk zones. Based on the risk level and parameter configuration of each region in the parameter risk overlay distribution, the station power supply topology is divided into three risk zones. All red areas and their adjacent yellow buffer areas in the parameter risk overlay distribution are merged into a high-risk zone. The boundary of the high-risk zone is extended outward by one equipment unit to ensure that the risk diffusion range is covered. Due to the continuous environmental humidity exceeding 85% during the rainy season, condensation appeared on the surface of the insulators on the low-voltage side busbar of station service transformer No. 1 in a certain substation. During the night inspection, a slight discharge sound was found at the base of the insulator of the busbar support. The busbar and its subordinate feeders No. 1-4 are merged into a high-risk zone to prevent the fault from spreading and affecting the power supply of the entire station. The part of the yellow area in the parameter risk overlay distribution that is not included in the high-risk zone is designated as a medium-risk zone, as is the area of ​​feeders No. 5-6. The green area in the parameter risk overlay distribution is designated as a low-risk zone, as is the area of ​​feeders No. 7-8, which is designated as a low-risk zone due to the short equipment commissioning time and good operating environment. The partitioning results are divided into high, medium, and low risk partitions. Each high, medium, and low risk partition includes the topological range of each partition and the list of nodes it contains. The high-risk partition in the high, medium, and low risk partitions usually contains 20%-30% of the total number of nodes in the entire site.

[0063] Based on the risk zoning, risk diffusion boundaries are identified, and a zoning execution sequence is generated. The topological connections between zoning zones are analyzed to identify potential risk diffusion boundary locations. When a high-risk zone is adjacent to a medium-risk zone, the boundary between the two zones is designated as a Level 1 risk diffusion boundary. Equipment failures at this boundary can cause risk to spread from the high-risk area to the medium-risk area. For example, in a substation, feeders 4 and 5 are connected via a bus tie switch. If feeder 4 experiences a short circuit due to a cable joint failure, the fault current may be conducted through the bus to feeder 5, causing malfunction of its protection system. This tie location is marked as a Level 1 risk diffusion boundary. When a medium-risk zone is adjacent to a low-risk zone, the boundary between the two zones is designated as a Level 2 risk diffusion boundary. The evaluation execution order for each zone is determined based on the risk diffusion boundary level. The high-risk zone, due to its highest risk and potential for outward diffusion, is evaluated first. Equipment on the Level 1 risk diffusion boundary is evaluated next to monitor for risk diffusion. The medium-risk zone is evaluated next, and the Level 2 risk diffusion boundary and the low-risk zone are evaluated last. The execution order information is integrated into a partition execution sequence. The partition execution sequence records the name and execution priority of each partition or boundary using the execution sequence number as an index. The partition execution sequence is arranged in a fixed order of "high-risk partition → first-level boundary → medium-risk partition → second-level boundary → low-risk partition".

[0064] The evaluation execution area is defined by a partition execution sequence. Following the execution order in the partition execution sequence, each partition and boundary is included in the evaluation execution scope one by one. First, the high-risk partition, ranked first in the partition execution sequence, is included in the evaluation execution area. The detection parameters for each node within this partition are configured as strict thresholds and short-cycle detection at the high-risk level. For example, the low-voltage busbar of substation No. 1 is listed as a high-risk partition due to insulator discharge risk. This busbar and feeders No. 1-4 are the first batch of evaluation execution areas, using a voltage deviation threshold of ±4% and a 10-minute cycle detection to promptly detect abnormal voltage fluctuations caused by insulation degradation. Next, the first-level risk diffusion boundary in the partition execution sequence is included in the evaluation execution area. Nodes at the boundary are equipped with high-risk level detection parameters to monitor risk diffusion. The connection point between feeders No. 4 and No. 5 is also included in the execution area. Finally, the medium-risk partition, second-level risk diffusion boundary, and low-risk partition in the partition execution sequence are included in the evaluation execution area in sequence, with each area using detection parameters corresponding to its risk level. All partitions and boundaries are integrated to form a complete evaluation execution area. The evaluation execution area includes the topology range, execution order, risk level, detection parameter configuration and corresponding real-time data acquisition interface of each area, covering all monitoring nodes of station power supply and ensuring that the evaluation is carried out in an orderly manner according to risk level and diffusion path.

[0065] Critical state detection is performed in the evaluation execution area to identify critical risk nodes. Actual detection is performed according to the detection parameters and cycles configured for each area within the evaluation execution area, collecting voltage, current, and protection status data at each monitoring point. The collected real-time data is compared with the thresholds configured in the evaluation execution area. When the detected value at a monitoring point is close to the threshold but has not yet exceeded it, it is determined to be in a critical state. For example, in a certain substation, feeder No. 3, due to the high proportion of inverter air conditioners in its load, experiences a large influx of harmonic current during peak summer electricity consumption, leading to voltage waveform distortion. The measured voltage deviation of this feeder reached 4.1%, while the threshold configured in the evaluation execution area is ±4.375%. The deviation rate reaches 93.7% of the threshold, indicating a critical state. This suggests that the voltage quality of this feeder is approaching the alarm boundary, requiring close monitoring of the harmonic development trend. Criteria for determining critical states were established: a critical state was defined as the measured value reaching 85%-100% of the threshold; a slight over-limit state was defined as the measured value reaching 100%-115% of the threshold; and a severe over-limit state was defined as the measured value exceeding 115% of the threshold. All monitoring points within the evaluation area that were in critical or over-limit states were statistically analyzed and sorted according to the severity of their states to form a list of critical risk nodes. Each critical risk node list included its location number, measured value, threshold value, degree of criticality, and state type. In this evaluation, a substation identified 12 critical risk nodes: 2 nodes were severely over-limited due to cable joint overheating; 3 nodes were slightly over-limited due to insufficient protection coordination margin; and 7 nodes were in a critical state due to harmonics or load fluctuations.

[0066] A station power supply safety assessment report is generated based on the critical risk nodes. The risk information and handling recommendations for each node in the critical risk nodes are summarized, and an assessment report document is generated according to the report template format. The report overview section summarizes the total number of critical risk nodes and the distribution of nodes in various states. This assessment identified 12 critical risk nodes, of which 2 severely exceeded limits requiring immediate action, 3 slightly exceeded limits requiring near-term action, and 7 were in a critical state requiring continuous monitoring. The report details section lists detailed information for each critical risk node, including node location, associated equipment, detection indicators, measured values, threshold values, degree of deviation, and recommended measures. For example, the voltage deviation at feeder node 3 of a certain substation reached a critical state due to harmonics from a frequency converter air conditioner. Recommended measures include installing a passive filter on the feeder's incoming side to suppress the 5th and 7th harmonics, increasing the periodic detection frequency from 1 hour to 30 minutes, and coordinating with property management to stagger the use of high-power air conditioning equipment during off-peak hours. The report's conclusions rate the overall safety status of the substation's power supply. When a critical risk node contains a severely over-limit node, the overall rating is unqualified and requires immediate rectification. When only slightly over-limit and critical state nodes exist, the overall rating is basically qualified and requires attention. When there are no over-limit nodes and critical state nodes are less than 10% of the total number of nodes, the overall rating is qualified. The above content is integrated into a substation power supply safety assessment report, which includes five parts: report overview, node details, risk analysis, handling recommendations, and overall rating. The substation power supply safety assessment report is automatically generated as a PDF document and pushed to the operation and maintenance management platform for relevant personnel to view and handle. For this substation, the overall rating of the substation power supply safety assessment report is basically qualified. The report recommends installing a filter for the harmonic problem caused by the concentrated use of frequency converter air conditioners in the office building on feeder No. 3, and recommends replacing the operating mechanism or replacing the entire circuit breaker for feeder No. 5 due to aging mechanisms after 12 years of operation.

[0067] To implement the station power supply safety evaluation method corresponding to the above method embodiments, and to achieve the corresponding functions and technical effects. See also Figure 2 , Figure 2 This diagram illustrates a structural block diagram of a station power supply safety assessment device 200 according to an embodiment of this application. For ease of explanation, only the parts relevant to this embodiment are shown. The station power supply safety assessment device 200 provided in this embodiment includes: Data acquisition module 201 is used to collect the voltage and current parameters of the station power supply, the configuration information of the protection device, and the operation cycle of the switching equipment, and to associate and match the voltage and current parameters with the configuration information of the protection device to construct a safety evaluation benchmark. Risk identification module 202 is used to identify areas with potential insulation degradation through the safety evaluation benchmark, perform cumulative impact assessment on the areas with potential insulation degradation to generate a risk level distribution map, and perform timing verification between the protection device configuration information and the operation cycle of the switchgear to generate protection coordination margin. The indicator construction module 203 is used to perform a hidden danger correlation analysis on the risk level distribution map and the protection coordination margin to determine the key evaluation nodes, evaluate the redundancy configuration adequacy based on the key evaluation nodes to generate redundancy levels, and construct a graded evaluation indicator set according to the redundancy levels. The adaptive correction module 204 is used to distinguish the graded evaluation index set according to the detection priority to generate real-time detection indexes and periodic detection indexes, track the degradation trend of the periodic detection indexes to obtain degradation offset coefficients, feed the degradation offset coefficients back to the real-time detection indexes for threshold correction to generate adaptive detection indexes, and generate evaluation coordination parameters according to the collaborative configuration of the adaptive detection indexes and the periodic detection indexes. The report generation module 205 is used to determine the evaluation execution area based on the evaluation collaboration parameters and the risk level distribution map, perform critical state detection in the evaluation execution area to identify critical risk nodes, and generate a station power supply safety evaluation report based on the critical risk nodes.

[0068] The aforementioned station power supply safety assessment device 200 can implement one of the station power supply safety assessment methods described in the above method embodiments. The options in the above method embodiments are also applicable to this embodiment, and will not be detailed here. The remaining contents of this application embodiment can be referred to the contents of the above method embodiments, and will not be repeated in this embodiment.

[0069] The purpose of the above embodiments is to reproduce and derive the technical solution of the present invention by way of example, and to fully describe the technical solution, purpose and effect of the present invention. The purpose is to enable the public to have a more thorough and comprehensive understanding of the disclosure of the present invention, and not to limit the scope of protection of the present invention.

[0070] The above embodiments are not an exhaustive list based on the present invention, and there may be many other embodiments not listed. Any substitutions and improvements made without departing from the concept of the present invention are within the protection scope of the present invention.

Claims

1. A method for evaluating the safety of station power supplies, characterized in that, include: The data acquisition station uses power supply voltage and current parameters, protection device configuration information, and switching equipment operation cycles to correlate and match the voltage and current parameters with the protection device configuration information to construct a safety evaluation benchmark. The safety assessment benchmark identifies areas with potential insulation degradation, and the cumulative impact of these areas is assessed to generate a risk level distribution map. The configuration information of the protection device is then time-sequentially verified with the operating cycle of the switchgear to generate a protection coordination margin. A hazard correlation analysis is performed on the risk level distribution map and the protection coordination margin to determine the key evaluation nodes. Based on the key evaluation nodes, the redundancy configuration adequacy is evaluated to generate redundancy levels. A graded evaluation index set is constructed based on the redundancy levels. The graded evaluation index set is divided into real-time detection indexes and periodic detection indexes according to detection priority. The degradation trend of the periodic detection index is tracked to obtain the degradation offset coefficient. The degradation offset coefficient is fed back to the real-time detection index for threshold correction to generate adaptive detection indexes. Evaluation coordination parameters are generated according to the collaborative configuration of the adaptive detection indexes and the periodic detection indexes. Based on the evaluation collaboration parameters and the risk level distribution map, the evaluation execution area is determined, critical state detection is performed in the evaluation execution area to identify critical risk nodes, and a station power supply safety evaluation report is generated based on the critical risk nodes.

2. The method according to claim 1, characterized in that, The process of identifying potential insulation degradation areas using the safety evaluation benchmark includes: Abnormal fluctuation characteristics are generated based on the aforementioned safety evaluation benchmark; The duration of the abnormal fluctuations was statistically analyzed to identify suspected areas of degradation. The degradation rate of the suspected deterioration areas is assessed to generate a degradation classification label; The degradation classification markers are used to locate areas with potential insulation degradation.

3. The method according to claim 1, characterized in that, The step of performing a timing verification between the protection device configuration information and the operating cycle of the switching equipment to generate a protection coordination margin includes: Extract protection action time limit parameters from the configuration information of the protection device; The timing deviation value is generated by comparing the protection action time limit parameter with the operation cycle of the switching equipment. Based on the time deviation value, a graded fit verification is performed to generate a valid fit identifier; The protective fit margin is determined by the effective identification of the fit.

4. The method according to claim 1, characterized in that, The step of performing a hazard correlation analysis on the risk level distribution map and the protection coordination margin to determine key evaluation nodes includes: The risk level distribution map is overlaid and mapped with the protection coordination margin to generate a risk margin correlation map; The risk margin correlation diagram is used to filter high-risk, low-margin areas to generate key areas of concern. A node priority list is generated by performing power supply path uniqueness detection on the key areas of interest. The key evaluation nodes are determined based on the node priority list.

5. The method according to claim 1, characterized in that, The step of tracking the degradation trend of the periodic detection index to obtain the degradation offset coefficient includes: Continuous sampling data is extracted from the periodic detection index to generate a detection data curve; The rate of change of the detected data curves is analyzed to determine the degradation rate; The degradation rate is subjected to abrupt change detection to generate a deviation amplitude; The degradation offset coefficient is determined based on the deviation magnitude.

6. The method according to claim 1, characterized in that, The step of feeding back the degradation offset coefficient to the real-time detection index for threshold correction to generate an adaptive detection index includes: The threshold adjustment amount is determined based on the degradation offset coefficient; The threshold adjustment amount is superimposed on the original threshold of the real-time detection index to generate a correction threshold; The correction threshold is subjected to over-limit constraints to generate a restricted correction threshold; An adaptive detection index is generated by updating the real-time detection index using the constrained correction threshold.

7. The method according to claim 1, characterized in that, The process of determining the assessment execution area based on the assessment collaboration parameters and the risk level distribution map includes: The assessment collaboration parameters are mapped to the risk level distribution map to generate a parameter risk overlay distribution; The risk superposition distribution of the parameters is divided into high, medium and low risk zones. Based on the high, medium, and low risk zones, risk diffusion boundaries are identified, and a partition execution sequence is generated. The evaluation execution area is defined by the partition execution sequence.

8. The method according to claim 3, characterized in that, The step of comparing the protection action time limit parameter with the operating cycle of the switching equipment to generate a timing deviation value includes: The upper and lower limit ranges of the protection action time limit parameters are defined to generate a valid time limit range; The operation cycle of the switching device is matched with the effective time interval to generate a cycle matching position; The quantization margin deviation is based on the boundary interval between the period matching position and the effective time interval. The margin deviation is marked with an insufficient margin warning to generate a time-series deviation value.

9. The method according to claim 5, characterized in that, The step of determining the degradation rate by analyzing the rate of change of the detection data curve includes: The detected data curve is segmented to identify trends and generate segmented change features; The segmented change characteristics are used to identify trend inflection points and generate trend reversal indicators. Based on the trend reversal markers, valid change segments are filtered to generate a valid change set; The degradation rate is determined by performing change gradient fusion on the effective set of changes.

10. A station power supply safety assessment device, characterized in that, include: The data acquisition module is used to collect the voltage and current parameters of the power supply, the configuration information of the protection device, and the operation cycle of the switching equipment. It also associates and matches the voltage and current parameters with the configuration information of the protection device to construct a safety evaluation benchmark. The risk identification module is used to identify areas with potential insulation degradation hazards through the safety evaluation benchmark, perform cumulative impact assessment on the areas with potential insulation degradation hazards to generate a risk level distribution map, and perform time-series verification between the protection device configuration information and the operation cycle of the switchgear to generate protection coordination margin. The indicator construction module is used to perform hidden danger correlation analysis on the risk level distribution map and the protection coordination margin to determine the key evaluation nodes, evaluate the redundancy configuration adequacy based on the key evaluation nodes to generate redundancy levels, and construct a graded evaluation indicator set according to the redundancy levels. An adaptive correction module is used to distinguish the graded evaluation index set according to the detection priority to generate real-time detection indexes and periodic detection indexes, track the degradation trend of the periodic detection indexes to obtain degradation offset coefficients, feed the degradation offset coefficients back to the real-time detection indexes for threshold correction to generate adaptive detection indexes, and generate evaluation coordination parameters based on the collaborative configuration of the adaptive detection indexes and the periodic detection indexes. The report generation module is used to determine the evaluation execution area based on the evaluation collaboration parameters and the risk level distribution map, perform critical state detection in the evaluation execution area to identify critical risk nodes, and generate a station power supply safety evaluation report based on the critical risk nodes.

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