Method and system for evaluating health status of arrester group based on key node monitoring

Abstract

This invention discloses a method and system for assessing the health status of surge arresters based on key node monitoring, belonging to the field of power distribution system condition assessment technology. The method includes the following steps: performing electromagnetic transient simulation on the power distribution line under test based on the parameters of the surge arrester group; analyzing the spatiotemporal evolution law of lightning impact in the power distribution line based on the simulation results, and selecting key monitoring nodes related to stress characteristics based on the spatiotemporal evolution law; collecting multidimensional state data at the key monitoring nodes, which, together with the power distribution line physical structure data, constitutes a heterogeneous dataset, and preprocessing the heterogeneous dataset; and using a spatial inversion strategy based on isomorphic field theory to perform full-line inversion and state assessment on the preprocessed heterogeneous dataset to obtain the final health status assessment result. This invention aims to achieve comprehensive perception of the status of surge arresters across the entire power distribution line using a low-cost sparse monitoring network, thereby improving the intelligence and efficiency of power distribution network operation and maintenance.

Description

Technical Field

[0001] This invention relates to the field of power distribution system condition assessment technology, and in particular to a method and system for assessing the health status of surge arresters based on critical node monitoring. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] In 10kV power distribution systems, metal oxide surge arresters (MOAs) are core components for limiting overvoltages and protecting the insulation of lines and equipment. Their operational reliability is crucial to power grid safety. Surge arresters operating outdoors for extended periods are subjected to the combined effects of continuous operating voltage, alternating ambient temperature and humidity, and transient overvoltage surges. This causes the varistor resistance characteristics to gradually deteriorate, leading to increased resistive leakage current and reduced thermal stability. In severe cases, this can trigger thermal breakdown or insulation breakdown accidents, resulting in line tripping and large-scale power outages.

[0004] Currently, condition assessment of surge arresters (MOAs) primarily employs two technical approaches: periodic offline preventative testing and online monitoring. Offline testing, limited by the testing cycle, struggles to capture sudden damage caused by lightning strikes or operational overvoltages during the intervals between tests, resulting in significant time-related blind spots. While online monitoring technology, covering all nodes, can provide real-time equipment status, its widespread distribution, complex branches, and large number of devices in power distribution lines necessitate high hardware investment and communication maintenance costs for monitoring all surge arresters on the line, hindering its large-scale application in engineering projects.

[0005] Furthermore, existing monitoring and diagnostic technologies are mostly limited to the independent analysis of the electrical parameters of individual surge arresters, lacking a system-level condition assessment approach. In engineering, the overvoltage stress distribution borne by a group of surge arresters on the same distribution line has clear spatial correlation and topological constraint characteristics, but existing methods do not fully utilize these characteristics, resulting in excessively high monitoring costs or incomplete monitoring coverage. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for assessing the health status of surge arresters based on key node monitoring. This method utilizes the propagation and attenuation laws of electromagnetic waves on transmission lines to establish a mapping relationship between a small number of key nodes and the status of all equipment along the entire line, effectively resolving the contradiction between monitoring cost and coverage. This invention aims to achieve comprehensive perception of the status of surge arresters across the entire line using a low-cost sparse monitoring network, thereby improving the intelligence and efficiency of distribution network operation and maintenance.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solution: The first aspect of this invention provides a method for assessing the collective health status of surge arresters based on critical node monitoring, comprising the following steps: Electromagnetic transient simulation of the power distribution line under test is performed based on the group parameters of the surge arrester under test. Based on the simulation results, the spatiotemporal evolution of lightning impacts in power distribution lines is analyzed, and key monitoring nodes related to stress characteristics are selected according to the spatiotemporal evolution. Multidimensional status data at key monitoring nodes are collected. The multidimensional status data and the physical structure data of the power distribution line constitute a heterogeneous dataset, and the heterogeneous dataset is preprocessed. By employing a spatial inversion strategy based on isomorphic field theory, a full-path inversion and state assessment are performed on the preprocessed heterogeneous dataset to obtain the final health status evaluation results.

[0008] Furthermore, the specific steps for performing electromagnetic transient simulation of the distribution line under test based on the group parameters of the surge arrester under test are as follows: Analysis of the group state correlation mechanism of surge arresters based on the stress distribution characteristics of power distribution lines; A lightning impulse simulation model for distribution lines is constructed based on the state correlation mechanism of surge arresters. The lightning impulse simulation model for distribution lines includes a distribution line simulation model and a lightning current model.

[0009] Furthermore, the lightning current model uses a double exponential wave current source to simulate lightning strikes, setting three lightning strike scenarios: lightning strike at the beginning of the corresponding line, lightning strike in the middle of the corresponding line, and lightning strike at the end of the corresponding line.

[0010] Furthermore, the specific steps for analyzing the arrester group state correlation mechanism based on the stress distribution characteristics of power distribution lines are as follows: Analysis of the nonlinear characteristics and aging properties of surge arresters; Analyze the voltage traveling wave conduction mechanism of power distribution lines under lightning strikes; Based on the nonlinear characteristics and aging properties of surge arresters and the voltage traveling wave conduction mechanism of distribution lines under lightning impact, a spatial mapping relationship between overvoltage energy dissipation and surge arrester aging is established.

[0011] Furthermore, the specific steps for screening key monitoring nodes related to stress characteristics based on spatiotemporal evolution are as follows: Based on the simulation data, the maximum voltage amplitude of each surge arrester node under different lightning strike locations was extracted, and the stress distribution envelope diagram of the entire line was drawn. The stress envelope characteristics of the stress distribution envelope diagram of the entire line are analyzed, and key monitoring nodes are determined based on the principle of maximizing stress coverage and minimizing interpolation distance error.

[0012] Furthermore, the specific steps for performing full-path inversion and state assessment of the preprocessed heterogeneous dataset using a spatial inversion strategy based on isomorphic field theory are as follows: Based on the stress field distribution reconstructed from the preprocessed heterogeneous dataset, multi-dimensional inversion of current, temperature, and fluctuation number is performed, including normalized current inversion based on temperature correction, relative temperature rise inversion, and fluctuation number inversion. A non-uniformly graded state assessment is performed on the multi-dimensional inversion.

[0013] Furthermore, the specific steps for non-uniformly graded state assessment of multi-dimensional inversion are as follows: The safety margin of the leakage current of a surge arrester is defined to characterize the static insulation level of the surge arrester. The rate of loss of the safety margin of the surge arrester leakage current is determined according to the five-level non-uniform design condition assessment standard. The inversion results are assessed for state based on the non-uniform five-level state assessment criteria.

[0014] A second aspect of the present invention provides a surge arrester group health status assessment system based on critical node monitoring, comprising: The simulation module is configured to perform electromagnetic transient simulation of the power distribution line under test based on the group parameters of the surge arrester under test; The key point screening module is configured to analyze the spatiotemporal evolution of lightning impacts in power distribution lines based on simulation results, and screen key monitoring nodes related to stress characteristics based on the spatiotemporal evolution. The dataset construction module is configured to collect multidimensional status data at key monitoring nodes. The multidimensional status data and the physical structure data of the power distribution line constitute a heterogeneous dataset, and the heterogeneous dataset is preprocessed. The state assessment module is configured to use a spatial inversion strategy based on isomorphic field theory to perform full-path inversion and state assessment on the preprocessed heterogeneous dataset, and obtain the final health status assessment result.

[0015] A third aspect of the present invention provides a computer-readable storage medium storing a computer program adapted to be loaded by a processor and to execute steps in the surge arrester group health status assessment method based on critical node monitoring as described in the first aspect of the present invention.

[0016] A fourth aspect of the present invention provides a computer device comprising: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the surge arrester group health status assessment method based on critical node monitoring as described in the first aspect of the present invention.

[0017] The above one or more technical solutions have the following beneficial effects: This invention discloses a method and system for assessing the collective health status of surge arresters based on key node monitoring. In 10kV distribution networks, zinc oxide surge arresters have numerous nodes and complex operating conditions; their insulation degradation directly affects the reliability of the power supply. Addressing the issues of high cost of deploying online monitoring devices across the entire line and blind spots in manual inspections, this invention constructs an electromagnetic transient simulation model of a typical 10kV distribution line, analyzes the overvoltage stress distribution envelope characteristics under different lightning strike points and topologies, and establishes an optimized location strategy for key monitoring nodes. Furthermore, it proposes a spatial interpolation inversion algorithm to infer the operating status of non-monitoring points using measured data from key nodes. This invention aims to achieve comprehensive perception of the status of surge arresters across the entire line using a low-cost sparse monitoring network, thereby improving the intelligence and efficiency of distribution network operation and maintenance.

[0018] This invention first analyzes the spatiotemporal evolution of lightning strikes in distribution lines based on MATLAB / Simulink electromagnetic transient simulation, and selects key monitoring nodes covering stress extrema based on stress envelope characteristics. Secondly, it constructs a theoretical model of an "electro-thermal-mechanical isomorphic field," and reconstructs the insulation aging, thermal stability, and dynamic fatigue state of all line surge arresters using spatial interpolation algorithms based on multidimensional state data collected from key nodes. Finally, it establishes a three-dimensional evaluation system including safety margin consumption rate, relative temperature rise, and fluctuation frequency, and adopts a non-uniform grading standard adapted to the aging acceleration law and a maximum value judgment strategy to achieve accurate classification of equipment health status. This invention effectively overcomes the limitations of independent monitoring of single devices, significantly reducing the deployment cost of sensor networks while achieving real-time perception and accurate diagnosis of the health status of the entire group of surge arresters in distribution lines, providing a theoretical basis and technical support for differentiated operation and maintenance of distribution network equipment.

[0019] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of the surge arrester group health status assessment method based on key node monitoring in Embodiment 1 of the present invention; Figure 2This is the equivalent circuit diagram of the zinc oxide surge arrester in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the spatial propagation and attenuation of lightning shock waves on a line in Embodiment 1 of the present invention; Figure 4 This describes the spatial cascading mapping mechanism of surge arrester aging in Embodiment 1 of the present invention. Figure 5 This is a diagram of the power distribution line topology in Embodiment 1 of the present invention; Figure 6 This is an envelope diagram showing the maximum voltage stress distribution of line surge arresters at different lightning strike locations in Embodiment 1 of the present invention; Figure 7 This is a flowchart of the spatial inversion strategy algorithm in Embodiment 1 of the present invention; Figure 8 This is a curve showing the fitting of the calculated leakage current value and the actual value in the deduced data table of Embodiment 1 of the present invention. Detailed Implementation

[0022] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used in these embodiments have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof. The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0024] Example 1: Embodiment 1 of the present invention provides a method for assessing the collective health status of surge arresters based on critical node monitoring, such as... Figure 1 As shown, it includes the following steps: S1: Perform electromagnetic transient simulation of the distribution line under test based on the group parameters of the surge arrester under test.

[0025] S1.1: Analysis of the group state correlation mechanism of surge arresters based on the stress distribution characteristics of power distribution lines.

[0026] S1.1.1: Analysis of the nonlinear characteristics and aging characterization of surge arresters.

[0027] In one specific implementation, this embodiment uses a zinc oxide surge arrester (MOA) as an example. The core component of the zinc oxide surge arrester is a zinc oxide resistive varistor, which has excellent nonlinear volt-ampere characteristics. Under normal power frequency operating voltage, the varistor exhibits a megaohm-level impedance, and the current flowing through it is only in the microampere range. When subjected to lightning strikes or switching overvoltage impulses, the varistor impedance instantly drops to the ohm level, rapidly conducting and discharging the lightning current, clamping the overvoltage below the equipment insulation level. The equivalent circuit model of the zinc oxide surge arrester is as follows: Figure 2 As shown.

[0028] Depend on Figure 2 It can be seen that, electrically, MOA can be equivalent to a nonlinear resistor. With capacitor Parallel model, The resistance of the zinc oxide resistive element is the granular resistance. The total current flowing through the surge arrester is... From capacitive components and resistive components Vector composition: (1).

[0029] Among them, capacitive current Depending on the mains voltage and valve plate capacitance, it is usually relatively stable, while the resistive current... This is a key indicator reflecting the aging state of the valve plate. As MOA (Metal Oxide Asphalt) is subjected to long-term power frequency voltage and multiple lightning strikes, its grain boundary structure gradually degrades, leading to… This significantly increases the leakage current of the surge arrester, leading to a significant increase in the leakage current. In this embodiment, the leakage current change rate is selected as a characteristic quantity to characterize the static insulation level of the surge arrester.

[0030] Therefore, the active power loss generated by the resistive current is converted into Joule heat, leading to an increase in the varistor temperature. Simultaneously, the zinc oxide varistor exhibits a negative temperature resistance characteristic; the increased temperature, in turn, causes a further increase in the resistive current, forming a positive feedback loop. Thus, when a surge arrester has a defect, it usually first manifests as an abnormal temperature rise; if this is not detected in time, it will induce thermal collapse. Therefore, this embodiment selects relative temperature rise as the second characteristic quantity to characterize the thermal stability of the surge arrester.

[0031] Regarding the dynamic response of surge arresters under transient overvoltage impulses, a surge arrester in a healthy state should be able to quickly cut off the power frequency follow current after operation, and the current should smoothly recover to a steady state. However, equipment in an aging or sub-healthy state may experience arc reignition or current oscillation during the recovery phase after the impulse due to fatigue of the valve material or a decline in arc extinguishing performance. Therefore, this embodiment selects the number of fluctuations as the third characteristic quantity to characterize the dynamic response capability of the surge arrester.

[0032] S1.1.2: Analysis of the voltage traveling wave conduction mechanism of power distribution lines under lightning impact.

[0033] In one specific implementation, this embodiment takes a 10kV distribution line as an example. The aging of surge arresters on distribution lines does not occur in isolation, but is closely related to the distribution of overvoltage stress borne by the line. When a lightning strike occurs at a point on the line, the lightning wave, as a non-periodic pulse traveling wave, propagates along the conductor to both sides. Due to the resistance, conductance, and ground loss of the 10kV distribution line, the lightning surge wave undergoes energy attenuation and waveform distortion during transmission. Assume the initial amplitude of the lightning overvoltage traveling wave is... Propagation distance along the route The voltage amplitude after It can be approximated as: (2).

[0034] In the formula, This is the attenuation coefficient of the line, which is related to the conductor parameters and frequency. A schematic diagram of the spatial propagation and attenuation of lightning surge waves on a line is shown below. Figure 3 As shown, the closer the surge arrester is to the lightning strike point, the greater the overvoltage amplitude it experiences, meaning the greater the overvoltage stress, the more energy it absorbs, and the faster its aging rate. With increasing electrical distance, the overvoltage amplitude decays exponentially, and the impact on the surge arrester gradually weakens. This spatial correlation between stress and distance forms the physical basis for using key point data to estimate the overall state in this embodiment.

[0035] S1.1.3: Based on the nonlinear characteristics and aging characteristics of surge arresters and the voltage traveling wave conduction mechanism of distribution lines under lightning impact, establish the spatial mapping relationship between overvoltage energy dissipation and surge arrester aging.

[0036] In one specific implementation, the aging process of a group of surge arresters in a distribution line is not an isolated random event, but follows a strict spatial cascade mapping mechanism with overvoltage traveling waves as the excitation source, energy dissipation as the intermediate process, and insulation damage as the final result. When lightning or switching overvoltage traveling waves intrude into the distribution line, as the initial physical excitation of the system, their transmission process on the line is accompanied by a clear spatial attenuation characteristic. Affected by line impedance and ground conductance, the overvoltage waveform exhibits physically regular amplitude attenuation and waveform distortion at different locations along the line, forming a continuously distributed electric stress field. In this physical process, the zinc oxide surge arrester, as an energy discharge channel, has its valve plate cumulative damage directly dependent on the overvoltage energy absorbed at its location. Due to the continuous spatial distribution of the electric stress field, there is an isomorphic field constraint between the cumulative damage of the valve plates of the surge arresters at each node, such as... Figure 4 As shown.

[0037] Depend on Figure 4 Analysis reveals that the damage levels of adjacent nodes do not evolve independently, but are strongly coupled by the line's topology and the traveling wave propagation equation. This constraint implies that the insulation damage distribution across the entire line possesses inherent integrity and predictability. Based on this mechanism, by sampling key points located at stress extrema or topological critical positions, the boundary conditions and core evolutionary characteristics of this isomorphic field can be captured. The monitoring system does not need to cover all equipment along the entire line; it only needs to utilize measured data from key nodes, combined with isomorphic field constraint logic, to decouple and reconstruct the operating status of non-monitored points across the entire line. This provides the fundamental physical theoretical basis for this invention to achieve accurate global state perception using a sparse monitoring network.

[0038] S1.2: Construct a lightning impulse simulation model for power distribution lines based on the state correlation mechanism of surge arresters.

[0039] In one specific implementation, the lightning impact simulation model for power distribution lines includes a power distribution line simulation model and a lightning current model. The lightning current model uses a double exponential wave current source to simulate lightning strikes, setting three lightning strike scenarios: lightning strike at the beginning of the corresponding line, lightning strike in the middle of the corresponding line, and lightning strike at the end of the corresponding line.

[0040] Specifically, a 10kV distribution type YH5WZ-17 / 45 surge arrester was used. A model was built in MATLAB / Simulink, and the volt-ampere characteristic parameters were fitted. The inherent capacitance of the surge arrester was simulated by two parallel capacitors in the Surge Arrester module. The parameter settings are shown in Table 1.

[0041] Table 1. Surge arrester parameter settings

[0042] To simulate the operating characteristics of surge arresters under real-world conditions, this embodiment constructs a 10kV "Type I" three-phase distribution line simulation model containing 12 MOA sets, as follows: Figure 5 As shown in Table 2, the surge arresters are numbered #1 to #12 from the first segment (power supply end) to the last segment (load end). The location (distance from the power supply) of each surge arrester is set based on the actual power distribution line topology of a certain location, and the parameter settings are shown in Table 2.

[0043] Table 2. Location of each surge arrester

[0044] The power distribution line adopts a distributed parameter model, and the parameter settings are shown in Table 3.

[0045] Table 3. Line Parameter Settings

[0046] The lightning current model uses a double exponential wave current source to simulate lightning strikes. The waveform parameters are set to an 8 / 20μs standard lightning wave, the current amplitude is set to 10kA, and the start time is 0.02s to simulate a moderate-intensity induced lightning overvoltage.

[0047] S2: Analyze the spatiotemporal evolution of lightning strikes in power distribution lines based on simulation results, and select key monitoring nodes related to stress characteristics based on the spatiotemporal evolution.

[0048] S2.1: Analyze the spatiotemporal evolution of lightning strikes in power distribution lines based on simulation results.

[0049] In one specific implementation, the collective response characteristics of surge arresters under different lightning strike points are first analyzed. In order to obtain the spatial distribution law of line stress, three typical and representative lightning strike conditions are simulated, corresponding to lightning strikes at the beginning, middle and end of the line, respectively.

[0050] S2.1.1: Operating Condition 1: Overvoltage Intrusion Response Characteristics on the Power Supply Side.

[0051] Specifically, this operating condition simulates a lightning strike occurring at the beginning of the line, specifically before surge arrester #1, mimicking a scenario where a lightning surge enters the distribution line from the substation's power supply side. Simulation waveforms show that surge arrester #1 instantaneously experiences the highest impulse voltage amplitude and energy discharge pressure along the entire line, with the steepest voltage rise, fully preserving the high-frequency components of the lightning surge. As the traveling wave propagates towards the end of the line, due to the attenuation effect of the line impedance and the shunting effect of the surge arresters along the line, the voltage stress experienced by subsequent surge arresters, including surge arrester #2 (only 0.39 km away) and subsequent nodes #3 to #12, exhibits a significant exponential decrease with increasing electrical distance. This operating condition indicates that surge arrester #1 is the only sensitive node for capturing operational overvoltages and lightning surges from the upstream power grid. Without monitoring of this point, the system cannot obtain the initial boundary conditions for stress inversion across the entire line, leading to an inability to accurately distinguish between external intrusion and internal induced overvoltage. Therefore, surge arrester #1 is established as the key monitoring point at the beginning of the line.

[0052] S2.1.2: Operating Condition 2: Verification of Line Transmission Attenuation and Monitoring Blind Zone.

[0053] Specifically, in this operating condition, the lightning strike occurs in the geometric center region of the line, meaning the overvoltage peak between arresters #6 and #7 is concentrated at arresters #6 and #7 in the middle section of the line, with the peak at this central region, rapidly attenuating towards both ends of the line. Simulation waveforms show that, comparing the voltage waveforms of arresters #1 at the beginning and #12 at the end, due to line resistance and ground conductance losses, the residual voltage amplitude measured at the edge nodes is significantly lower than that in the central region, only 40%-50% of the peak value in the central region. This operating condition indicates that if monitoring is only conducted at the beginning and end, a strong lightning strike in the middle section can easily be smoothed out as a minor disturbance when it propagates to the edge. The middle section of the line becomes a blind spot for state perception, easily misjudging a strong lightning strike in the middle section as a minor disturbance at the far end. This leads to a serious underestimation of the aging condition of the arresters in the middle region. Therefore, the #6 surge arrester located at the electrical center is selected as the key mid-section monitoring point to support the accuracy of the overall line state inversion. This reduces the maximum electrical distance from any non-monitoring point to the monitoring point to less than half of the total length, significantly reducing the distance error of the spatial interpolation algorithm.

[0054] S2.1.3: Operating Condition 3: Terminal Traveling Wave Reflection Superposition Effect Specifically, this operating condition simulates a lightning strike occurring at the end of the line, specifically behind surge arrester #12, mimicking the transmission of a traveling wave from lightning to the line's end. The simulation waveforms show that surge arrester #12 experiences extremely high voltage stress, with its residual voltage amplitude and tail energy significantly higher than neighboring nodes. Since the ends of 10kV lines typically exhibit high impedance or open-circuit characteristics, the traveling wave undergoes positive reflection upon reaching the end, resulting in a doubling of the voltage amplitude due to the superposition of the incident and reflected waves. This operating condition indicates that surge arrester #12, affected by the traveling wave reflection mechanism, is the weakest link in the entire line, with the lowest insulation margin and the highest risk of aging. Therefore, surge arrester #12 represents an extreme operating condition and must be closely monitored to capture the extreme stress values ​​caused by the reflection effect, avoiding overlooking the most serious aging risks. Thus, surge arrester #12 is established as a key monitoring point at the end of the line.

[0055] S2.2: Select key monitoring nodes related to stress characteristics based on spatiotemporal evolution laws.

[0056] S2.2.1: Extract the maximum voltage amplitude of each surge arrester node under different lightning strike locations based on simulation data, and draw the stress distribution envelope diagram of the entire line.

[0057] In one specific implementation, by combining simulation data from the three typical operating conditions described above, the maximum voltage amplitude of each surge arrester node under different lightning strike locations is extracted, and a stress distribution envelope diagram of the entire line is plotted as follows: Figure 6 As shown.

[0058] S2.2.2: Analyze the stress envelope characteristics of the stress distribution envelope diagram of the entire line, and determine the key monitoring nodes based on the principle of maximizing the stress coverage range and minimizing the interpolation distance error.

[0059] In one specific implementation, analysis Figure 6 The stress envelope characteristics are shown in the red curve, which represents the head-end effect. Surge arrester #1 can capture all extreme overvoltage intrusions from the power supply side. The blue curve represents the tail-end effect, where surge arrester #12 can capture extreme reflected overvoltages at the end of the line. The green curve represents the mid-section support effect; surge arrester #6, located at the electrical center of the line, connects the stress transformation trends at the head and tail.

[0060] In this embodiment, maximizing stress coverage means ensuring that the monitoring points can capture the extreme values ​​and boundary conditions of the voltage stress across the entire line, i.e., without missing the range of the most severe operating conditions. This is reflected in the selection of surge arresters #1 and #12. #1, according to the red curve in the simulation, can capture all extreme values ​​of input overvoltage intrusion from the power supply side. #12, according to the blue curve in the simulation, is the point with the lowest insulation margin and the highest aging risk due to the traveling wave reflection effect; therefore, it can capture extreme values ​​of reflected overvoltage.

[0061] Minimizing interpolation distance error refers to shortening the electrical distance between any calculation point and the nearest monitoring point through reasonable point placement. Since the error of spatial interpolation algorithms typically increases with distance, shorter distances result in higher inversion accuracy. This is reflected in the selection of surge arrester #6. Because #6 is located at the electrical center of the line and is a key point connecting the stress transformation trends at the beginning and end (represented by the peak of the green curve), introducing #6 can reduce the maximum electrical distance from any non-monitoring point to a monitoring point along the entire line to within 25% of the total line length. This significantly reduces the distance error of the spatial interpolation algorithm, providing support for calculation accuracy.

[0062] Maximizing stress coverage is fundamental and a prerequisite, thus having higher priority. Therefore, if there is a conflict between coverage and distance error, the principle of maximizing stress coverage takes precedence. It is essential to prioritize locking the first and last nodes to capture input and reflection stress extrema, establish the physical boundary conditions for inversion, and prevent the omission of the most critical operating conditions. Based on this, distance error is crucial for accuracy. By introducing mid-section nodes to eliminate mid-section sensing blind spots, the inversion interpolation radius is reduced to a minimum, thereby maximizing the numerical accuracy of state estimation while ensuring the integrity of the physical boundaries.

[0063] Therefore, based on the principle of maximizing stress coverage and minimizing interpolation distance error, this embodiment selects three sets of surge arresters—#1 at the beginning, #6 in the middle, and #12 at the end—as key monitoring points. Monitoring point #1 serves as the topological reference, responsible for monitoring input stress on the substation side. Monitoring point #12 serves as the boundary reference, responsible for monitoring reflected stress at the end. Monitoring point #6 serves as the interpolation anchor point, reducing the maximum electrical distance from any non-monitoring point to the monitoring point to within 25% of the total line length, thus providing support for the accuracy of spatial inversion calculations.

[0064] S3: Collect multidimensional status data at key monitoring nodes. The multidimensional status data and the physical structure data of the power distribution line constitute a heterogeneous dataset, and the heterogeneous dataset is preprocessed.

[0065] Flowchart as follows Figure 7 As shown, the specific steps include: S3.1: Construct heterogeneous datasets.

[0066] In one specific implementation, to achieve the mapping from discrete monitoring points to the continuous state of the entire line, this embodiment first needs to construct a standardized input dataset, consisting of two heterogeneous data parts. The first part is a static topology set describing the physical structure of the distribution line. , is represented as: (3).

[0067] in, For the entire line The equipment number of each surge arrester. The corresponding electrical location coordinates (distance between each surge arrester tower and the substation). This is the initial factory leakage current reference value for the equipment.

[0068] The second part consists of high-frequency sensor data streams originating from key monitoring points. , is represented as: (4).

[0069] in, Use timestamps for data collection to ensure time sequence alignment of multi-source data. This refers to the raw observation value of leakage current collected in real time by the sensor. The ambient temperature data is recorded synchronously for subsequent temperature drift correction of the leakage current. For the first The overvoltage action and arc oscillation frequency at key monitoring points reflect the equipment's arc extinguishing recovery capability and insulation fatigue degree after being subjected to transient impacts. The equipment number for the surge arrester at the monitoring point is the equipment number for the entire line, where Set of equipment numbers belonging to key monitoring points It is a key sensing node determined based on the characteristics of line overvoltage distribution. In this embodiment... Defined as: (5).

[0070] S3.2: Preprocess heterogeneous datasets.

[0071] In one specific implementation, due to the complex electromagnetic environment of the power distribution network, the raw sensor data contains transient electromagnetic noise, which manifests in the time domain as non-periodic, high-frequency spikes with randomly changing amplitudes, masking the true steady-state trend of the surge arrester's leakage current. Therefore, this embodiment constructs a data cleaning module, first utilizing overvoltage action and arc oscillation frequency... Perform validity-based splitting on the original data stream, when a certain time period When the equipment is determined to be in a non-steady state of arc reignition or severe oscillation, then... The data from this period contains a large number of high-frequency components and cannot accurately reflect insulation aging. Therefore, the data from this period is marked as invalid samples and removed from steady-state calculations.

[0072] For the selected steady-state period data, the high-frequency sampled discrete data stream is mapped to a daily-scale steady-state feature vector to filter out high-frequency transient interference and extract long-period trend components that can truly characterize the health status of the equipment. For the first... The feature vector of a monitoring point on a certain day The definition is as follows: (6).

[0073] in, The arithmetic mean of the leakage current for the day is obtained by averaging the sampling points throughout the day and using the low-pass filtering principle to eliminate random high-frequency noise with a mean of zero, thereby extracting a stable fundamental amplitude of the leakage current. This represents the cumulative number of oscillations on that day, reflecting the dynamic fatigue characteristics of the equipment. The average ambient temperature for the day is used to provide environmental parameters for the subsequent establishment of a current-temperature correlation correction model.

[0074] S4: Using a spatial inversion strategy based on isomorphic field theory, the preprocessed heterogeneous dataset is inverted across the entire path and its state is assessed to obtain the final health status assessment results.

[0075] S4.1: Based on the stress field distribution reconstructed from the preprocessed heterogeneous dataset, multi-dimensional inversion of current, temperature, and fluctuation number is performed, including normalized current inversion based on temperature correction, relative temperature rise inversion, and fluctuation number inversion.

[0076] In one specific implementation, to obtain the operational status of all calculated points along the entire line, this embodiment proposes and constructs a theoretical model of an "electric-thermal-mechanical isomorphic field." Since surge arresters on distribution lines are not isolated entities but rather coupled nodes sharing the same voltage traveling wave transmission path, the spatial continuity of the power frequency voltage and overvoltage traveling waves distributed along the line leads to a strong correlation between the electrical stress levels of adjacent nodes. High electrical stress inevitably induces high leakage current, resulting in higher Joule heat loss and more severe dynamic oscillations under impact. Therefore, the current distribution field, temperature rise distribution field, and dynamic fatigue distribution field are spatially geometrically isomorphic. Based on the stress field distribution reconstructed from monitoring point data, the insulation, thermal, and dynamic states of the entire line can be simultaneously inverted, with inversions performed on the three dimensions of current, temperature, and the number of fluctuations.

[0077] S4.1.1: Temperature-corrected normalized current inversion.

[0078] Specifically, zinc oxide resistance elements exhibit negative temperature resistance characteristics; as ambient temperature increases, the resistive current naturally increases. To eliminate the environmental thermal effect, the Arrhenius reaction rate equation is used to calculate the measured steady-state current. Corrected to Standard reference temperature: (7).

[0079] in, For the first The standard leakage current corrected for each key monitoring point. This is a temperature correction factor, reflecting the temperature sensitivity of the valve plate material; a typical value is used. .

[0080] After obtaining the corrected steady-state current, directly spatial interpolating the measured leakage current value will result in significant errors due to the dispersion of the initial values ​​of different surge arresters. Therefore, this embodiment proposes a spatial inversion strategy of "correction-normalization-interpolation-restore". First, a dimensionless aging factor is defined. To characterize the relative deterioration of monitoring points, initial individual differences are eliminated through normalization calculations: (8).

[0081] in, Indicates the first in the circuit The initial factory leakage current reference value of the surge arrester at each key monitoring point.

[0082] Based on the physical law of electromagnetic field stress attenuation with distance, an inverse distance-weighted (IDW) model is further constructed. For any unmonitored line segment... Aging factors of surge arresters It is derived from the weighted sum of aging factors at all monitoring points: (9).

[0083] in, This is used for spatial weighting. According to potential distribution theory, the closer the distance to the monitoring point, the more similar the overvoltage intrusion waveform and the closer the aging trend. Therefore, the distance between the monitoring point and the calculated point is considered. The relationship is: (10).

[0084] Finally, using the initial factory leakage current reference value of the calculation point itself, the calculated aging factor is inversely transformed into the predicted current value of that node. : (11).

[0085] This current inversion process utilizes the environmental stress information transmitted by the monitoring points while preserving the inherent properties of the calculation points themselves.

[0086] S4.1.2: Relative temperature rise inversion.

[0087] Specifically, the heat generated by the surge arrester consists of two parts: the ambient reference temperature and the internal fault-generated heat. Since the surge arrester at the calculation point lacks an independent temperature sensor, this embodiment constructs an ambient reference temperature and extracts group statistical characteristics to inversely calculate the relative temperature rise of each surge arrester at the calculation point.

[0088] Assuming that within the same micrometeorological region, the temperature of a healthy surge arrester is the lowest and closest to the air temperature. Therefore, the optimal individual among the monitoring points is used as the environmental reference frame to avoid reference drift caused by the heating of individual monitoring points. A reference environmental temperature is defined for the entire line. for: (12).

[0089] in, This represents the average ambient temperature of the day, and the relative temperature rise. This reflects the intensity of the heat source caused by an internal anomaly in the surge arrester leading to a fault. The relative temperature rise of the surge arrester at each monitoring point is defined as: (13).

[0090] In isomorphic fields, the Joule heating effect is more pronounced in regions of concentrated electrical stress, thus the temperature rise distribution also follows a spatial attenuation law. Based on spatial interpolation of the relative temperature rise at monitoring points, the relative temperature rise of the surge arrester at the estimated point is predicted. : (14).

[0091] S4.1.3: Fluctuation frequency inversion.

[0092] Specifically, the frequency of oscillations characterizes the frequency of arc reignition and dynamic recovery capability of equipment under transient impacts. Lightning surge waves propagate along lines in the form of traveling waves, causing a collective impact on equipment within a certain area. When high-frequency oscillations are recorded at all monitoring points, it indicates that the section is in an active lightning zone. Although the estimated point in the middle of this section was not directly monitored, its electromagnetic environment and the impact stress level experienced by its equipment are comparable to those of adjacent monitoring points, and it can be considered to have experienced a similar intensity of dynamic impact accumulation. Therefore, by inverting the frequency of oscillations at the monitoring points, the frequency of oscillations at the estimated point's surge arrester can be predicted through spatial interpolation. : (15).

[0093] S4.2: Perform non-uniform hierarchical state assessment on multi-dimensional inversion.

[0094] S4.2.1: Defines the safety margin of the leakage current of the surge arrester, which characterizes the static insulation level of the surge arrester.

[0095] In one specific implementation, to comprehensively evaluate the surge arrester's condition, a comprehensive assessment is conducted based on three dimensions: predicted leakage current, relative temperature rise, and number of fluctuations. The safety margin of the surge arrester's leakage current is defined as the range from its initial factory state to a limiting threshold, characterizing the arrester's static insulation level. In this embodiment, the limiting threshold is set according to industry standard GB / T 11032-2020. for Therefore, regarding the first For each surge arrester calculated at a certain point, the safety margin consumption rate is defined as: (16).

[0096] in, The larger the value, the more safety margin the surge arrester consumes, and the worse its operating condition.

[0097] S4.2.2: The rate of loss of the safety margin of the surge arrester leakage current is determined according to the design non-uniform five-level state judgment standard.

[0098] In one specific implementation, the relative temperature rise characterizes the degree of thermal stability defect of the surge arrester, the number of fluctuations characterizes the degree of deterioration of the surge arrester's arc extinguishing performance, and the larger the corresponding index, the worse the operating condition.

[0099] Based on the above three dimensions, this embodiment designs a non-uniform five-level state judgment standard, as shown in Table 4.

[0100] Table 4. Criteria for Judging Non-Uniform Five-Level State

[0101] Table 4 illustrates the nonlinearity of the interval division, defining each judgment interval as wide at the beginning and narrow at the end to adapt to the accelerated aging process. In the early stages of aging, a wider judgment interval is provided to tolerate measurement errors and minor environmental disturbances. However, in the middle and later stages of aging, the judgment interval gradually narrows, making the transitions between state levels more sensitive, thus providing a strong early warning signal when the surge arrester approaches the failure threshold.

[0102] S4.2.3: Perform state assessment on the inversion results based on the non-uniform five-level state assessment criteria.

[0103] In one specific implementation, the order of AEs is set in a positive order, with the risk index gradually increasing. Based on this judgment standard, the final state level of the surge arrester is determined by the maximum value of the three dimensions. That is, after the three dimensions are determined, the level with the largest risk index is selected as the current final state level of the surge arrester. This strategy can effectively avoid the masking effect of low-risk indicators covering high-risk indicators in the traditional weighted average algorithm, and ensure that the system maintains the highest sensitivity to various potential faults.

[0104] Table 5. Data from the projection

[0105] The operational data of 12 surge arresters on a 10kV distribution line of a power company in Jiangsu Province from July 10, 2025 to September 1, 2025 were used as the input dataset for the surge arrester group state inversion and judgment model to reconstruct the state of the entire line. Surge arresters #1, #6, and #12 were selected as monitoring points to calculate the operating state level of the remaining surge arresters, and the calculated data is shown in Table 5.

[0106] Taking leakage current as an example, the predicted value of the surge arrester at the calculation point and the actual value of the operating data were compared, and the error was calculated to be 1.9%. The fitted curve obtained from the calculation is shown below. Figure 8 As shown, by Figure 8 Analysis shows that all sample points are closely distributed near the ideal diagonal, with no obvious outliers. The error in predicting the leakage current is 1.9%. Using the actual data values, calculate the actual state level of the predicted points according to the state assessment criteria in Table 4, and compare it with the predicted state levels in Table 5 to calculate their consistency. : (17).

[0107] in, To estimate the number of surge arresters whose rating is exactly the same as the actual rating, This represents the total number of surge arresters estimated. Therefore, the accuracy rate of state level determination for all estimated points in this example is 100%, thus verifying the reliability of the method.

[0108] This embodiment proposes a method for inverting and analyzing the group state of surge arresters in distribution lines based on key node monitoring. Addressing the pain points of high cost of full-scale monitoring, low efficiency of manual inspection, and narrow coverage of single-point monitoring in current distribution network surge arrester operation and maintenance, it provides a complete, low-cost, and high-precision solution. Through electromagnetic transient simulation modeling, isomorphic field theory construction, and multi-dimensional analysis strategy design, the following main conclusions are drawn: 1) The spatiotemporal evolution of lightning surge waves on a 10kV distribution line was analyzed using MATLAB / Simulink simulation. The results show that the line head bears the extreme value of the intrusion overvoltage from the power source side, the line tail bears the extreme value of the traveling wave reflection overvoltage, and the line electrical center is the key support point connecting the head and tail stress attenuation. These three points were selected as key monitoring points to construct a stress field covering the entire line, effectively avoiding the monitoring blind spots caused by traditional random point selection and providing complete boundary conditions for the overall line state inversion.

[0109] 2) It breaks through the limitations of single electrical quantity inversion and establishes a spatial isomorphic mapping relationship between current field, temperature field and dynamic stress field. A regional inversion algorithm based on leakage current, temperature rise and fluctuation number is proposed. In the absence of independent environmental reference and full-line monitoring, it successfully realizes accurate inference of the insulation aging, internal heating and dynamic fatigue of 12 sets of surge arresters in the whole line from the data of 3 monitoring points.

[0110] 3) A three-dimensional diagnostic index was designed, including insulation margin depletion rate, relative temperature rise, and fluctuation frequency. Based on the accelerated aging law of equipment, a non-uniform grading standard was formulated; and a maximum value envelope decision strategy based on the short-board effect was adopted to effectively avoid the masking effect of low-risk indicators covering high-risk indicators, and to effectively avoid the omission of early weak defects and sudden faults in the surge arrester group of distribution lines, thus achieving high-sensitivity early warning of faults.

[0111] Example 2: Embodiment 2 of the present invention provides a surge arrester group health status assessment system based on critical node monitoring, comprising: The simulation module is configured to perform electromagnetic transient simulation of the power distribution line under test based on the group parameters of the surge arrester under test; The key point screening module is configured to analyze the spatiotemporal evolution of lightning impacts in power distribution lines based on simulation results, and screen key monitoring nodes related to stress characteristics based on the spatiotemporal evolution. The dataset construction module is configured to collect multidimensional status data at key monitoring nodes. The multidimensional status data and the physical structure data of the power distribution line constitute a heterogeneous dataset, and the heterogeneous dataset is preprocessed. The state assessment module is configured to use a spatial inversion strategy based on isomorphic field theory to perform full-path inversion and state assessment on the preprocessed heterogeneous dataset, and obtain the final health status assessment result.

[0112] Example 3: Embodiment 3 of the present invention provides a computer-readable storage medium storing a computer program adapted for loading by a processor and executing the steps in the surge arrester group health status assessment method based on critical node monitoring as described in Embodiment 1 of the present invention.

[0113] Example 4: Embodiment 4 of the present invention provides a computer device, the device comprising: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the steps in the surge arrester group health status assessment method based on critical node monitoring as described in Embodiment 1 of the present invention.

[0114] The steps and methods involved in Examples 2, 3 and 4 above correspond to those in Example 1. For specific implementation details, please refer to the relevant description section of Example 1.

[0115] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application. In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, an optical medium, or a semiconductor medium, etc. The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for assessing the collective health status of surge arresters based on key node monitoring, characterized in that, Includes the following steps: Electromagnetic transient simulation of the power distribution line under test is performed based on the group parameters of the surge arrester under test. Based on the simulation results, the spatiotemporal evolution of lightning impacts in power distribution lines is analyzed, and key monitoring nodes related to stress characteristics are selected according to the spatiotemporal evolution. Multidimensional status data at key monitoring nodes are collected. The multidimensional status data and the physical structure data of the power distribution line constitute a heterogeneous dataset, and the heterogeneous dataset is preprocessed. By employing a spatial inversion strategy based on isomorphic field theory, a full-path inversion and state assessment are performed on the preprocessed heterogeneous dataset to obtain the final health status evaluation results.

2. The method for assessing the health status of surge arresters based on key node monitoring as described in claim 1, characterized in that, The specific steps for performing electromagnetic transient simulation of the distribution line under test based on the group parameters of the surge arrester under test are as follows: Analysis of the group state correlation mechanism of surge arresters based on the stress distribution characteristics of power distribution lines; A lightning impulse simulation model for distribution lines is constructed based on the state correlation mechanism of surge arresters. The lightning impulse simulation model for distribution lines includes a distribution line simulation model and a lightning current model.

3. The method for assessing the health status of surge arresters based on key node monitoring as described in claim 2, characterized in that, The lightning current model uses a double exponential wave current source to simulate lightning strikes, setting three lightning strike conditions: lightning strike at the beginning of the corresponding line, lightning strike in the middle of the corresponding line, and lightning strike at the end of the corresponding line.

4. The method for assessing the health status of surge arresters based on key node monitoring as described in claim 1, characterized in that, The specific steps for analyzing the arrester group state correlation mechanism based on the stress distribution characteristics of power distribution lines are as follows: Analysis of the nonlinear characteristics and aging properties of surge arresters; Analyze the voltage traveling wave conduction mechanism of power distribution lines under lightning strikes; Based on the nonlinear characteristics and aging properties of surge arresters and the voltage traveling wave conduction mechanism of distribution lines under lightning impact, a spatial mapping relationship between overvoltage energy dissipation and surge arrester aging is established.

5. The method for assessing the group health status of surge arresters based on key node monitoring as described in claim 1, characterized in that, The specific steps for screening key monitoring nodes related to stress characteristics based on spatiotemporal evolution laws are as follows: Based on the simulation data, the maximum voltage amplitude of each surge arrester node under different lightning strike locations was extracted, and the stress distribution envelope diagram of the entire line was drawn. The stress envelope characteristics of the stress distribution envelope diagram of the entire line are analyzed, and key monitoring nodes are determined based on the principle of maximizing stress coverage and minimizing interpolation distance error.

6. The method for assessing the group health status of surge arresters based on key node monitoring as described in claim 1, characterized in that, The specific steps for performing full-path inversion and state assessment on the preprocessed heterogeneous dataset using a spatial inversion strategy based on isomorphic field theory are as follows: Based on the stress field distribution reconstructed from the preprocessed heterogeneous dataset, multi-dimensional inversion of current, temperature, and fluctuation number is performed, including normalized current inversion based on temperature correction, relative temperature rise inversion, and fluctuation number inversion. A non-uniformly graded state assessment is performed on the multi-dimensional inversion.

7. The method for assessing the group health status of surge arresters based on critical node monitoring as described in claim 6, characterized in that, The specific steps for non-uniformly graded state assessment of multi-dimensional inversion are as follows: The safety margin of the leakage current of a surge arrester is defined to characterize the static insulation level of the surge arrester. The rate of loss of the safety margin of the surge arrester leakage current is determined according to the five-level non-uniform design condition assessment standard. The inversion results are assessed for state based on the non-uniform five-level state assessment criteria.

8. A surge arrester group health status assessment system based on key node monitoring, characterized in that, include: The simulation module is configured to perform electromagnetic transient simulation of the power distribution line under test based on the group parameters of the surge arrester under test; The key point screening module is configured to analyze the spatiotemporal evolution of lightning impacts in power distribution lines based on simulation results, and screen key monitoring nodes related to stress characteristics based on the spatiotemporal evolution. The dataset construction module is configured to collect multidimensional status data at key monitoring nodes. The multidimensional status data and the physical structure data of the power distribution line constitute a heterogeneous dataset, and the heterogeneous dataset is preprocessed. The state assessment module is configured to use a spatial inversion strategy based on isomorphic field theory to perform full-path inversion and state assessment on the preprocessed heterogeneous dataset, and obtain the final health status assessment result.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed as described in any one of claims 1-7: the surge arrester group health status assessment method based on critical node monitoring.

10. A computer device, characterized in that, include: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the surge arrester group health status assessment method based on critical node monitoring as described in any one of claims 1-7.

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