Methods, devices, electronic equipment and storage media for early warning of insulation status in power distribution networks

Abstract

This application provides a method, device, electronic device, and storage medium for early warning of insulation status in a distribution network. The method includes: acquiring the distribution network topology; determining single-index matrices at each level based on the distribution network topology and multiple insulation features, multiple equipment nodes, multiple line nodes, and multiple transformer substation nodes, thereby determining the degradation ratio coefficients of multiple insulation features at each level; determining the degradation weights of multiple insulation features at each level based on the degradation ratio coefficients at each level, and determining the electrical coupling influence matrix of the upstream node of the target node on the target node at each level, thereby determining the global comprehensive status index corresponding to each level where the target node is located; and determining the early warning level and outputting early warning information based on the global comprehensive status index corresponding to each level where the target node is located, according to a pre-configured distribution network insulation status level threshold.

Description

Technical Field

[0001] This application relates to the field of insulation condition early warning technology, and in particular to a method, device, electronic device, and storage medium for early warning of insulation condition in power distribution networks. Background Technology

[0002] As the final link in the power system, the distribution network directly undertakes the core task of transmitting electrical energy to users. The stability of its insulation state directly determines the reliability of power supply, the safety of grid operation, and the quality of electricity for users. With the continuous expansion of the distribution network scale and the widespread application of complex topologies such as radial and ring networks, the number of various insulating devices such as transformers, switchgear, cables, and surge arresters has surged. Multiple factors, including the operating environment, working conditions, and life cycle of each insulating device, can lead to the gradual deterioration of the equipment's insulation performance. If the insulation state is not determined in a timely and accurate manner and maintenance measures are not taken, it is very easy to cause faults such as insulation breakdown and short circuits, resulting in large-scale power outages and causing serious economic losses and social impacts.

[0003] While existing technologies for determining the insulation status of distribution networks are simple to operate and have low barriers to implementation, they are limited by their technical design concepts and cannot meet the needs of modern distribution networks for lean, intelligent, and comprehensive operation and maintenance. Summary of the Invention

[0004] In view of this, this application provides a method, device, electronic device and storage medium for early warning of insulation status of distribution network, which realizes timely early warning of insulation status of each node of distribution network and avoids large-scale power outages caused by insulation breakdown, short circuit and other faults.

[0005] In a first aspect, embodiments of this application provide a method for early warning of insulation status in a power distribution network, including: Obtain the distribution network topology, which includes multiple insulation features and multiple levels, including equipment level, line level, and transformer substation level. The equipment level includes multiple equipment nodes, the line level includes multiple line nodes, and the transformer substation level includes multiple transformer substation nodes. Based on the distribution network topology and the multiple insulation features, multiple equipment nodes, multiple line nodes, and multiple transformer substation nodes, determine the equipment-level single-index matrix, the line-level single-index matrix, and the transformer substation single-index matrix, respectively. Based on the equipment-level single index matrix, the line-level single index matrix, the transformer area-level single index matrix, and the hierarchy of the multiple insulation features, the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer area-level degradation ratio coefficient of the multiple insulation features are determined respectively. Based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer substation-level degradation ratio coefficient, the degradation weights of the multiple insulation features at each level are determined, and the electrical coupling influence matrix of the upstream node of the target node on the target node at each level is determined. Based on the degradation weights corresponding to each level and the electrical coupling influence matrix of the upstream nodes of the target node on the target node in each level, the global comprehensive state index corresponding to each level where the target node is located is determined. Based on the global comprehensive status indicators corresponding to each level where the target node is located, the early warning level is determined according to the pre-configured distribution network insulation status level threshold and the early warning information is output.

[0006] Secondly, embodiments of this application provide a power distribution network insulation status early warning device, comprising: The matrix determination module is used to obtain the distribution network topology, which includes multiple insulation features and multiple levels, including equipment level, line level and transformer substation level, multiple equipment nodes, multiple line nodes and multiple transformer substation nodes. Based on the distribution network topology and the multiple insulation features, multiple equipment nodes, multiple line nodes and multiple transformer substation nodes, the module determines the equipment-level single index matrix, the line-level single index matrix and the transformer substation single index matrix respectively. The matrix determination module is also used to determine the equipment-level degradation ratio coefficient, line-level degradation ratio coefficient, and transformer-level degradation ratio coefficient of the multiple insulation features based on the equipment-level single index matrix, the line-level single index matrix, the transformer area-level single index matrix, and the hierarchy of the multiple insulation features, respectively. The matrix determination module is also used to determine the degradation weight of the multiple insulation features in each level based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer substation-level degradation ratio coefficient, and to determine the electrical coupling influence matrix of the upstream node of the target node on the target node in each level. The matrix processing module is used to determine the global comprehensive state index corresponding to each level of the target node based on the degradation weights corresponding to each level and the electrical coupling influence matrix of the upstream nodes of the target node on the target node in each level. The early warning output module is used to determine the early warning level and output early warning information based on the global comprehensive status indicators corresponding to each level where the target node is located, according to the pre-configured distribution network insulation status level threshold.

[0007] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions implementing the steps of the method as described in the first aspect when executed by the processor.

[0008] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method as described in the first aspect.

[0009] Fifthly, embodiments of this application provide a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0010] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the method as described in the first aspect.

[0011] The distribution network insulation status early warning method provided in this application constructs single-index matrices at three levels: equipment, lines, and transformer substations, and calculates the degradation ratio coefficient and degradation weight layer by layer. This enables a comprehensive and detailed assessment of the insulation status of nodes at different levels in the distribution network, avoiding the limitations of single-level assessment. Simultaneously, by quantifying the electrical coupling influence matrix of upstream nodes on the target node, the method integrates the node's own insulation degradation with the upstream-transmitted coupling degradation contribution, thereby obtaining a more accurate and forward-looking global comprehensive status index that better reflects actual operating conditions. This effectively improves the accuracy and foresight of insulation risk identification. Furthermore, the automatic generation and output of early warning information based on pre-configured level thresholds achieves efficient and automated processing from data acquisition and status assessment to early warning closed-loop, providing clear and quantitative decision support for maintenance personnel. This effectively reduces the risk of faults caused by insulation degradation in the distribution network, improving power supply reliability and intelligent operation and maintenance levels.

[0012] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0013] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This paper illustrates one of the flowcharts of a power distribution network insulation status early warning method according to an embodiment of this application; Figure 2 This is a second schematic flowchart illustrating an embodiment of a power distribution network insulation status early warning method according to this application; Figure 3 A structural block diagram of a power distribution network insulation status early warning device according to an embodiment of this application is shown; Figure 4 A structural block diagram of an electronic device according to an embodiment of this application is shown. Detailed Implementation

[0014] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0015] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0016] The distribution network insulation status early warning method provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0017] This application provides a method for early warning of insulation status in a distribution network. This method can be configured into a processor that is communicatively connected to the distribution network and insulation equipment. Therefore, the following explanation uses the processor as the execution entity to describe the relevant embodiments. Preferably, the embodiments of this application are applicable to distribution network systems. Figure 1 As shown, the method is implemented through steps 101 to 105: Step 101: The processor obtains the distribution network topology, which includes multiple insulation features and multiple levels, including equipment level, line level, and transformer substation level. The equipment level includes multiple equipment nodes, the line level includes multiple line nodes, and the transformer substation level includes multiple transformer substation nodes. Based on the distribution network topology and the multiple insulation features, multiple equipment nodes, multiple line nodes, and multiple transformer substation nodes, the controller determines the equipment-level single-index matrix, the line-level single-index matrix, and the transformer substation-level single-index matrix, respectively.

[0018] For example, the processor can obtain equipment ledgers, line connection relationships, and transformer substation affiliations from a power distribution network geographic information system, production management system, or real-time database. It then performs topology parsing to extract node sets and their connections at the equipment, line, and transformer substation levels, and associates each node with its insulation characteristics. Insulation characteristics can include insulation resistance values, leakage current, dielectric loss factor, insulation aging factor, etc. The equipment level can include circuit breakers, disconnectors, and transformers; the line level can include overhead lines or cable segments; and the transformer substation level can include distribution transformer substations, low-voltage substations, etc. Based on the parsed topology and characteristic data, the processor can construct three single-indicator matrices: an equipment-level single-indicator matrix, a line-level single-indicator matrix, and a transformer substation-level single-indicator matrix. Each matrix can be stored using sparse matrix storage to improve computational efficiency. Finally, the processor can output three two-dimensional numerical matrices for subsequent insulation status assessment, risk warning, or fault location analysis.

[0019] Step 102: Based on the equipment-level single index matrix, line-level single index matrix, transformer area-level single index matrix, and the hierarchy of multiple insulation features, the processor determines the equipment-level degradation ratio coefficient, line-level degradation ratio coefficient, and transformer area-level degradation ratio coefficient for each of the multiple insulation features.

[0020] The processor first sets a degradation baseline or health threshold for each insulation feature in the equipment-level, line-level, and transformer substation-level single-indicator matrices according to the hierarchical structure of the distribution network. For each level, the processor iterates through the values ​​of the same insulation feature across all nodes in the single-indicator matrix of that level and calculates the degradation ratio coefficient for each insulation feature at that level. The equipment-level degradation ratio coefficient reflects the proportion of a certain insulation feature's degradation at a certain equipment node relative to the total degradation of that feature across all equipment nodes; the line-level and transformer substation-level degradation ratio coefficients are calculated similarly. Finally, the processor can output the equipment-level, line-level, and transformer substation-level degradation ratio coefficients corresponding to each insulation feature to locate weak links and dominant degradation factors in different levels.

[0021] Step 103: The processor determines the degradation weight of multiple insulation features in each level based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer area-level degradation ratio coefficient, and determines the electrical coupling influence matrix of the upstream node of the target node on the target node in each level.

[0022] The processor first uses the determined insulation feature degradation ratio coefficients for each level as basic weights. Then, it weights and fuses these weights with the sensitivity or importance of each insulation feature to the overall insulation performance at that level, thus determining the degradation weight of each insulation feature at each level and obtaining weight vectors for equipment, line, and distribution area levels. Based on this, the processor, considering the radial or mesh topology of the distribution network, traces upstream from the target node along the power flow direction or electrical connection relationship to identify all upstream nodes. For each pair of upstream and downstream nodes, the processor uses an electrical coupling quantization model based on line impedance parameters, electrical distances between nodes, load current distribution, and the insulation feature degradation weights of each upstream node to calculate the electrical coupling influence matrix of each upstream node on the target node under specific insulation features.

[0023] Step 104: Based on the degradation weights corresponding to each level and the electrical coupling influence matrix of the upstream nodes of the target node on the target node in each level, the processor determines the global comprehensive state index corresponding to each level where the target node is located.

[0024] The processor first weights and aggregates the degradation weights of each insulation feature corresponding to the target node in its respective level with the measured or evaluated values ​​of these insulation features on the target node, calculating the intra-level degradation index for that level. Then, based on the current level and the determined electrical coupling influence matrix of upstream nodes on the target node, the processor superimposes the intra-level degradation indices of each upstream node according to the coupling influence coefficient, obtaining the coupling degradation contribution value transmitted from the upstream. The processor can then fuse the intra-level degradation index of the target node with the upstream coupling degradation contribution value according to a preset ratio coefficient, finally generating a global comprehensive status index for the target node at the corresponding level. This index is a dimensionless value between 0 and 1, comprehensively reflecting the insulation degradation level of the target node itself and the additional influence caused by upstream nodes through electrical coupling, used to assess the true health risk level of the node in the overall operation of the distribution network.

[0025] Specifically, the global comprehensive status index corresponding to each level where the target node is located can be determined by the fourth formula, which is:

[0026] Among them, P z K represents the global comprehensive state index corresponding to level z; zThis is the single-index matrix corresponding to the z-th level; Let be the degradation weight matrix of the insulation features at level z; For Hadama accumulation; Let be the electrical coupling influence matrix corresponding to the z-th node.

[0027] Step 105: Based on the global comprehensive status indicators corresponding to each level where the target node is located, the processor determines the warning level according to the pre-configured distribution network insulation status level threshold and outputs the warning information.

[0028] A threshold table for distribution network insulation status levels is pre-configured in the processor. This table divides the numerical range of the global comprehensive status index into multiple continuous intervals, each corresponding to a specific warning level. For each target node, the processor compares the global comprehensive status index value calculated at each level with the intervals in the threshold table to determine the warning level the node falls into at the current level. If the same target node has corresponding global comprehensive status indices at multiple levels, the processor can select the highest warning level among the multiple warning levels for the target node, or it can determine the warning level based on a preset level priority. After determining the warning level of the target node, the processor can also generate corresponding warning information and output it to the monitoring terminal of maintenance personnel, mobile inspection equipment, or the superior dispatch system through a human-machine interface, alarm log, message queue, or standardized communication protocol, thereby completing the closed-loop processing of insulation status warnings.

[0029] Thus, the distribution network insulation status early warning method provided in this application constructs single-index matrices at three levels—equipment, lines, and transformer substations—and calculates the degradation ratio coefficient and degradation weight layer by layer. This enables a comprehensive and detailed assessment of the insulation status of nodes at different levels in the distribution network, avoiding the limitations of single-level assessment. Simultaneously, by quantifying the electrical coupling influence matrix of upstream nodes on the target node, the method integrates the node's own insulation degradation with the upstream-transmitted coupling degradation contribution, thereby obtaining a more accurate and forward-looking global comprehensive status index that better reflects actual operating conditions. This effectively improves the accuracy and foresight of insulation risk identification. Furthermore, the automatic generation and output of early warning information based on pre-configured level thresholds achieves efficient and automated processing from data acquisition and status assessment to early warning closed-loop, providing clear and quantitative decision support for maintenance personnel. This effectively reduces the risk of faults caused by insulation degradation in the distribution network, improving power supply reliability and intelligent operation and maintenance levels.

[0030] In some embodiments, such as Figure 2 As shown, step 101 can be achieved through steps 1011 to 1012: Step 1011: The processor obtains the distribution network topology and constructs a directed topology association model.

[0031] The processor can obtain the distribution network topology from files such as the distribution network geographic information system or production management system. The distribution network topology includes all equipment nodes, line nodes, and transformer substation nodes, their connections, and electrical direction information. The processor then transforms the undirected connections between nodes into directed edges based on the power flow direction or a preset power supply path. In practical applications, the starting node is typically the power source, extending along the feeder trunk line towards the load side to determine the parent-child relationship between each pair of upstream and downstream nodes. The mapping between nodes and directed edges is stored using an adjacency list or sparse matrix. Based on this, the processor constructs a directed topology association model, which includes node sets, edge sets, and hierarchical affiliation mappings.

[0032] Step 1012: The processor determines the device-level single index matrix based on the topology association model, determines the line-level single index matrix based on the device-level single index matrix, and determines the substation-level single index matrix based on the device-level single index matrix and the line-level single index matrix.

[0033] Specifically, the processor first generates a device-level single-index matrix based on the set of device nodes and the insulation characteristics of each device in the constructed directed topology association model. Then, the processor calculates the device-level single-index matrix according to the membership relationship between device nodes and line nodes in the directed topology association model. For all device nodes included in each line node, for each insulation characteristic, methods such as weighted average, maximum value, or cumulative summation are used to calculate the corresponding insulation characteristic value for that line node, and the line-level single-index matrix is ​​determined. Similarly, the line-level single-index matrix undergoes similar calculations to determine the transformer substation-level single-index matrix.

[0034] In the above embodiments, the processor constructs a directed topological association model containing clear upstream and downstream relationships, and then, based on this model, sequentially derives the line-level single-index matrix from the device-level single-index matrix, and then derives the transformer substation-level single-index matrix from the line-level single-index matrix, thus realizing the structured transmission and layer-by-layer aggregation of multi-level insulation characteristic data of the distribution network. This method not only accurately reflects the electrical membership and power flow direction between nodes at different levels, providing a reliable topological foundation for subsequent calculations of degradation weights and electrical coupling influence matrices, but also effectively reduces data redundancy and computational complexity through a layer-by-layer recursive calculation method, avoiding information loss or error amplification caused by direct cross-level aggregation. This improves the accuracy and computational efficiency of insulation condition assessment, enhances the feasibility of the early warning method, and strengthens its adaptability to large and medium-sized distribution networks.

[0035] In some embodiments, step 1011 can be implemented by step 1011a: Step 1011a: The processor obtains the distribution network topology and determines the construction of a directed topology association model based on the first formula, which is:

[0036] Where G is the directed topological association model, V is the set of nodes, and E is the set of edges. d V is a set of device nodes. l V is the set of line nodes. t This is the set of nodes in the transformer area.

[0037] The above embodiments construct a mailbox topology model by expressing the three types of nodes in the distribution network—equipment nodes, line nodes, and transformer substation nodes—and their directed connections in a standardized and structured mathematical form. This allows the constructed finite topology model to clearly define the set boundaries and membership relationships of nodes at different levels, avoiding ambiguity in the topology description. It also provides a foundation for subsequent processors to automatically parse the power flow direction, upstream and downstream relationships, and hierarchical mapping between nodes, thereby improving the standardization and reusability of data processing in insulation condition assessment and facilitating the rapid configuration of early warning methods in different distribution network systems.

[0038] In some embodiments, step 1012 can be implemented by steps 1012a to 1012c: Step 1012a: The processor constructs a device-level single index matrix based on a directed topology association model, with multiple device nodes as rows and multiple insulation features as columns.

[0039] Specifically, the processor determines the device-level single-index matrix based on the directed topology association model and a pre-configured fifth formula. The fifth formula is:

[0040] Among them, K d For equipment-level single-index matrix; K d，ij Let be the single-index pass rate coefficient for the j-th type of insulation characteristic of the i-th equipment; m is the total number of equipment nodes; n is the total number of insulation characteristics; x d，ij x is the measured value of the j-th type of insulation characteristic of the i-th device node; d，ij，0 x is the initial value of the j-th type of insulation characteristic of the i-th device node; d，ij，th The health threshold for the j-th type of insulation characteristic of the i-th device node; The lifecycle impact factor is assigned a value according to the equipment node during the equipment commissioning phase; Operating environment impact factors; This refers to the operating condition influencing factor.

[0041] It should be noted that the measured values ​​x for each insulation characteristic mentioned in the fifth formula are...d，ij The original characteristic values ​​of each insulation feature are obtained, and then dimensionless and topologically corrected before being uniformly mapped to... The values ​​obtained after the interval are given. The total number of equipment nodes, specific data on operating environment impact factors, and operating condition impact factors involved in the fifth formula can all be determined based on the directed topological association model. Insulation characteristics and their total number, initial values ​​of each insulation characteristic, health thresholds of each insulation characteristic, operating environment impact factors for each device, and life-cycle impact factors are all pre-configured in the processor. The life-cycle impact factor reflects the insulation aging and degradation caused by the equipment's years of operation. It can be divided into stages: commissioning period / maintenance period / aging period / retirement period, with values ​​assigned separately. The operating environment impact factor reflects the environmental impacts of the equipment's operating environment, such as temperature, humidity, pollution level, corrosivity, and altitude. The operating environment impact factor is consistent with the regional node factor value and is unrelated to insulation characteristics. The operating condition impact factor reflects the real-time load rate, start-stop frequency, overvoltage, three-phase imbalance, and other operating condition impacts of the equipment. It is unrelated to insulation characteristics and is determined based on the equipment level and the equipment's load status.

[0042] Step 1012b: The processor constructs a line-level single-index matrix based on the device-level single-index matrix, with multiple line nodes as rows and multiple insulation features as columns.

[0043] The processor determines the line-level single-index matrix based on the device-level single-index matrix and the pre-configured sixth formula. The sixth formula is:

[0044] Among them, K l For line-level single-index matrix; K l，pj m is the single-index pass rate coefficient for the j-th type of insulation characteristics of the p-th line; l Total number of lines; For K l，pj Weighting coefficients; The single-index pass rate coefficient for the j-th type of insulation characteristics of the p-th line body; These are the weighting coefficients for the device aggregation features; U represents the number of device nodes on the p-th line; p Let K be the set of device nodes on the p-th line; d，ij is the single-index pass rate coefficient for the j-th type of insulation feature of the i-th equipment node; n is the total number of insulation features.

[0045] Specifically, when line p has a measured value of the j-th type of insulation characteristic, the single-index pass coefficient of the j-th type of insulation characteristic of line p is calculated using equation (1) in the sixth formula; when line p does not have a measured value of the j-th type of insulation characteristic, the single-index pass coefficient of the j-th type of insulation characteristic of line p is calculated using equation (2) in the sixth formula. The single-index pass coefficient of the j-th type of insulation characteristic of line p is obtained by calculating the equipment-level single-index matrix, and the equipment aggregate characteristic is:

[0046] In the sixth formula, the total number of lines, the number of device nodes on the p-th line, and the set of device nodes on the p-th line can all be determined based on the directed topology association model, while K l，pj The weighting coefficients for the device aggregation features and the weighting coefficients for the device aggregation features are preset in the processor.

[0047] Step 1012c: The processor constructs a transformer area-level single index matrix based on the device-level single index matrix and the line-level single index matrix, with multiple transformer area nodes as rows and multiple insulation features as columns.

[0048] The processor determines the area-level single-indicator matrix based on the line-level single-indicator matrix and the pre-configured seventh formula. The seventh formula is:

[0049] Among them, K t For a single-indicator matrix at the substation level; K t，qj m is the single-index pass rate coefficient for the j-th type of insulation characteristic of the q-th transformer substation; t is the total number of transformer substations; n is the total number of insulation characteristics; for Weighting coefficients; Let J be the insulation characteristic coefficient of the j-th type of main transformer equipment in the q-th distribution area. This insulation characteristic coefficient is the single index matrix of the equipment node. M represents the weighting coefficients for the aggregation features of the transformer area; l-q The number of lines under the jurisdiction of the q-th transformer substation; U represents the number of non-main transformer equipment nodes under the jurisdiction of the q-th distribution area; q K represents the number of line nodes and equipment nodes under the jurisdiction of the q-th transformer area; d，ij K is the single-index pass rate coefficient for the j-th type of insulation characteristic of the i-th equipment node. l，pj This is the single-index pass rate coefficient for the j-th type of insulation characteristic of the p-th line. The aggregation characteristic of the transformer substation is:

[0050] In the seventh formula, the total number of transformer substations, the j-th type insulation characteristic coefficient of the main transformer equipment in the q-th transformer substation, the number of lines under the jurisdiction of the q-th transformer substation, the number of non-main transformer equipment nodes under the jurisdiction of the q-th transformer substation, and the number of nodes under the jurisdiction of the q-th transformer substation can all be obtained based on the directed topological correlation matrix, while the two weight coefficients are pre-configured in the processor.

[0051] The main transformer equipment mentioned in the above embodiments usually refers to the distribution transformer. The main transformer equipment is the core equipment in the distribution area level. It is responsible for converting higher voltage level power into low voltage power suitable for user side use and undertakes functions such as voltage transformation, power distribution and fault isolation. Non-main transformer equipment refers to other equipment in the distribution area other than the main transformer, such as circuit breakers, disconnect switches, fuses, surge arresters, capacitors, low voltage distribution boxes and various line connection equipment.

[0052] In the above embodiments, the fifth formula introduces the full life cycle impact factor, operating environment impact factor, and operating condition impact factor into the equipment-level single-index matrix, enabling the single-index qualification coefficient of equipment insulation status to comprehensively reflect the dynamic impact of multiple factors such as aging, environment, and operating conditions. The sixth formula, in the line-level single-index matrix, rationally integrates the insulation characteristics of the line itself and its subordinate equipment through weighted coefficients, achieving effective aggregation of equipment information to the line level. The seventh formula, in the distribution area-level single-index matrix, further coordinates the contributions of the main transformer equipment, its subordinate lines, and other non-main transformer equipment, ensuring the comprehensiveness and coordination of the distribution area-level insulation assessment. This layer-by-layer, weighted fusion matrix construction method ensures the accurate transmission and scale uniformity of insulation characteristic data at each level, while avoiding data distortion caused by simple superposition or loss. This lays a solid foundation for the accurate calculation of subsequent degradation ratio coefficients, degradation weights, and global comprehensive status indicators, improving the quantitative assessment capability and engineering applicability of the distribution network insulation status early warning method in multi-level, multi-factor scenarios.

[0053] In some embodiments, step 102 can be implemented by steps 1021 to 1023: Step 1021: Based on the device-level single index matrix and multiple insulation features, the processor determines multiple first proportions of the multiple insulation features in the non-conforming nodes at the device level, and determines the device-level degradation ratio coefficient of the multiple insulation features based on the multiple first proportions.

[0054] Step 1022: Based on the line-level single index matrix and multiple insulation features, the processor determines multiple second proportions of multiple insulation features in the line-level unqualified nodes, and determines the line-level degradation ratio coefficient of multiple insulation features based on the multiple second proportions.

[0055] Step 1023: Based on the single index matrix at the substation level and multiple insulation features, the processor determines multiple third proportions of the non-conforming nodes of multiple insulation features at the substation level, and determines the substation-level degradation ratio coefficient of multiple insulation features based on the multiple third proportions.

[0056] Since the calculation methods for the first, second, and third ratios are the same, the calculation methods for the equipment-level degradation ratio coefficient, line-level degradation ratio coefficient, and transformer area-level degradation ratio coefficient are also the same. Therefore, the following section will briefly introduce the calculation process of the first ratio and the equipment-level degradation ratio coefficient. The calculation methods for the second ratio and the line-level degradation ratio coefficient, and the third ratio and the transformer area degradation ratio coefficient will not be elaborated further. The processor can traverse each column of all equipment nodes in the equipment-level single-index matrix according to the preset health thresholds for each insulation feature, and determine the number of equipment nodes whose insulation feature values ​​exceed the threshold range. This number is recorded as the number of unqualified equipment nodes. The number of unqualified equipment nodes is divided by the total number of equipment nodes to obtain the proportion of unqualified nodes for that insulation feature in the equipment level, which is recorded as the first ratio. For each insulation feature, the processor obtains a corresponding first ratio. Then, the processor uses the first ratio as the basic data vector to calculate the information entropy and weight of each insulation feature, and finally outputs a set of equipment-level degradation ratio coefficients to reflect the relative contribution of each insulation feature to the overall degradation state of the equipment level.

[0057] The above embodiments objectively quantify the relative contribution of different insulation characteristics to the overall degradation state at each level from a statistical distribution perspective, thereby avoiding biases caused by subjective weighting. The three levels employ the same calculation logic, ensuring the consistency and comparability of the degradation proportion coefficients. This provides a data-driven, adaptive quantitative basis for determining subsequent degradation weights and generating global comprehensive state indicators, thereby improving the versatility and accuracy of the early warning method under different distribution network structures and insulation characteristic combinations.

[0058] In some embodiments, step 103 can be implemented via step 1031: Step 1031: Based on the device-level degradation ratio coefficient, line-level degradation ratio coefficient, transformer area-level degradation ratio coefficient, and the pre-configured second formula, the processor determines the degradation weights of multiple insulation features at each level, and determines the electrical coupling influence matrix of the upstream node to the target node at each level based on the multiple insulation features and the pre-configured third formula. The second formula is:

[0059] in, This represents the degradation weight of the j-th type of insulation feature at the z-th level; The basic weights for the j-th type of insulation characteristics; , is the degradation percentage coefficient of the j-th type of insulation characteristic in the z-th layer; The basic weights for the k-th type of insulation characteristics; d is the degradation ratio coefficient of the k-th type of insulation characteristic in the z-th level; d is the equipment level identifier; l is the line level identifier; t is the transformer substation level identifier. The third formula is:

[0060] in, Let be the electrical coupling effect matrix of the upstream node degradation at level z on the i'th node; These are the weighting coefficients; for The total number of nodes in; is the average value of each insulation characteristic of the v-th node in the z-th level; Let be the set of upstream nodes of the i'th node in the z-th level; d is the device level identifier; l is the line level identifier; and t is the transformer substation level identifier.

[0061] The processor first calculates the degradation weight of each insulation feature in each level according to the second formula, and then quantifies the electrical coupling influence matrix of upstream nodes on target nodes in each level based on the third formula. The processor applies the third formula to the equipment level, line level, and transformer substation level respectively, thereby quantifying the transmission influence of the insulation degradation state of upstream nodes on downstream target nodes in the distribution network topology, and outputs the electrical coupling influence matrix of each target node in each level for subsequent fusion of global comprehensive status indicators.

[0062] The above embodiments achieve standardized calculation of degradation weight and electrical coupling influence matrix through pre-configured second and third formulas, thereby providing quantitative input that includes both feature importance and topological coupling relationship for the subsequent generation of global comprehensive status index, improving the physical rationality and calculation consistency of the early warning method in multi-level, multi-node complex distribution networks.

[0063] In some embodiments, step 1031 can be implemented by steps 1031a to 1031c: Step 1031a: The processor determines the first degradation weight of multiple insulation features in the device level based on the device-level degradation ratio parameter and the second formula, and determines the electrical coupling influence matrix of the upstream node of the target node on the target node in the device level based on the multiple insulation features and the third formula.

[0064] Step 1031b: The processor determines the second degradation weight of multiple insulation features in the line level based on the line-level degradation ratio parameter and the second formula, and determines the electrical coupling influence matrix of the upstream node of the target node on the target node in the line level based on multiple insulation features and the third formula.

[0065] Step 1031c: The processor determines the third degradation weight of multiple insulation features in the substation level based on the substation-level degradation ratio parameter and the second formula, and determines the electrical coupling influence matrix of the upstream node of the target node on the target node in the substation level based on multiple insulation features and the third formula.

[0066] Since the second formula is used to calculate each degradation weight, and the third formula is used to calculate the electrical coupling influence matrix of the upstream node of the target node at each level, this section will only introduce the process of determining the first degradation weight and then the electrical coupling influence matrix of the upstream node of the target node at the equipment level. The related calculations at the line level and transformer substation level will not be elaborated upon. Based on the previously calculated equipment-level degradation ratio coefficient, the processor uses the second formula to calculate the first degradation weight of multiple insulation features at the equipment level. Specifically, the numerator is obtained by multiplying the basic weight of the j-th type of insulation feature by the equipment-level degradation ratio coefficient, and the denominator is the sum of the products of the basic weights of all k types of insulation features and the equipment-level degradation ratio coefficient, thus obtaining the first degradation weight of the j-th type of insulation feature at the equipment level. The processor then identifies a target node in the device hierarchy and determines all upstream device nodes in the line where the target node is located based on the directed topology association model. It extracts the evaluation values ​​of each upstream device node on each insulation feature and calculates their mean. The pre-configured weight coefficient is then multiplied by the mean insulation feature of each upstream device node, divided by the total number of upstream device nodes, and the calculation results of all upstream device nodes are accumulated to obtain the electrical coupling influence matrix. Finally, the processor outputs the first degradation weight corresponding to each target node in the device hierarchy and the electrical coupling influence quantification matrix of the upstream device nodes on it, which are used for subsequent calculation of the global comprehensive state index of the device hierarchy.

[0067] The above embodiments employ a hierarchical, independent calculation approach with a unified formula within each level. This ensures consistency and comparability of the evaluation logic across different levels. Furthermore, it allows the degradation weights and electrical coupling influence matrices for each level to accurately reflect the unique node types, topological relationships, and insulation characteristic distributions of that level, avoiding information distortion caused by cross-level aliasing. Simultaneously, the calculation results from each level can be used to generate global comprehensive status indicators for the corresponding level, providing a more refined and modular quantitative basis for the final evaluation. This enhances the adaptability and computational accuracy of the early warning method in multi-layered heterogeneous distribution networks.

[0068] Furthermore, such as Figure 3As shown, as a specific implementation of the above-mentioned distribution network insulation status early warning method, this application embodiment provides a distribution network insulation status early warning device 300. The distribution network insulation status early warning device 300 includes: a matrix determination module 301, a matrix processing module 302, and an early warning output module 303.

[0069] The matrix determination module 301 is used to obtain the distribution network topology, which includes multiple insulation features and multiple levels, including equipment level, line level and transformer substation level, multiple equipment nodes, multiple line nodes and multiple transformer substation nodes. Based on the distribution network topology and multiple insulation features, multiple equipment nodes, multiple line nodes and multiple transformer substation nodes, the matrix determination module 301 determines the equipment-level single index matrix, the line-level single index matrix and the transformer substation single index matrix respectively.

[0070] The matrix determination module 301 is also used to determine the equipment-level degradation ratio coefficient, line-level degradation ratio coefficient, and transformer-level degradation ratio coefficient of multiple insulation features based on the equipment-level single index matrix, line-level single index matrix, transformer area-level single index matrix, and the hierarchy of multiple insulation features.

[0071] The matrix determination module 301 is also used to determine the degradation weights of multiple insulation features in each level based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer area-level degradation ratio coefficient, and to determine the electrical coupling influence matrix of the upstream node of the target node on the target node in each level.

[0072] The matrix processing module 302 is used to determine the global comprehensive state index corresponding to each level of the target node based on the degradation weights corresponding to each level and the electrical coupling influence matrix of the upstream nodes of the target node on the target node in each level.

[0073] The early warning output module 303 is used to determine the early warning level and output early warning information based on the global comprehensive status indicators corresponding to each level where the target node is located, according to the pre-configured distribution network insulation status level threshold.

[0074] In some embodiments, the matrix determination module 301 can obtain the distribution network topology and construct a directed topology association model.

[0075] The matrix determination module 301 can determine the equipment-level single index matrix based on the topology association model, determine the line-level single index matrix based on the equipment-level single index matrix, and determine the substation-level single index matrix based on the equipment-level single index matrix and the line-level single index matrix.

[0076] In some embodiments, the matrix determination module 301 can obtain the distribution network topology and determine the construction of a directed topology association model based on a first formula, which is:

[0077] Where G is the directed topological association model, V is the set of nodes, E is the set of edges, and V d V is a set of device nodes. l V is the set of line nodes. t It is a set of nodes in the transformer area.

[0078] In some embodiments, the matrix determination module 301 can construct a device-level single index matrix based on a directed topology association model, with multiple device nodes as rows and multiple insulation features as columns.

[0079] The matrix determination module 301 can also construct a line-level single index matrix based on the device-level single index matrix, with multiple line nodes as rows and multiple insulation features as columns.

[0080] The matrix determination module 301 can also construct a transformer substation-level single index matrix based on the equipment-level single index matrix and the line-level single index matrix, with multiple transformer substation nodes as rows and multiple insulation features as columns.

[0081] In some embodiments, the matrix determination module 301 can determine multiple first proportions of multiple insulation features in the equipment level of non-conforming nodes based on the equipment-level single index matrix and multiple insulation features, and determine the equipment-level degradation ratio coefficient of multiple insulation features based on the multiple first proportions.

[0082] The matrix determination module 301 can also determine multiple second proportions of multiple insulation features in the line level of unqualified nodes based on the line-level single index matrix and multiple insulation features, and determine the line-level degradation ratio coefficient of multiple insulation features based on the multiple second proportions.

[0083] The matrix determination module 301 can also determine multiple third proportions of unqualified nodes of multiple insulation features at the substation level based on the substation-level single index matrix and multiple insulation features, and determine the substation-level deterioration ratio coefficient of multiple insulation features based on the multiple third proportions.

[0084] In some embodiments, the matrix determination module 301 can determine the degradation weights of multiple insulation features at each level based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, the transformer area-level degradation ratio coefficient, and a pre-configured second formula, and determine the electrical coupling influence matrix of the upstream node of the target node on the target node at each level based on the multiple insulation features and a pre-configured third formula. The second formula is:

[0085] in, This represents the degradation weight of the j-th type of insulation feature at the z-th level; The basic weights for the j-th type of insulation characteristics; , is the degradation percentage coefficient of the j-th type of insulation characteristic in the z-th layer; The basic weights for the k-th type of insulation characteristics; d is the degradation ratio coefficient of the k-th type of insulation characteristic in the z-th level; d is the equipment level identifier; l is the line level identifier; t is the transformer substation level identifier.

[0086] The third formula is:

[0087] in, Let be the electrical coupling effect matrix of the upstream node degradation at level z on the i'th node; These are the weighting coefficients; for The total number of elements; is the average value of each insulation characteristic of the v-th node in the z-th level; Let be the set of upstream nodes of the i'th node in the z-th level; d is the device level identifier; l is the line level identifier; and t is the transformer substation level identifier.

[0088] In some embodiments, the matrix determination module 301 can determine the first degradation weight of multiple insulation features in the device level based on the device-level degradation ratio parameter and the second formula, and determine the electrical coupling influence matrix of the upstream node of the target node to the target node in the device level based on the multiple insulation features and the third formula. The matrix determination module 301 can determine the second degradation weight of multiple insulation features in the line level based on the line-level degradation ratio parameter and the second formula, and determine the electrical coupling influence matrix of the upstream node of the target node to the target node in the line level based on multiple insulation features and the third formula. The matrix determination module 301 can determine the third degradation weight of multiple insulation features in the transformer substation level based on the transformer substation degradation ratio parameter and the second formula, and determine the electrical coupling influence matrix of the upstream node of the target node on the target node in the transformer substation level based on multiple insulation features and the third formula.

[0089] The power distribution network insulation status early warning device in this application embodiment can be an electronic device or a component of an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the device.

[0090] The distribution network insulation status early warning device provided in this application embodiment can achieve... Figures 1 to 2 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0091] This application also provides an electronic device, such as... Figure 4 As shown, the electronic device 400 includes a processor 401 and a memory 402. The memory 402 stores a program or instruction that can run on the processor 401. When the program or instruction is executed by the processor 401, it implements the various steps of the above-described distribution network insulation status early warning method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0092] The memory 402 can be used to store software programs and various data. The memory 402 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 402 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 402 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0093] Processor 401 may include one or more processing units; optionally, processor 401 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 401.

[0094] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described distribution network insulation status early warning method embodiment and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0095] This application also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described distribution network insulation status early warning method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0096] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0097] This application also provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described distribution network insulation status early warning method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0098] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0099] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for early warning of insulation status in a distribution network, characterized in that, include: Obtain the distribution network topology, which includes multiple insulation features and multiple levels, including equipment level, line level, and transformer substation level. The equipment level includes multiple equipment nodes, the line level includes multiple line nodes, and the transformer substation level includes multiple transformer substation nodes. Based on the distribution network topology and the multiple insulation features, multiple equipment nodes, multiple line nodes, and multiple transformer substation nodes, determine the equipment-level single-index matrix, the line-level single-index matrix, and the transformer substation single-index matrix, respectively. Based on the equipment-level single index matrix, the line-level single index matrix, the transformer area-level single index matrix, and the hierarchy of the multiple insulation features, the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer area-level degradation ratio coefficient of the multiple insulation features are determined respectively. Based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer substation-level degradation ratio coefficient, the degradation weights of the multiple insulation features at each level are determined, and the electrical coupling influence matrix of the upstream node of the target node on the target node at each level is determined. Based on the degradation weights corresponding to each level and the electrical coupling influence matrix of the upstream nodes of the target node on the target node in each level, the global comprehensive state index corresponding to each level where the target node is located is determined. Based on the global comprehensive status indicators corresponding to each level where the target node is located, the early warning level is determined according to the pre-configured distribution network insulation status level threshold and the early warning information is output.

2. The method for early warning of insulation status in a distribution network according to claim 1, characterized in that, The process of obtaining the distribution network topology, determining a device-level single-index matrix based on the distribution network topology, determining a line-level single-index matrix based on the device-level single-index matrix, and determining a transformer substation-level single-index matrix based on the device-level single-index matrix and the line-level single-index matrix includes: Obtain the distribution network topology and construct a directed topology association model; The device-level single indicator matrix is ​​determined based on the topology association model, the line-level single indicator matrix is ​​determined based on the device-level single indicator matrix, and the substation-level single indicator matrix is ​​determined based on the device-level single indicator matrix and the line-level single indicator matrix.

3. The method for early warning of insulation status in a distribution network according to claim 2, characterized in that, The process of obtaining the distribution network topology and constructing a directed topology association model includes: The distribution network topology is obtained, and the directed topology association model is constructed based on a first formula, which is: Where G is the directed topological association model, V is the node set, E is the edge set, and V d V is the set of the device nodes. l V is the set of the line nodes. t This refers to the set of nodes in the transformer area.

4. The method for early warning of insulation status in a distribution network according to claim 2, characterized in that, The process of determining the device-level single-index matrix based on the topology association model, determining the line-level single-index matrix based on the device-level single-index matrix, and determining the transformer substation-level single-index matrix based on the line-level single-index matrix includes: Based on the directed topology association model, and with the multiple device nodes as rows and the multiple insulation features as columns, the device-level single index matrix is ​​constructed. Based on the device-level single index matrix, and with the multiple line nodes as rows and the multiple insulation features as columns, the line-level single index matrix is ​​constructed. Based on the equipment-level single-index matrix and the line-level single-index matrix, and with the multiple transformer area nodes as rows and the multiple insulation features as columns, the transformer area-level single-index matrix is ​​constructed.

5. The method for early warning of insulation status in a distribution network according to claim 1, characterized in that, The determination of the equipment-level degradation ratio coefficient, line-level degradation ratio coefficient, and transformer-level degradation ratio coefficient for the multiple insulation characteristics based on the equipment-level single-index matrix, the line-level single-index matrix, the transformer-area-level single-index matrix, and the hierarchy of the multiple insulation characteristics includes: Based on the equipment-level single index matrix and the multiple insulation features, a number of first proportions of the multiple insulation features in the equipment level are determined, and the equipment-level degradation ratio coefficient of the multiple insulation features is determined based on the multiple first proportions. Based on the line-level single index matrix and the multiple insulation features, a number of second proportions of the multiple insulation features in the line level are determined respectively, and the line-level degradation ratio coefficient of the multiple insulation features is determined based on the multiple second proportions. Based on the single index matrix at the transformer substation level and the multiple insulation features, a number of third proportions of the non-conforming nodes of the multiple insulation features at the transformer substation level are determined, and the transformer substation level degradation ratio coefficient of the multiple insulation features is determined based on the multiple third proportions.

6. The method for early warning of insulation status in a distribution network according to claim 1, characterized in that, The determination of the degradation weights of the multiple insulation features at each level based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer substation-level degradation ratio coefficient, and the determination of the electrical coupling influence matrix of the upstream node of the target node on the target node at each level, including: Based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, the transformer substation-level degradation ratio coefficient, and the pre-configured second formula, the degradation weights of the multiple insulation features in each level are determined. Based on the multiple insulation features and the pre-configured third formula, the electrical coupling influence matrix of the upstream node of the target node on the target node in each level is determined. The second formula is: in, This represents the degradation weight of the j-th type of insulation feature at the z-th level; The basic weights for the j-th type of insulation characteristics; , is the degradation percentage coefficient of the j-th type of insulation characteristic in the z-th layer; The basic weights for the k-th type of insulation characteristics; d represents the degradation percentage coefficient of the k-th type of insulation characteristic in the z-th level; d represents the equipment level identifier; l represents the line level identifier; t represents the transformer substation level identifier; The third formula is: in, Let be the electrical coupling effect matrix of the upstream node degradation at level z on the i'th node; These are the weighting coefficients; for The total number of elements; is the average value of each insulation characteristic of the v-th node in the z-th level; Let be the set of upstream nodes of the i'th node in the z-th level; d is the device level identifier; l is the line level identifier; and t is the transformer substation level identifier.

7. The method for early warning of insulation status in a distribution network according to claim 6, characterized in that, The process involves determining the degradation weights of multiple insulation features at each level based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, the transformer substation-level degradation ratio coefficient, and a pre-configured second formula. It also involves determining the electrical coupling influence matrix of the upstream node of the target node on the target node at each level based on the multiple insulation features and a pre-configured third formula, including: Based on the equipment-level degradation ratio parameter and the second formula, the first degradation weight of the plurality of insulation features in the equipment level is determined, and based on the plurality of insulation features and the third formula, the electrical coupling influence matrix of the upstream node of the target node on the target node in the equipment level is determined; Based on the line-level degradation ratio parameter and the second formula, the second degradation weight of the multiple insulation features in the line level is determined, and based on the multiple insulation features and the third formula, the electrical coupling influence matrix of the upstream node of the target node on the target node in the line level is determined. Based on the transformer substation-level degradation ratio parameter and the second formula, the third degradation weight of the plurality of insulation features in the transformer substation level is determined, and based on the plurality of insulation features and the third formula, the electrical coupling influence matrix of the upstream node of the target node on the target node in the transformer substation level is determined.

8. A power distribution network insulation status early warning device, characterized in that, include: The matrix determination module is used to obtain the distribution network topology, which includes multiple insulation features and multiple levels, including equipment level, line level and transformer substation level, multiple equipment nodes, multiple line nodes and multiple transformer substation nodes. Based on the distribution network topology and the multiple insulation features, multiple equipment nodes, multiple line nodes and multiple transformer substation nodes, the module determines the equipment-level single index matrix, the line-level single index matrix and the transformer substation single index matrix respectively. The matrix determination module is also used to determine the equipment-level degradation ratio coefficient, line-level degradation ratio coefficient, and transformer-level degradation ratio coefficient of the multiple insulation features based on the equipment-level single index matrix, the line-level single index matrix, the transformer area-level single index matrix, and the hierarchy of the multiple insulation features, respectively. The matrix determination module is also used to determine the degradation weight of the multiple insulation features in each level based on the equipment-level degradation ratio coefficient, the line-level degradation ratio coefficient, and the transformer substation-level degradation ratio coefficient, and to determine the electrical coupling influence matrix of the upstream node of the target node on the target node in each level. The matrix processing module is used to determine the global comprehensive state index corresponding to each level of the target node based on the degradation weights corresponding to each level and the electrical coupling influence matrix of the upstream nodes of the target node on the target node in each level. The early warning output module is used to determine the early warning level and output early warning information based on the global comprehensive status indicators corresponding to each level where the target node is located, according to the pre-configured distribution network insulation status level threshold.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that run on the processor, the program or instructions being executed by the processor to implement the steps of the distribution network insulation status early warning method as described in any one of claims 1 to 7.

10. A readable storage medium having a program or instructions stored thereon, characterized in that, When the program or instructions are executed by the processor, they implement the steps of the distribution network insulation status early warning method as described in any one of claims 1 to 7.

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