Topological change self-adaptive medium-voltage power distribution network cable insulation defect monitoring method

Abstract

The invention relates to the technical field of medium-voltage power distribution network cable online monitoring, in particular to a medium-voltage power distribution network cable insulation defect monitoring method, device and equipment and a computer storage medium. The medium-voltage power distribution network cable insulation defect monitoring method comprises the following steps: searching a power distribution network cable network terminal node according to an original node characteristic value matrix, combining the terminal node with an adjacent cable line from a power distribution network load terminal node, and calculating an equivalent characteristic value; and deleting the merged terminal nodes, simplifying the topological matrix and the eigenvalue matrix until the simplest eigenvalue matrix is obtained, calculating to obtain a frequency response function curve, and training to obtain a defect monitoring model. The medium-voltage cable insulation defect on-line monitoring method can realize on-line monitoring of the medium-voltage cable insulation defect under the conditions of complex topology and time varying of the power distribution network, has strong adaptability to topology change of the power distribution network, and only needs a small amount of actual power distribution network on-line monitoring data.

Description

Technical Field

[0001] The present invention relates to the technical field of on-line monitoring of medium-voltage distribution network cables, and in particular to a method, device, equipment and computer storage medium for monitoring insulation defects of medium-voltage distribution network cables. Background Art

[0002] With the continuous advancement of the urbanization process, the scale of the underground distribution network in China has gradually expanded. As the main energy transmission medium, the proportion of cables in the total length of distribution lines has also gradually increased. However, due to the special working environment of underground cables, irreversible insulation aging often occurs due to moisture absorption and overload heat effects, resulting in a decrease in insulation strength and breakdown voltage, and ultimately leading to line failures, endangering the safe and reliable operation of the distribution network. Therefore, in order to ensure the safe and reliable operation of cables, real-time monitoring of their insulation is particularly important.

[0003] At present, most studies focus on how to diagnose and locate cable faults, and methods based on traveling waves, model-based methods, and data-driven methods have been proposed. However, these methods can only cut off the faulty cable in time after the cable fault occurs, and have poor detection effects on complex cable network topologies. Although it can avoid the formation of serious cascading faults, it will still cause power outages in some areas, affecting normal industrial production and residents' lives. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the problem of poor monitoring effect of cable faults in the prior art.

[0005] To solve the above technical problem, the present invention provides a method for monitoring insulation defects of medium-voltage distribution network cables, including:

[0006] Obtaining the original eigenvalue matrix of the original distribution network cable topology diagram, including the original topology representation matrix, the original node load impedance matrix, the original node type matrix, the original cable unit length impedance matrix, and the original cable length matrix;

[0007] Circularly traversing and deleting the cable branches where the terminal nodes are located in the original distribution network cable topology diagram, and updating the eigenvalue matrix until the topology representation matrix reaches the simplest form, obtaining the simplest distribution network cable topology diagram and the corresponding simplest eigenvalue matrix;

[0008] Setting cable defects based on the simplest distribution network cable topology diagram, generating multiple distribution network cable topology diagrams with defects, repeating the above steps, obtaining the simplest eigenvalue matrices corresponding to the multiple distribution network cable topology diagrams with defects, and calculating the frequency response curves;

[0009] Training the defect monitoring model according to multiple groups of frequency response curves and the original eigenvalue matrix;

[0010] Input the frequency response curve of the actual medium-voltage distribution network cable and the original eigenvalue matrix into the trained defect monitoring model to obtain the monitoring result.

[0011] Preferably, obtaining the original eigenvalue matrix of the original distribution network cable topology map includes the original topology characterization matrix, the original node load impedance matrix, the original node type matrix, the original cable unit length impedance matrix, and the original cable length matrix, including:

[0012] Number each node in the original distribution network cable topology map, and generate the original topology characterization matrix according to the node connection relationship;

[0013] Obtain the time-varying curve of the power supply load at the cable end corresponding to the original distribution network cable topology map, and calculate the average equivalent impedance to generate the original node load impedance matrix;

[0014] Obtain the type of each node in the original distribution network cable topology map to generate the node type matrix;

[0015] Obtain the resistance per unit length, inductance per unit length, conductance per unit length, and capacitance per unit length of each cable in the distribution network corresponding to the original distribution network cable topology map to generate the original cable unit length impedance matrix, and generate the cable length matrix according to the length of each cable.

[0016] Preferably, obtaining the resistance per unit length, inductance per unit length, conductance per unit length, and capacitance per unit length of each cable in the distribution network corresponding to the original distribution network cable topology map to generate the original cable unit length impedance matrix includes:

[0017] Construct a two-dimensional matrix, where the element in the m-th row and n-th column represents the unit length characteristic impedance of the cable connecting node m and node n;

[0018] Calculate the unit length impedance Z of the cable connecting node m and node n according to the resistance per unit length, inductance per unit length, conductance per unit length, and capacitance per unit length of the cable connecting node m and node n mn :

[0019]

[0020] where R mn , G mn , L mn , C mn are respectively the resistance per unit length, conductance per unit length, inductance per unit length, and capacitance per unit length of the cable connecting node m and node n, j is the imaginary unit, and ω is the angular frequency.

[0021] Preferably, the original topology characterization matrix is the adjacency matrix of the cable topology.

[0022] Preferably, the criterion for determining that the topological characterization matrix reaches the simplest form is as follows:

[0023] When the node types of the columns with a sum of 1 in the topological characterization matrix are only the nodes for testing the frequency response curve, the topological characterization matrix reaches the simplest form.

[0024] Preferably, the steps of cyclically traversing and deleting the cable branches where the terminal nodes are located in each original distribution network cable topology diagram and updating the eigenvalue matrix until the topological characterization matrix reaches the simplest form, obtaining multiple simplest distribution network cable topology diagrams and corresponding simplest eigenvalue matrices include:

[0025] Step a: Obtain the equivalent load impedance of the current distribution network terminal node and the adjacent cable line, and delete the cable branch where the current distribution network terminal node is located in the current distribution network cable topology diagram;

[0026] Step b: Set the impedance values related to the current distribution network terminal node in the current node load impedance matrix to 0, update the impedance values of the nodes connected to the current distribution network terminal node in the current node load impedance matrix to the equivalent load impedance of the current distribution network terminal node and the adjacent cable line, and set the relevant columns of the current topological characterization matrix, the current node type matrix, the current cable unit length impedance matrix, and the current cable length matrix related to the current distribution network terminal node to 0;

[0027] Step c: Repeat steps a - c until the current topological characterization matrix reaches the simplest form.

[0028] Preferably, setting the cable defects based on the simplest distribution network cable topology diagram includes:

[0029] Set the cable defect segment characteristics including the starting position of the cable defect, the ending position of the cable defect, and the characteristic impedance of the cable defect segment based on the simplest distribution network cable topology diagram;

[0030] If the cable defect segment spans an existing main cable node, introduce a virtual node in the main cable.

[0031] The present invention also provides a medium - voltage distribution network cable insulation defect monitoring device, including:

[0032] An eigenvalue matrix acquisition module, configured to acquire the original eigenvalue matrix of the original distribution network cable topology diagram, including the original topological characterization matrix, the original node load impedance matrix, the original node type matrix, the original cable unit length impedance matrix, and the original cable length matrix;

[0033] A topology simplification module, which is used to traverse and delete the cable branches where the terminal nodes are located in the original distribution network cable topology diagram, and update the eigenvalue matrix until the topology representation matrix reaches the simplest form, so as to obtain the simplest distribution network cable topology diagram and the corresponding simplest eigenvalue matrix;

[0034] A training set generation module, which is used to set cable defects based on the simplest distribution network cable topology diagram, generate multiple distribution network cable topology diagrams with defects, repeat the above steps, obtain the simplest eigenvalue matrices corresponding to multiple distribution network cable topology diagrams with defects, and calculate the frequency response curves;

[0035] A model training module, which is used to train the defect monitoring model according to multiple groups of frequency response curves and the original eigenvalue matrix;

[0036] A defect monitoring module, which is used to input the frequency response curve and the original eigenvalue matrix of the actual medium-voltage distribution network cable into the trained defect monitoring model to obtain the monitoring result.

[0037] The present invention also provides a medium-voltage distribution network cable insulation defect monitoring device, including:

[0038] A memory, which is used to store computer programs;

[0039] A processor, which is used to implement the steps of the above-mentioned medium-voltage distribution network cable insulation defect monitoring method when executing the computer program.

[0040] The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned medium-voltage distribution network cable insulation defect monitoring method are implemented.

[0041] The above technical solution of the present invention has the following advantages compared with the prior art:

[0042] For the medium-voltage distribution network cable insulation defect monitoring method of the present invention, the terminal nodes of the distribution network cable network are found according to the original node eigenvalue matrix. Starting from the load terminal nodes of the distribution network, the terminal nodes are merged with the adjacent cable lines, and the equivalent eigenvalues are calculated; the merged terminal nodes are deleted, and the topology matrix and eigenvalue matrix are simplified until the simplest eigenvalue matrix is obtained and the frequency response function curve is calculated, and the defect monitoring model is trained. The present invention can realize the online monitoring of medium-voltage cable insulation defects under the complex and time-varying conditions of the distribution network topology, has strong adaptability to the change of the distribution network topology, and only requires a small amount of actual distribution network online monitoring data, improving the timeliness and accuracy of cable fault monitoring. Description of the Drawings

[0043] To make the content of the present invention easier to be clearly understood, the following further elaborates on the present invention in detail according to specific embodiments of the present invention and in conjunction with the accompanying drawings, where:

[0044] Figure 1 is the implementation flowchart of a method for monitoring cable insulation defects in a medium-voltage distribution network provided by the present invention;

[0045] Figure 2 is the implementation flowchart of a method for monitoring cable insulation defects in a medium-voltage distribution network provided by an embodiment of the present invention;

[0046] Figure 3 is the frequency response curve of a defective distribution network cable in an embodiment of the present invention. Specific embodiments

[0047] The core of the present invention is to provide a method, device, equipment and computer storage medium for monitoring cable insulation defects in a medium-voltage distribution network, effectively improving the timeliness and accuracy of cable fault monitoring.

[0048] To enable those skilled in the art to better understand the solution of the present invention, the following further elaborates on the present invention in detail in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0049] Please refer to Figure 1 , Figure 1 is the implementation flowchart of a method for monitoring cable insulation defects in a medium-voltage distribution network provided by the present invention; the specific operation steps are as follows:

[0050] S101: Obtain the original eigenvalue matrix of the original distribution network cable topology diagram, including the original topology representation matrix, the original node load impedance matrix, the original node type matrix, the original cable unit length impedance matrix, and the original cable length matrix;

[0051] S102: Traverse and delete the cable branches where the terminal nodes are located in the original distribution network cable topology diagram in a loop, and update the eigenvalue matrix until the topology representation matrix reaches the simplest form, obtaining the simplest distribution network cable topology diagram and the corresponding simplest eigenvalue matrix;

[0052] S103: Set cable defects based on the simplest distribution network cable topology diagram, generate multiple defective distribution network cable topology diagrams, repeat the above steps, obtain the simplest eigenvalue matrices corresponding to the multiple defective distribution network cable topology diagrams, and calculate the frequency response curve;

[0053] S104: Train the defect monitoring model based on multiple groups of frequency response curves and the original eigenvalue matrix;

[0054] S105: Input the frequency response curve and the original eigenvalue matrix of the actual medium-voltage distribution network cable into the trained defect monitoring model to obtain the monitoring result.

[0055] Please refer to Figure 2 , Figure 2 which is the implementation flowchart of a method for monitoring insulation defects of medium-voltage distribution network cables provided by an embodiment of the present invention.

[0056] Based on the above embodiments, this embodiment elaborates on step S101 in detail:

[0057] In some embodiments, draw a cable topology diagram according to the actual distribution network cable topology, number each node in the original distribution network cable topology diagram, record the total number of nodes as N, and generate an original topology representation matrix T0 according to the node connection relationship;

[0058] In one embodiment, the generated original topology representation matrix T0 is the adjacency matrix of the cable topology;

[0059] In a specific embodiment, the topology diagram drawn according to the actual distribution network cable topology contains 8 nodes and 8 cable lines, and the generated original topology representation matrix T0 is an 8×8 symmetric matrix containing 32 non-zero elements.

[0060] In some embodiments, obtain the time-varying curve of the power supply load at the cable end corresponding to the original distribution network cable topology diagram, calculate the average equivalent impedance, and generate an original node load impedance matrix Z0;

[0061] In one embodiment, the time-varying curve of the power supply load at the cable end includes the real part and the imaginary part curves of the equivalent, the average equivalent impedance is the average value of the time-varying load in a day, and the generated original node load impedance matrix Z0 is a vector with a length of N. If the node is a non-terminal node, the corresponding position of Z0 is recorded as 0.

[0062] In some embodiments, obtain the type of each node in the original distribution network cable topology diagram to generate a node type matrix K0;

[0063] In one embodiment, the node types in the original distribution network cable topology diagram include cable load terminal nodes, cable line branch point nodes, and frequency response curve test nodes. Among them, the node type of the cable load terminal is marked as 1, the node type of the cable line branch point is marked as 2, and the node type of the frequency response curve test node is marked as 3;

[0064] In a specific embodiment, the original distribution network cable topology diagram includes 2 frequency response curve tests, 2 cable load terminal nodes, and 4 cable line branch point nodes;

[0065] In a specific embodiment, the average equivalent impedance of the cable load terminal nodes is 180 + 0.02j.

[0066] In some embodiments, for each cable in the distribution network corresponding to the original distribution network cable topology diagram, the resistance per unit length R, inductance per unit length L, conductance per unit length G, and capacitance per unit length C are obtained, an original cable impedance matrix per unit length ZL0 is generated, and a cable length matrix L0 is generated according to the length of each cable;

[0067] In one embodiment, the original cable impedance matrix per unit length ZL0 is an N×N square matrix, where the element in the m-th row and n-th column represents the characteristic impedance per unit length Z of the cable connecting node m and node n mn of the cable connecting node m and node n, and the cable length matrix L0 is an N×N square matrix, where the element in the m-th row and n-th column represents the length of the cable connecting node m and node n, Z mn The calculation formula is:

[0068]

[0069] where R mn and G mn and L mn and C mn are respectively the resistance per unit length, conductance per unit length, inductance per unit length, and capacitance per unit length of the cable connecting node m and node n, j is the imaginary unit, and ω is the angular frequency;

[0070] In a specific embodiment, the cables are of the same type, R = 0.0142Ω, L = 7.5583e -8 and G = 3.3776e -5 and C = 4.972e -10 The cable lengths are respectively: 145m, 100m, 156m, 187m, 267m, 245m, 289m, 193m.

[0071] Based on the above embodiments, this embodiment details step S102:

[0072] In some embodiments, the cable branches where the terminal nodes are located in the original distribution network cable topology diagram are traversed and deleted in a loop, and the eigenvalue matrix is updated until the topological characterization matrix reaches the simplest form, obtaining the simplest distribution network cable topology diagram and the corresponding simplest eigenvalue matrix, including:

[0073] Step a: Obtain the equivalent load impedance Z′ of the current distribution network terminal node P and the adjacent cable line, and delete the cable branch where the current distribution network terminal node is located on the current distribution network cable topology map. Denote the node connected to the terminal node P as Q;

[0074] Step b: Set the impedance values related to the current distribution network terminal node in the current node load impedance matrix Z0 to 0, update the impedance value of the node Q connected to the current distribution network terminal node in the current node load impedance matrix to the equivalent load impedance Z′ of the current distribution network terminal node and the adjacent cable line, and set the relevant columns of the current topology characterization matrix, the current node type matrix, the current cable unit length impedance matrix, and the current cable length matrix related to the current distribution network terminal node to 0;

[0075] Step c: Repeat steps a - c until the current topology characterization matrix reaches the simplest form.

[0076] In one embodiment, the calculation of the equivalent impedance between the terminal node P and the adjacent cable line can adopt a theoretical formula or a simulation method. The theoretical formula ignores the change of cable distribution parameters with frequency and only considers the reflection and refraction process of signals in the cable and the terminal load. For the simulation, a simulation model can be established using PSCAD software, a single - frequency sine signal can be input, and the equivalent impedance can be obtained by measuring the current signal.

[0077] In a specific embodiment, the equivalent impedance matrix is assumed to be a frequency - linearly - related matrix, and the expression form of its element Z′ is:

[0078] Z′ = A + jB·f

[0079] For the case where Z′ is non - linear with frequency, the equivalent impedance is represented by the coefficients A and B obtained by least - squares fitting.

[0080] In one embodiment, when the node types of the columns with a sum of 1 in the topology characterization matrix are only frequency - response curve test nodes, the topology characterization matrix reaches the simplest form. At this time, there is only one main cable connecting the test nodes on the topology map.

[0081] Based on the above embodiments, this embodiment details step S103:

[0082] In some embodiments, the repeated above steps in step S103 refer to:

[0083] Obtain the eigenvalue matrix of the defective distribution network cable topology map, including the topology characterization matrix, the node load impedance matrix, the node type matrix, the cable unit length impedance matrix, and the cable length matrix;

[0084] Traverse and delete the cable branches where the terminal nodes are located in the defective distribution network cable topology diagram, and update the eigenvalue matrix until the topological characterization matrix reaches the simplest form, obtaining the corresponding simplest eigenvalue matrix;

[0085] The specific steps refer to the above embodiments and will not be elaborated in this embodiment;

[0086] In some embodiments, based on the simplest distribution network cable topology diagram, the cable defects are set as follows:

[0087] Based on the simplest distribution network cable topology diagram, the characteristics of the cable defect segment including the starting position of the cable defect, the ending position of the cable defect, and the characteristic impedance of the cable defect segment are set;

[0088] In one embodiment, the starting position and ending position of the cable defect are represented by the distances from the starting test point in the simplest distribution network cable topology diagram, the length of the defect segment is the ending position distance minus the starting position distance, and the characteristic impedance of the defect segment is at least 10% different from the characteristic impedance of the normal segment.

[0089] In one embodiment, if the cable defect segment spans an existing main cable node, a virtual node is introduced into the main cable, and a new defective distribution network cable topology diagram is regenerated;

[0090] In one embodiment, the cable frequency response curve F(ω) is the ratio of the amplitude of the received signal at the test node to the amplitude of the transmitted signal;

[0091] In a specific embodiment, the frequency range is at least 50 kHz - 10 MHz, and the frequency resolution is at least 10 kHz.

[0092] As Figure 3 , Figure 3 is the frequency response curve of a defective distribution network cable in an embodiment of the present invention.

[0093] Based on the above embodiments, this embodiment elaborates on step S104 in detail:

[0094] In some embodiments, using multiple groups of original eigenvalue matrices and the frequency response curve F(ω) corresponding to the defective distribution network cable topology diagram, that is, multiple groups of T0, Z0, K0, ZL0, L0, F(ω) to train the defect monitoring model by neural network;

[0095] In a specific embodiment, 10,000 groups of frequency response curves of defective distribution network cables are generated for each of the 3 topologies for training.

[0096] Based on the above embodiments, this embodiment elaborates on step S105 in detail:

[0097] In some embodiments, the frequency response curve of the actual medium-voltage distribution network cable is collected, and the curve and the T0, Z0, K0, ZL0, and L0 matrices corresponding to the actual medium-voltage distribution network are input into the trained defect monitoring model to obtain the judgment results of the defect location and severity.

[0098] In a specific embodiment, the trained defect monitoring model is used to predict that the starting position of the cable defect is 468 m and the ending position is 472 m. The actual starting position of the defect is 463 m and the ending position is 473 m, with an error within 1%; the defect severity is that the distributed capacitance increases to 1.1843 times the original, and the actual defect is that the distributed capacitance increases to 1.2 times the original, with an error of 1.3%.

[0099] According to the actual distribution network cable topology, an original topology characterization matrix is generated, the eigenvalue information of the distribution network cable network nodes is collected to generate an original node eigenvalue matrix; the eigenvalue information of the distribution network cable lines is collected to generate an original cable line eigenvalue matrix; the terminal nodes of the distribution network cable network are found according to the original node eigenvalue matrix. Starting from the load terminal nodes of the distribution network, the terminal nodes are merged with the adjacent cable lines to calculate the equivalent eigenvalues; the merged terminal nodes are deleted to simplify the topology matrix and eigenvalue matrix to obtain a new topology and eigenvalue matrix; the matrix simplification is repeated to obtain the simplest eigenvalue matrix; then, based on the simplest topology graph, cable defects are set to generate multiple defective distribution network cable topology graphs, and the topology graphs are simplified again. The frequency response function curve is calculated according to the simplest characteristic matrix of the defective distribution network cable topology graph; finally, the neural network is trained using the frequency response curves corresponding to multiple groups of defective distribution network cable topology graphs and the original eigenvalue matrix to obtain a defect monitoring model; the frequency response curve and the original eigenvalue matrix of the actual medium-voltage distribution network are collected and input into the defect monitoring model to obtain the judgment results of the defect location and severity. The present invention can realize the online monitoring of the insulation defects of medium-voltage cables under the complex and time-varying conditions of the distribution network topology, has strong adaptability to the changes in the distribution network topology, and only requires a small amount of actual distribution network online monitoring data.

[0100] An embodiment of the present invention also provides a medium-voltage distribution network cable insulation defect monitoring device; the specific device may include:

[0101] An eigenvalue matrix acquisition module, configured to acquire the original eigenvalue matrix of the original distribution network cable topology graph, including an original topology characterization matrix, an original node load impedance matrix, an original node type matrix, an original cable unit length impedance matrix, and an original cable length matrix;

[0102] A topology simplification module, which is used to traverse and delete the cable branches where the terminal nodes are located in the original cable topology diagram of the distribution network, and update the eigenvalue matrix until the topology representation matrix reaches the simplest form, so as to obtain the simplest cable topology diagram of the distribution network and the corresponding simplest eigenvalue matrix;

[0103] A training set generation module, which is used to set cable defects based on the simplest cable topology diagram of the distribution network, generate multiple cable topology diagrams of the distribution network with defects, repeat the above steps, obtain the simplest eigenvalue matrices corresponding to multiple cable topology diagrams of the distribution network with defects, and calculate the frequency response curves;

[0104] A model training module, which is used to train the defect monitoring model according to multiple groups of frequency response curves and the original eigenvalue matrix;

[0105] A defect monitoring module, which is used to input the frequency response curve and the original eigenvalue matrix of the actual medium-voltage distribution network cable into the trained defect monitoring model to obtain the monitoring result.

[0106] The medium-voltage distribution network cable insulation defect monitoring device of this embodiment is used to implement the foregoing medium-voltage distribution network cable insulation defect monitoring method. Therefore, the specific implementation manners in the medium-voltage distribution network cable insulation defect monitoring device can be seen in the embodiment part of the foregoing medium-voltage distribution network cable insulation defect monitoring method. For example, the eigenvalue matrix acquisition module, the topology simplification module, the training set generation module, the model training module, and the defect monitoring module are respectively used to implement steps S101, S102, S103, S104, and S105 in the foregoing medium-voltage distribution network cable insulation defect monitoring method. Therefore, the specific implementation manners can refer to the descriptions of the corresponding various part embodiments and will not be elaborated here.

[0107] A specific embodiment of the present invention also provides a medium-voltage distribution network cable insulation defect monitoring device, including: a memory, which is used to store a computer program; a processor, which is used to implement the steps of the foregoing medium-voltage distribution network cable insulation defect monitoring method when executing the computer program.

[0108] A specific embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the foregoing medium-voltage distribution network cable insulation defect monitoring method are implemented.

[0109] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0110] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0111] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0113] Obviously, the above embodiments are merely examples for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or variations can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. And the obvious changes or variations derived therefrom are still within the protection scope of the present invention.

Claims

1. A method for monitoring insulation defects of cables in a medium voltage distribution network, characterized in that: include: Obtaining the original eigenvalue matrix of the original distribution network cable topology diagram, including the original topology characterization matrix, the original node load impedance matrix, the original node type matrix, the original cable unit length impedance matrix and the original cable length matrix; The cable branches where the terminal nodes are located in the original distribution network cable topology are traversed and deleted in a loop, and the eigenvalue matrix is ​​updated until the topology representation matrix is ​​simplified, and the simplified distribution network cable topology and the corresponding simplified eigenvalue matrix are obtained; Based on the simplest distribution network cable topology diagram, cable defects are set, multiple distribution network cable topology diagrams containing defects are generated, the above steps are repeated to obtain the simplest eigenvalue matrix corresponding to the multiple distribution network cable topology diagrams containing defects, and a frequency response curve is calculated; The defect monitoring model is trained according to multiple sets of frequency response curves and original eigenvalue matrices; The frequency response curve and original eigenvalue matrix of the actual medium-voltage distribution network cable are input into the trained defect monitoring model to obtain the monitoring results.

2. The method for monitoring insulation defects of cables in a medium voltage distribution network according to claim 1, characterized in that: The original eigenvalue matrix of the original distribution network cable topology diagram is obtained, including the original topology characterization matrix, the original node load impedance matrix, the original node type matrix, the original cable unit length impedance matrix and the original cable length matrix, including: Number each node in the original distribution network cable topology diagram, and generate an original topology representation matrix based on the node connection relationship; Obtain the time-varying curve of the power supply load at the end of the cable corresponding to the original distribution network cable topology diagram, calculate the average equivalent impedance, and generate the original node load impedance matrix; Obtain the type of each node in the original distribution network cable topology diagram and generate a node type matrix; The resistance per unit length, inductance per unit length, conductance per unit length and capacitance per unit length of each cable in the distribution network corresponding to the original distribution network cable topology diagram are obtained to generate the original cable unit length impedance matrix, and the cable length matrix is ​​generated according to the length of each cable.

3. The method for monitoring insulation defects of cables in a medium voltage distribution network according to claim 2, characterized in that: The step of obtaining the resistance per unit length, the inductance per unit length, the conductance per unit length, and the capacitance per unit length of each cable in the distribution network corresponding to the original distribution network cable topology diagram, and generating the original cable unit length impedance matrix comprises: Construct a two-dimensional matrix, in which the element in the mth row and the nth column represents the characteristic impedance per unit length of the cable connecting the node m and the node n; The unit length impedance Z of the cable connecting node m and node n is calculated based on the unit length resistance, unit length inductance, unit length conductance and unit length capacitance of the cable connecting node m and node n. mn : Among them, R mn , G mn , L mn , C mn are the resistance per unit length, conductance per unit length, inductance per unit length, and capacitance per unit length of the cable connecting node m and node n, j is an imaginary unit, and ω is the angular frequency.

4. The method for monitoring insulation defects of cables in a medium voltage distribution network according to claim 2, characterized in that: The original topology characterization matrix is ​​an adjacency matrix of the cable topology.

5. The method for monitoring insulation defects of cables in a medium voltage distribution network according to claim 4, characterized in that: The topological characterization matrix reaches the simplest judgment basis as follows: When the node types of the columns whose sum is 1 in the topology characterization matrix are only the frequency response curve test nodes, the topology characterization matrix reaches the simplest.

6. The method for monitoring insulation defects of cables in a medium voltage distribution network according to claim 1, characterized in that: The loop traverses and deletes the cable branches where the terminal nodes are located in each original distribution network cable topology diagram, and updates the eigenvalue matrix until the topology representation matrix is ​​simplified, and obtains multiple simplified distribution network cable topology diagrams and corresponding simplified eigenvalue matrices including: Step a: Obtain the equivalent load impedance of the current distribution network terminal node and the adjacent cable line, and delete the cable branch where the current distribution network terminal node is located on the current distribution network cable topology diagram; Step b: Set the impedance value related to the current distribution network terminal node in the current node load impedance matrix to 0, update the impedance value of the node connected to the current distribution network terminal node in the current node load impedance matrix to the equivalent load impedance of the current distribution network terminal node and the adjacent cable line, and set the relevant columns of the current topology characterization matrix, the current node type matrix, the current cable unit length impedance matrix and the current cable length matrix related to the current distribution network terminal node to 0; Step c: Repeat steps ac until the current topological representation matrix reaches the minimum.

7. The method for monitoring insulation defects of cables in a medium voltage distribution network according to claim 1, characterized in that: The setting of cable defects based on the simplest distribution network cable topology diagram includes: Setting the cable defect segment characteristics including the cable defect start position, the cable defect end position and the cable defect segment characteristic impedance based on the simplest distribution network cable topology diagram; If the defective cable section crosses an existing trunk cable node, a virtual node is introduced into the trunk cable.

8. A medium voltage distribution network cable insulation defect monitoring device, characterized in that: include: An eigenvalue matrix acquisition module is used to obtain the original eigenvalue matrix of the original distribution network cable topology diagram, including the original topology characterization matrix, the original node load impedance matrix, the original node type matrix, the original cable unit length impedance matrix and the original cable length matrix; A topology simplification module is used to loop through and delete the cable branches where the terminal nodes are located in the original distribution network cable topology diagram, and update the eigenvalue matrix until the topology representation matrix is ​​the simplest, thereby obtaining the simplest distribution network cable topology diagram and the corresponding simplest eigenvalue matrix; A training set generation module is used to set cable defects based on the simplest distribution network cable topology diagram, generate multiple distribution network cable topology diagrams containing defects, repeat the above steps, obtain the simplest eigenvalue matrix corresponding to the multiple distribution network cable topology diagrams containing defects, and calculate the frequency response curve; A model training module is used to train a defect monitoring model based on multiple sets of frequency response curves and original eigenvalue matrices; The defect monitoring module is used to input the frequency response curve and original eigenvalue matrix of the actual medium-voltage distribution network cable into the trained defect monitoring model to obtain the monitoring results.

9. A medium voltage distribution network cable insulation defect monitoring device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of a method for monitoring insulation defects of cables in a medium-voltage distribution network as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of a method for monitoring insulation defects of cables in a medium-voltage distribution network as claimed in any one of claims 1 to 7 are implemented.

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