Method and device for locating power quality abnormal path and related product

Abstract

The application discloses a power quality abnormal path positioning method and device and related products, and is applied to a server. The method comprises the following steps: acquiring target power quality data of a target power distribution network; determining target power quality abnormal data in the target power quality data; determining a target abnormal area corresponding to the target power quality abnormal data and a target cable corresponding to the target abnormal area; acquiring theoretical magnetic field distribution data corresponding to the target cable; when the target abnormal area is located underground or in a cable tunnel, determining a target laying path of the target cable based on the theoretical magnetic field distribution data; and detecting and maintaining the target cable according to the target laying path and the target power quality abnormal data. By adopting the embodiment of the application, the function of determining the cable abnormal path at low cost is realized.

Description

Technical Field

[0001] This invention relates to the field of power equipment technology, and in particular to a method, device, and related products for locating abnormal power quality paths. Background Technology

[0002] Electricity, as an economical, practical, clean, convenient, and easily controlled and converted secondary energy source, has become a basic resource for people's lives. However, with the rapid development and widespread application of power electronics technology, power quality problems are becoming increasingly prominent, bringing increasingly serious impacts to the power grid, power users, and society.

[0003] To solve power quality problems, it is first necessary to identify abnormal power paths where power quality issues exist. Currently, this is generally done using radio frequency identification (RFID) technology. For example, an electronic tag is placed at regular intervals along the power cable. Workers use handheld readers to read the relevant information about the power cable from the electronic tags. Based on the information read, the path of the power cable with power quality problems, i.e., the abnormal path, is determined. However, this method requires multiple electronic tags and manual maintenance, which is costly. Therefore, it is urgent to solve the problem of how to determine abnormal cable paths at a low cost. Summary of the Invention

[0004] This invention provides a method, apparatus, and related products for locating abnormal power quality paths. By acquiring abnormal power quality data of the distribution network, the abnormal area where the abnormality occurs is determined. Then, based on theoretical magnetic field distribution data, the laying path of the cable that is abnormal in the abnormal area is found, i.e., the abnormal cable path. Since the theoretical magnetic field distribution data can be obtained through computer simulation and calculation without the need for physical equipment, this invention achieves the function of determining abnormal cable paths at a low cost compared to traditional on-site survey and testing methods.

[0005] In a first aspect, embodiments of the present invention provide a method for locating power quality anomaly paths, applied to a server, the method comprising:

[0006] Obtain target power quality data for the target distribution network;

[0007] Identify the target power quality anomaly data in the target power quality data;

[0008] Determine the target abnormal region corresponding to the target power quality abnormal data and the target cable corresponding to the target abnormal region;

[0009] Obtain the theoretical magnetic field distribution data corresponding to the target cable;

[0010] When the target anomalous area is located underground or in a cable tunnel, the target laying path of the target cable is determined based on the theoretical magnetic field distribution data.

[0011] The target cable is inspected and maintained based on the target laying path and the target power quality anomaly data.

[0012] Secondly, embodiments of the present invention provide a device for locating abnormal power quality paths, the device comprising: an acquisition unit, a determination unit, and a maintenance unit, wherein...

[0013] The acquisition unit is used to acquire target power quality data of the target distribution network;

[0014] The determining unit is used to determine target power quality anomaly data in the target power quality data; and to determine the target anomaly region corresponding to the target power quality anomaly data and the target cable corresponding to the target anomaly region.

[0015] The acquisition unit is also used to acquire theoretical magnetic field distribution data corresponding to the target cable;

[0016] The determining unit is also used to determine the target laying path of the target cable based on the theoretical magnetic field distribution data when the target abnormal area is located underground or in a cable tunnel;

[0017] The maintenance unit is used to inspect and maintain the target cable based on the target laying path and the target power quality anomaly data.

[0018] Thirdly, embodiments of this application provide a server, including: a processor and a memory, the memory being used to store one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps in the first aspect of embodiments of this application.

[0019] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the first aspect of embodiments of this application.

[0020] Fifthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the first aspect of embodiments of this application. The computer program product may be a software installation package.

[0021] As can be seen, by implementing the embodiments of the present invention, target power quality data of the target power distribution network is obtained; target power quality anomaly data in the target power quality data is determined; target anomaly areas corresponding to the target power quality anomaly data and target cables corresponding to the target anomaly areas are determined; theoretical magnetic field distribution data corresponding to the target cables is obtained; when the target anomaly area is located underground or in a cable tunnel, the target laying path of the target cable is determined based on the theoretical magnetic field distribution data; the target cable is inspected and maintained according to the target laying path and the target power quality anomaly data. Thus, by obtaining the power quality anomaly data of the power distribution network, the anomaly area where the anomaly occurs is determined. Then, the laying path of the cable in the anomaly area, i.e., the cable anomaly path, is found according to the theoretical magnetic field distribution data. Since the theoretical magnetic field distribution data can be obtained through computer simulation and calculation without the need for physical equipment, compared with the traditional on-site survey and testing methods, the function of determining the cable anomaly path at a low cost is achieved. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the background art, the accompanying drawings used in the embodiments of the present invention or the background art will be described below.

[0023] Figure 1 This is a flowchart of a method for locating an abnormal power quality path provided in an embodiment of this application;

[0024] Figure 2 This is a schematic diagram of the structure of a cable provided in an embodiment of this application;

[0025] Figure 3 This is a schematic diagram of a cable installation method provided in an embodiment of this application;

[0026] Figure 4 This is a schematic diagram of another cable installation method provided in an embodiment of this application;

[0027] Figure 5 This is a diagram illustrating the positional relationship between point P and the cable, provided in an embodiment of this application.

[0028] Figure 6 This is a functional unit block diagram of a power quality anomaly path locating device provided in an embodiment of this application;

[0029] Figure 7 This is a schematic diagram of the structure of a server provided in an embodiment of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0031] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0032] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0033] The server described in this application embodiment can be a cloud server.

[0034] First, let me explain some of the terms used in this application:

[0035] Power quality data refers to various parameters and indicators that describe the power quality of a power system. These data may include parameters such as voltage, current, frequency, power factor, harmonic content, voltage fluctuation, flicker, and three-phase imbalance.

[0036] Power quality anomalies refer to power quality parameter values ​​that exceed the normal range or do not meet expectations during power quality monitoring. These anomalies may be caused by faults, interference, load changes, or other factors in the power system. Common power quality anomalies include voltage sags, voltage swells, voltage interruptions, frequency deviations, and excessive harmonic content. These anomalies may affect the normal operation of the power system and the safe operation of power equipment; therefore, timely monitoring and analysis are necessary to identify the causes of the anomalies and take appropriate measures to resolve them.

[0037] Theoretical magnetic field distribution data: In this application, theoretical magnetic field distribution data refers to the distribution of the magnetic field around the cable calculated based on electromagnetic field theory and mathematical models. It includes information such as the magnitude, direction, and distribution shape of the magnetic field, and can be expressed in mathematical expressions or graphs. Theoretical magnetic field distribution data can provide a reference for the design, installation, and operation of cables, helping engineers assess the impact of the electromagnetic field environment around the cable on surrounding equipment and personnel, and take appropriate protective measures.

[0038] Laying environment: This refers to the environmental conditions in which the cable is installed and used. These environmental conditions may affect the cable's performance, lifespan, and magnetic field, so these factors need to be considered when selecting cables and laying them.

[0039] Finite element analysis (FEM) is a numerical analysis method used to solve mechanical, electromagnetic, and thermodynamic problems involving complex structures. It divides a complex structure into many small elements and analyzes and calculates these elements to obtain the characteristics and response of the entire structure. In FEM, the structure is first divided into a finite number of elements, each with a specific shape and properties. These elements are then connected by nodes to form a finite element model. Next, each element is analyzed mechanically, electromagnetically, or thermodynamically to obtain parameters such as internal forces, strain, and magnetic field strength. Finally, by combining the parameters of all elements, the characteristics and response of the entire structure are obtained. FEM can be used to analyze various types of structures, such as cables and buildings.

[0040] Please see Figure 1 , Figure 1 This is a flowchart of a method for locating abnormal power quality paths provided in an embodiment of this application, as shown below. Figure 1 The method for locating power quality anomaly paths shown can be applied to servers, and the method includes, but is not limited to, the following steps:

[0041] S101. Obtain the target power quality data of the target distribution network.

[0042] In this embodiment of the application, the power quality data may include at least one of the following: voltage data, current data, grid voltage qualification rate, grid frequency qualification rate, grid three-phase imbalance qualification rate, grid flicker qualification rate, grid harmonic qualification rate, inter-grid harmonic qualification rate, etc., which are not limited here.

[0043] In a specific embodiment, multiple power quality monitoring devices can be installed at key points in the target distribution network. These devices monitor the power quality data of the target distribution network to obtain target power quality data. Specifically, the key points in the target distribution network that need to be monitored can be determined first, such as the locations of transformers, buses, and important loads in the distribution network. Then, power quality monitoring devices are installed at the monitoring points. These devices can measure power quality parameters in real time, such as voltage, current, frequency, power factor, and harmonic content. Specifically, the power quality monitoring devices can include at least one of the following: power quality analyzer, power quality monitor, power quality data acquisition device, etc., without limitation. The power quality data of the target distribution network is collected by the power quality monitoring devices, and the collected data is transmitted to a data center or cloud for storage and analysis via a server.

[0044] Some of the power quality data can be calculated using the following formula:

[0045] Voltage pass rate = (1 - voltage over-limit time / total operating time) * 100%;

[0046] Frequency pass rate = (1 - frequency over-limit time / total operating statistical time) * 100%;

[0047] Three-phase voltage imbalance pass rate = (1 - three-phase voltage imbalance over-limit time / total operating statistical time) * 100%;

[0048] Flicker pass rate = (1 - flicker over-limit time / total operating statistical time) * 100%;

[0049] Harmonic compliance rate = (1 - harmonic over-limit time / total operating statistical time) * 100%;

[0050] Interharmonic compliance rate = (1 - Interharmonic over-limit time / Total operating statistical time) * 100%;

[0051] In this way, target power quality data in the target distribution network can be obtained.

[0052] S102. Determine the target power quality anomaly data in the target power quality data.

[0053] In this embodiment of the application, abnormal power quality data can refer to power quality parameter values ​​that exceed the normal range or do not meet expectations during the power quality monitoring process.

[0054] In a specific embodiment, the target power quality data can be filtered by the server, and data whose power quality values ​​exceed the normal range or do not meet expectations can be selected, i.e., target power quality abnormal data.

[0055] Optionally, step S102, determining the target power quality anomaly data in the target power quality data, may include the following steps:

[0056] 21. Perform data cleaning on the target power quality data to remove useless data from the target power quality data and obtain reference power quality data. The useless data includes at least one of the following: erroneous data, expired data, and duplicate data.

[0057] 22. Select all non-compliant data from the reference power quality data to obtain the target power quality anomaly data.

[0058] In this embodiment, the target power quality data can be cleaned by a server to remove useless data. Specifically, the useless data can be expired data. Statistical analysis can be used to identify and process the useless data in the target power quality data. The processing method can be to directly delete the detected expired data to finally obtain reference power quality data.

[0059] Furthermore, all non-compliant data in the reference power quality data can be selected. Specifically, the compliance can be determined by various power quality indicators in the reference power quality data. For example, the power quality indicator can be the voltage compliance rate. Alternatively, all power quality data in the reference power quality data whose power quality indicators are lower than the preset indicator values ​​can be extracted to obtain all non-compliant data, which are the target power quality abnormal data.

[0060] S103. Determine the target abnormal region corresponding to the target power quality abnormal data and the target cable corresponding to the target abnormal region.

[0061] In this embodiment of the application, the target power quality anomaly data may include: power consumption data and the location information corresponding to the power consumption data; the anomaly area indicates that the cable in the area may have a power quality anomaly problem, or that a power quality anomaly problem already exists.

[0062] In a specific embodiment, the location information contained in the target power quality anomaly data can be obtained first, and the target anomaly area can be determined based on the location information. In addition, the target cable corresponding to the target anomaly area can also be determined.

[0063] Optionally, step S103, determining the target abnormal region corresponding to the target power quality abnormal data and the target cable corresponding to the target abnormal region, may include the following steps:

[0064] 31. Obtain multiple power quality anomaly location data from the target power quality anomaly data;

[0065] 32. Draw a reference cable distribution map based on the multiple power quality anomaly location data;

[0066] 33. Compare the reference cable distribution map with the preset cable distribution map to determine the target abnormal area;

[0067] 34. Obtain the cable data corresponding to the target abnormal area;

[0068] 35. Determine the target cable based on the cable data.

[0069] In this embodiment of the application, the preset cable distribution map can be a pre-prepared distribution map. The preset cable distribution map represents the arrangement of preset cables in a certain area. Pre-prepared cables refer to cables that are laid in advance according to planning and design requirements before the construction of buildings or other facilities.

[0070] In a specific embodiment, the location data corresponding to each power quality anomaly data can be obtained from the target power quality anomaly data to obtain multiple power quality anomaly location data. Then, a professional drawing tool (e.g., Matlab) can be used to draw a reference cable distribution map based on the multiple power quality anomaly location data. Next, the reference cable distribution map can be compared with a preset cable distribution map, comparing the two cable distribution maps row by row or column by column to find the same and different areas. Since the reference cable distribution map is drawn based on the power quality anomaly location data, the same areas of the two can be identified as the target anomaly areas.

[0071] Furthermore, cable data corresponding to the target anomaly area can be obtained through a server. Specifically, this can be done by retrieving cable data corresponding to the target anomaly area from the data center or database of the target power distribution network. Then, the target cable can be identified based on the cable data. Specifically, the number of cables in the target anomaly area can be determined based on the cable data, and then these cables can be compared sequentially according to the aforementioned power quality anomaly location data to finally determine the target cable and its location. For the identified target cable, further investigation and analysis can be conducted, such as reviewing the target cable's maintenance records, fault history, load conditions, etc., to understand the target cable's operating status and potential problems.

[0072] S104. Obtain the theoretical magnetic field distribution data.

[0073] In this embodiment of the application, the theoretical magnetic field distribution data refers to the distribution of the magnetic field around the cable calculated based on electromagnetic field theory and mathematical models.

[0074] In a specific embodiment, various information about the target cable can be obtained first, and the target cable can be analyzed and processed based on the above information to obtain the theoretical magnetic field distribution data of the target cable.

[0075] Optionally, step S104, obtaining the theoretical magnetic field distribution data corresponding to the target cable, may include the following steps:

[0076] A1. Obtain the target cable attribute data of the target cable;

[0077] A2. Establish a target cable model based on the target cable attribute data;

[0078] A3. Obtain the target laying environment data of the target cable;

[0079] A4. Establish a laying environment model based on the target laying environment data;

[0080] A5. Determine the target positional relationship between the target cable model and the laying environment model;

[0081] A6. Based on the target location relationship, combine the target cable model and the laying environment model to form a target simulation model;

[0082] A7. Determine the theoretical magnetic field distribution data of the target cable based on the target simulation model.

[0083] In this embodiment of the application, the cable attribute data may include at least one of the following: cable structural data and cable material data; the laying environment data may include at least one of the following: environmental structural parameters and environmental composition material data.

[0084] Please see Figure 2 , Figure 2 This is a structural schematic diagram of a cable 200 provided in an embodiment of this application, as shown below. Figure 2 As shown, the structural data of cable 200 may include: the thickness of outer sheath 21, the thickness of copper tape armor 22, the thickness of inner sheath 23, the diameter of conductor 24, the thickness of insulation layer 26, etc., which are not limited here; the material data of cable 200 may include: the material of outer sheath 21, the material of copper tape armor 22, the material of inner sheath 23, the material of conductor 24, the filling material of filling content 25, the material of insulation layer 26, etc., which are not limited here.

[0085] Among them, Figure 2 As can be seen from the diagram, conductor 24 contains a total of four circular structures: A, B, C, and N. The circular structures A, B, C, and N correspond to phase A conductor, phase B conductor, phase C conductor, and phase N conductor in cable 200, respectively.

[0086] The installation of the target cable may include at least one of the following: installed on the ground, installed underground, or installed in a cable tunnel, without any limitation.

[0087] Please see Figure 3 , Figure 3 This is a schematic diagram of a cable installation method provided in an embodiment of this application, as shown below. Figure 3 The cable tunnel 300 shown includes: an upper support 31, a middle support 32, and a lower support 34.

[0088] Among them, such as Figure 3 The cable 33 shown is installed on the middle support 32 and the lower support 34 of the cable tunnel 300. Of course, the cable 33 can also be installed on the upper support 31. Figure 3 This is just one possible scenario. Therefore, the structural parameters of the environment may include at least one of the following: tunnel width, tunnel height, number of cable support layers, support spacing, support width, and cable placement method, etc., which are not limited here. The cable placement method may include: suspended placement, cable tray placement, conduit placement, etc., which are not limited here.

[0089] Please see Figure 4 , Figure 4 This is a schematic diagram of another cable installation method provided in an embodiment of this application, as shown below. Figure 4 The cable 41 shown is installed in the soil 400 underground. Therefore, the environmental structural parameters can include: the composition of the soil 400, the burial depth, the cable placement method, etc., which are not limited here. It can be seen that... Figure 4 The burial depth of cable 41 is 0.7m. It should be noted that... Figure 4 This is just one possibility. To determine the actual cable installation situation, on-site testing may be necessary to obtain accurate data.

[0090] In a specific embodiment, target cable attribute data can be obtained first. Specifically, this data can be obtained from the data center or database of the target power distribution network. Alternatively, data not recorded in the data center or database can be obtained through on-site testing. Next, a target cable model is established based on the target cable attribute data. Specifically, this model can be established using simulation software (e.g., Maxwell software). The collected target cable attribute data is first analyzed to obtain information such as the cable's structural data, materials, dimensions, and electrical characteristics. This information can then be input into Maxwell software, and the modeling tools of Maxwell software are used to create a geometric model of the cable. Furthermore, based on the material characteristics of the target cable, corresponding material properties, such as conductivity, permeability, and dielectric constant, can be set in Maxwell software to finally obtain the target cable model.

[0091] Next, the target cable's target laying environment data can be obtained from the target distribution network's data center or database. Alternatively, for data not recorded in the data center or database, on-site inspections can be conducted by personnel from the target distribution network to obtain the target laying environment data. Then, a laying environment model is established based on the target laying environment data. Specifically, the laying environment model can be established using Maxwell software. It should be noted that the method for establishing the laying environment model is the same as that for establishing the target cable model, and will not be repeated here.

[0092] Furthermore, the target positional relationship between the target cable model and the laying environment model is determined. Based on this relationship, the target cable model and the laying environment model are combined to form a target simulation model. Specifically, the coordinate systems of the two models can be unified into a single coordinate system. Then, the actual positional relationship between the target cable and the laying environment in reality can be obtained. Based on this actual positional relationship, the target positional relationship between the two models in the coordinate system is determined. Further, the target cable model can be imported into the laying environment model, and they can be combined according to the target positional relationship to obtain the target simulation model. This can be achieved through model merging, Boolean operations, or other appropriate methods. Finally, simulation can be performed based on the target simulation model, and the theoretical magnetic field distribution data of the target cable can be obtained from the simulation results.

[0093] Optionally, determining the theoretical magnetic field distribution data of the target cable based on the target simulation model may include the following steps:

[0094] B1. The target cable model in the target simulation model is meshed to obtain a meshed cable model; the mesh shape includes one of the following: triangle, quadrilateral, or hexagon;

[0095] B2. Inject a first preset current signal into the mesh cable model to generate a magnetic field in the mesh cable model;

[0096] B3. Perform finite element analysis on the mesh cable model to obtain the theoretical magnetic field distribution data of the mesh cable model under the laying environment model.

[0097] In this embodiment of the application, the first preset current signal can be either default or preset in advance. The first preset current signal is a virtual signal, and its function is to generate a magnetic field in the target cable model.

[0098] In a specific embodiment, after constructing the target cable model, it is necessary to mesh the target cable model. Mesh generation is closely related to simulation accuracy and computational efficiency. If the mesh is coarse, the simulation accuracy is low, but the computation time is short; if the mesh is fine, the simulation accuracy is high, but the computation time is long. To achieve a match between simulation accuracy and computational speed, the mesh can be any pattern such as triangle, quadrilateral, or hexagon, or other mesh shapes.

[0099] Specifically, the target cable model can be meshed using Maxwell software. The meshing tool can be found in the function menu of Maxwell software. In the meshing tool, you can set the relevant parameters of the mesh, such as mesh size, mesh type, mesh density, etc. You can select appropriate mesh parameters according to the required simulation accuracy and computational efficiency. After setting, click the Apply button in Maxwell software to apply the set mesh to the target cable model and obtain a meshed cable model.

[0100] Next, a first preset current signal can be injected into the mesh cable model to generate a magnetic field. Further, finite element analysis can be performed on the mesh cable model to obtain the theoretical magnetic field distribution data under the laying environment model. Specifically, the first preset current signal can be a 1A three-phase power frequency AC current. The mesh cable model can be installed in two ways: individually or in combination with other cables. These two situations need to be discussed separately, as follows:

[0101] In the case of a standalone installation, i.e., the mesh cable model is a single cable, a first preset current signal is injected into the single cable, and finite element analysis is performed on the mesh cable model. Specifically, the electromagnetic field distribution results of the cable, i.e., the theoretical magnetic field distribution data, can be obtained through the solver of Maxwell software. Among them, the magnetic field on the surface of the A phase core is the largest, and the magnetic field extrema of the B phase core and the C phase core are located on the surface of the B phase core, the C phase core and the A phase core.

[0102] In the case of mixed installation, that is, the mesh cable model consists of multiple cables, a first preset current signal is injected into each of the multiple cables. Specifically, the electromagnetic field distribution results of the multiple cables can be obtained through the solver of Maxwell software, that is, the theoretical magnetic field distribution data. Among them, the magnetic induction intensity is mainly distributed inside the multiple cables, and the magnetic induction intensity outside the multiple cables is relatively small; the magnetic induction extremum is located at a certain position directly above the multiple cables.

[0103] The formula for calculating the magnetic induction intensity generated by the three-phase cores of the grid cable model at point P, a predetermined distance above the axis of the grid cable model, is as follows:

[0104]

[0105] Please refer to Figure 5 , Figure 5 This is a diagram illustrating the positional relationship between point P and the cable, as provided in an embodiment of this application. Figure 5 As shown, point P is located on the line connecting phase A conductor and neutral conductor (phase N), and is d away from the axis O of the mesh cable model; B a Let B be the magnetic flux density of phase A conductor at point P. b Let B be the magnetic flux density of phase B at point P. c Let μ0 be the magnetic flux density of the C-phase core at point P, μ0 be the free permeability, and R0 be the magnetic flux density. a R is the distance from point P to the conductor of phase A. b R is the distance from point P to the conductor of phase B. c Let I be the distance from point P to the C phase conductor. m Let θ represent the current corresponding to the m-th phase conductor. In the above formula, all three n's can be equal to 3. Phase 1 can correspond to phase A, phase 2 to phase B, and phase 3 to phase C. θ is the angle between the line connecting point P to the axis of the mesh cable model and the line connecting phase B conductor or phase C conductor to point P. The preset distance can be a default distance or a manually set distance.

[0106] When performing magnetic field analysis on a grid cable model, since the diameter of the grid cable model is much smaller than its length, the grid cable model can be considered equivalent to an infinitely long current-carrying straight conductor when analyzing its magnetic field distribution characteristics. According to the Biot-Sarvassi-Biscuit law, we know that:

[0107]

[0108] Integrating over point P, we can derive the formula for calculating the magnetic flux density B:

[0109]

[0110] Simplifying the above equation using trigonometric functions, and assuming the current-carrying straight conductor is infinitely long, we get:

[0111]

[0112] Therefore, we can obtain the above formula for calculating magnetic flux density, and we can also derive the formula for calculating the total magnetic flux density at point P (i.e., the theoretical magnetic field distribution):

[0113] B = B a -B b cosθ-B c cosθ

[0114] in, l b Let d be the distance from the B-phase conductor to the origin O, and d be the distance from point P to point O. The value of μ0 can be 4π × 10⁻⁶. -7 H / m. Thus, the magnetic field strength at point P can be obtained by calculating using the above formulas. Point P can be any point around the grid cable model. In other words, the magnetic field strength at all points around the grid cable model can be determined using the above formulas. The sum of the magnetic field strength data at all points is the theoretical magnetic field distribution data.

[0115] It's important to explain that during normal operation, the cable is subjected to a power frequency AC voltage. This AC current creates a skin effect within the cable core, causing the magnetic field to concentrate on the surface layer. Therefore, when meshing, a finer mesh needs to be created on the surface layer of the cable core, while the meshing inside the core can be relatively less dense. This results in a mesh with a dense surface and sparse interior, achieving a balance between simulation accuracy and computational efficiency.

[0116] S105. When the target abnormal area is located underground or in a cable tunnel, the target laying path of the target cable is determined based on the theoretical magnetic field distribution data.

[0117] In this embodiment of the application, the location of the target abnormal area can include three situations: located above ground, located underground, or located in a cable tunnel;

[0118] In a specific embodiment, if the target abnormal area is located on the ground, the cable laying path can be directly observed by the human eye, without the need to use the method in this application;

[0119] When the target anomalous area is located underground or in a cable tunnel, the cable cannot be observed by the human eye. In this case, the target laying path of the target cable can be determined based on theoretical magnetic field distribution data.

[0120] Optionally, step S105, determining the target laying path of the target cable based on the theoretical magnetic field distribution data, may include the following steps:

[0121] 51. Inject a second preset current signal into the target cable to generate a magnetic field in the target cable;

[0122] 52. Obtain a preset cable distribution map in the target abnormal area, and determine several possible paths of the target cable based on the preset cable distribution map;

[0123] 53. Detect the actual magnetic field distribution data of the target cable on the first possible path using a magnetic field detection device; the first possible path is any one of the plurality of possible paths;

[0124] 54. Compare the actual magnetic field distribution data with the theoretical magnetic field distribution data to obtain the target similarity value;

[0125] 55. When the target similarity value is greater than or equal to a preset similarity value, the first possible path is determined to be the target laying path;

[0126] 56. When the target similarity value is less than the preset similarity value, it is determined that the first possible path is not a path to the target.

[0127] In this embodiment, the second preset current signal can be either default or preset in advance, and the magnetic field detection device can include at least one of the following: magnetometer, magnetic field detector, triaxial magnetoresistive sensor, electromagnetic field probe, etc., which are not limited here.

[0128] In a specific embodiment, the first part of the target cable in the target abnormal area on the ground can be determined first. A second preset current signal can be injected into the first part of the cable by a detection signal source (e.g., a signal generator). After injection, the second preset current signal will flow through the entire path of the target cable, and the target cable will generate a magnetic field.

[0129] Next, a preset cable distribution map of the target abnormal area can be obtained from the database of the target power distribution network. Based on the preset cable distribution map, several possible paths of the target cable can be inferred. One path is selected from the above possible paths, namely the first possible path. The actual magnetic field distribution data of the target cable on the first possible path is detected by magnetic field detection equipment. Specifically, several key positions on the first possible path can be determined first, and detection can be carried out at these key positions to obtain multiple magnetic field distribution data, that is, the actual magnetic field distribution data.

[0130] Furthermore, the actual magnetic field distribution data can be compared with the theoretical magnetic field distribution data to obtain the target similarity value. Specifically, a similarity calculation method (such as Euclidean distance, cosine similarity, correlation coefficient, etc.) can be used to calculate the similarity between the actual magnetic field distribution data and the theoretical magnetic field distribution data, i.e., the target similarity value. When the target similarity value is greater than or equal to the preset similarity value, the first possible path can be determined as the target laying path. When the target similarity value is less than the preset similarity value, the first possible path can be determined as not the target laying path. In addition, it is necessary to re-select other possible paths from the above-mentioned possible paths, except for the first possible path, for detection until the target laying path is determined.

[0131] Alternatively, another method can be used to determine the target laying path. Since there are many data points related to the magnetic field distribution, it is impossible to compare every single data point without computer calculation, as the workload would be too great. Therefore, when performing manual calculations, the magnetic field data at several key locations in the target cable can be identified and compared. For example, the magnetic field data directly above the target cable, the magnetic field data at the end of the target cable, etc. The target laying path can be determined by using the magnetic field data at these key locations. If the measured magnetic field distribution data at a certain key location matches the theoretical magnetic field distribution, then that location can be identified as a location in the target laying path. Then, the above steps can be repeated to obtain all locations where the measured magnetic field distribution data matches the theoretical magnetic field distribution data. The combination of these locations constitutes the target laying path.

[0132] It should be noted that the second preset current signal can be the same as the first preset current signal, so that the target cable can generate the same magnetic field as the above-mentioned mesh cable model.

[0133] S106. The target cable is inspected and maintained based on the target laying path and the target power quality anomaly data.

[0134] In this embodiment, the potential problems of the target cable can be determined first based on the target power quality anomaly data, and the target cable can be inspected and maintained along the target laying path based on the problem.

[0135] Optionally, step S106, which involves inspecting and maintaining the target cable based on the target laying path and the target power quality anomaly data, may include the following steps:

[0136] 61. Based on the target power quality anomaly data, determine several potential problems with the target cable;

[0137] 62. Determine the target detection equipment based on the aforementioned issues;

[0138] 63. The target cable is detected by the target detection device according to the target laying path to obtain the target problem of the target cable;

[0139] 64. Determine the target processing method corresponding to the target problem;

[0140] 65. Perform maintenance on the target cable according to the target processing method to restore the target cable to its normal state.

[0141] In this embodiment of the application, the target detection device may include at least one of the following: power quality analyzer, cable fault detector, and cable path detector;

[0142] In a specific embodiment, several potential problems with the target cable can be identified first based on the target power quality anomaly data. Specifically, abnormal indicators in the target power quality anomaly data can be identified. For example, if the grid frequency qualification rate in the target power quality anomaly data is lower than the normal value, it indicates that the target cable may have problems such as load imbalance, line aging, or external interference. Then, the target detection equipment can be determined based on the above-mentioned problems. For example, if there are many problems related to voltage and current, a power quality analyzer can be selected as the target detection equipment. In practical applications, the detection equipment can be flexibly selected according to the different problems.

[0143] Furthermore, the target cable is inspected along the target laying path using a target detection device to obtain the inspection results. Based on the inspection results, the target problem of the target cable is determined. Then, the target handling method corresponding to the target problem can be determined. Specifically, a pre-stored mapping relationship between preset problems and handling methods can be used to determine the target handling method corresponding to the target problem. Maintenance operations are then performed on the target cable according to the target handling method to restore the target cable to a normal state.

[0144] As can be seen, by implementing the embodiments of the present invention, target power quality data of the target power distribution network is obtained; target power quality anomaly data in the target power quality data is determined; target anomaly areas corresponding to the target power quality anomaly data and target cables corresponding to the target anomaly areas are determined; theoretical magnetic field distribution data corresponding to the target cables is obtained; when the target anomaly area is located underground or in a cable tunnel, the target laying path of the target cable is determined based on the theoretical magnetic field distribution data; the target cable is inspected and maintained according to the target laying path and the target power quality anomaly data. Thus, by obtaining the power quality anomaly data of the power distribution network, the anomaly area where the anomaly occurs is determined. Then, the laying path of the cable in the anomaly area, i.e., the cable anomaly path, is found according to the theoretical magnetic field distribution data. Since the theoretical magnetic field distribution data can be obtained through computer simulation and calculation without the need for physical equipment, compared with the traditional on-site survey and testing methods, the function of determining the cable anomaly path at a low cost is achieved.

[0145] Please see Figure 6 , Figure 6 This is a functional unit block diagram of a power quality anomaly path locating device 600 provided in an embodiment of this application. Figure 6 The power quality anomaly path locating device 600 shown can be applied to a server and includes: an acquisition unit 601, a determination unit 602, and a maintenance unit 603, wherein...

[0146] The acquisition unit 601 is used to acquire target power quality data of the target distribution network;

[0147] The determining unit 602 is used to determine target power quality abnormal data in the target power quality data; and to determine the target abnormal area corresponding to the target power quality abnormal data and the target cable corresponding to the target abnormal area.

[0148] The acquisition unit 601 is also used to acquire the theoretical magnetic field distribution data corresponding to the target cable;

[0149] The determining unit 602 is further configured to determine the target laying path of the target cable based on the theoretical magnetic field distribution data when the target abnormal area is located underground or in a cable tunnel.

[0150] The maintenance unit 603 is used to detect and maintain the target cable based on the target laying path and the target power quality anomaly data.

[0151] Optionally, in acquiring the theoretical magnetic field distribution data corresponding to the target cable, the acquisition unit 601 is specifically used for:

[0152] Obtain the target cable attribute data of the target cable;

[0153] Establish a target cable model based on the target cable attribute data;

[0154] Obtain the target laying environment data for the target cable;

[0155] A laying environment model is established based on the target laying environment data;

[0156] Determine the target positional relationship between the target cable model and the laying environment model;

[0157] Based on the target location relationship, the target cable model and the laying environment model are combined to form a target simulation model;

[0158] The theoretical magnetic field distribution data of the target cable are determined based on the target simulation model.

[0159] Optionally, in determining the theoretical magnetic field distribution data of the target cable based on the target simulation model, the acquisition unit 601 is further specifically used for:

[0160] The target cable model in the target simulation model is meshed to obtain a meshed cable model; the mesh shape includes one of the following: triangle, quadrilateral, or hexagon;

[0161] A first preset current signal is injected into the mesh cable model to generate a magnetic field in the mesh cable model;

[0162] Finite element analysis was performed on the mesh cable model to obtain the theoretical magnetic field distribution data of the mesh cable model under the laying environment model.

[0163] Optionally, in determining the target laying path of the target cable based on the theoretical magnetic field distribution data, the determining unit 602 is specifically used for:

[0164] A second preset current signal is injected into the target cable to generate a magnetic field in the target cable;

[0165] Obtain a preset cable distribution map in the target abnormal area, and determine several possible paths of the target cable based on the preset cable distribution map;

[0166] The actual magnetic field distribution data of the target cable on the first possible path is detected by a magnetic field detection device; the first possible path is any one of the plurality of possible paths;

[0167] The actual magnetic field distribution data is compared with the theoretical magnetic field distribution data to obtain the target similarity value;

[0168] When the target similarity value is greater than or equal to a preset similarity value, the first possible path is determined to be the target laying path;

[0169] When the target similarity value is less than the preset similarity value, it is determined that the first possible path is not a path to the target.

[0170] Optionally, in determining the target abnormal region corresponding to the target power quality abnormality data and the target cable corresponding to the target abnormal region, the determining unit 602 is further specifically used for:

[0171] Multiple power quality anomaly location data are obtained from the target power quality anomaly data;

[0172] A reference cable distribution map was drawn based on the data on the locations of the multiple power quality anomalies.

[0173] The reference cable distribution map is compared with the preset cable distribution map to determine the target abnormal area;

[0174] Obtain the cable data corresponding to the target abnormal area;

[0175] The target cable is determined based on the cable data.

[0176] Optionally, in the process of inspecting and maintaining the target cable based on the target laying path and the target power quality anomaly data, the maintenance unit 603 is specifically used for:

[0177] Based on the target power quality anomaly data, several potential problems with the target cable are identified.

[0178] The target detection equipment is determined based on the aforementioned issues;

[0179] The target cable is detected by the target detection device according to the target laying path to obtain the target problem of the target cable;

[0180] Determine the target processing method corresponding to the target problem;

[0181] The target cable is maintained according to the target processing method to restore it to a normal state.

[0182] Optionally, in determining the target power quality anomaly data in the target power quality data, the determining unit 602 is further specifically used for:

[0183] The target power quality data is cleaned to remove useless data and obtain reference power quality data. The useless data includes at least one of the following: erroneous data, expired data, and duplicate data.

[0184] Select all non-compliant data from the reference power quality data to obtain the target power quality anomaly data.

[0185] In specific implementations, the power quality anomaly path locating device 600 described in the embodiments of the present invention can also execute other implementations described in the power quality anomaly path locating method provided in the embodiments of the present invention, which will not be repeated here.

[0186] Please see Figure 7 , Figure 7 This is a schematic diagram of a server structure provided in an embodiment of this application. The server may include a processor, a memory, and a communication interface. The processor, memory, and communication interface can be interconnected via a bus. One or more programs are stored in the memory and configured to be executed by the processor. In this embodiment, the programs include instructions for performing the following steps:

[0187] Obtain target power quality data for the target distribution network;

[0188] Identify the target power quality anomaly data in the target power quality data;

[0189] Determine the target abnormal region corresponding to the target power quality abnormal data and the target cable corresponding to the target abnormal region;

[0190] Obtain the theoretical magnetic field distribution data corresponding to the target cable;

[0191] When the target anomalous area is located underground or in a cable tunnel, the target laying path of the target cable is determined based on the theoretical magnetic field distribution data.

[0192] The target cable is inspected and maintained based on the target laying path and the target power quality anomaly data.

[0193] Optionally, in obtaining the theoretical magnetic field distribution data corresponding to the target cable, the above procedure includes instructions for performing the following steps:

[0194] Obtain the target cable attribute data of the target cable;

[0195] Establish a target cable model based on the target cable attribute data;

[0196] Obtain the target laying environment data for the target cable;

[0197] A laying environment model is established based on the target laying environment data;

[0198] Determine the target positional relationship between the target cable model and the laying environment model;

[0199] Based on the target location relationship, the target cable model and the laying environment model are combined to form a target simulation model;

[0200] The theoretical magnetic field distribution data of the target cable are determined based on the target simulation model.

[0201] Optionally, in determining the theoretical magnetic field distribution data of the target cable based on the target simulation model, the above procedure includes instructions for performing the following steps:

[0202] The target cable model in the target simulation model is meshed to obtain a meshed cable model; the mesh shape includes one of the following: triangle, quadrilateral, or hexagon;

[0203] A first preset current signal is injected into the mesh cable model to generate a magnetic field in the mesh cable model;

[0204] Finite element analysis was performed on the mesh cable model to obtain the theoretical magnetic field distribution data of the mesh cable model under the laying environment model.

[0205] Optionally, in determining the target laying path of the target cable based on the theoretical magnetic field distribution data, the above procedure includes instructions for performing the following steps:

[0206] A second preset current signal is injected into the target cable to generate a magnetic field in the target cable;

[0207] Obtain a preset cable distribution map in the target abnormal area, and determine several possible paths of the target cable based on the preset cable distribution map;

[0208] The actual magnetic field distribution data of the target cable on the first possible path is detected by a magnetic field detection device; the first possible path is any one of the plurality of possible paths;

[0209] The actual magnetic field distribution data is compared with the theoretical magnetic field distribution data to obtain the target similarity value;

[0210] When the target similarity value is greater than or equal to a preset similarity value, the first possible path is determined to be the target laying path;

[0211] When the target similarity value is less than the preset similarity value, it is determined that the first possible path is not a path to the target.

[0212] Optionally, in determining the target abnormal region corresponding to the target power quality abnormality data and the target cable corresponding to the target abnormal region, the above procedure includes instructions for performing the following steps:

[0213] Multiple power quality anomaly location data are obtained from the target power quality anomaly data;

[0214] A reference cable distribution map was drawn based on the data on the locations of the multiple power quality anomalies.

[0215] The reference cable distribution map is compared with the preset cable distribution map to determine the target abnormal area;

[0216] Obtain the cable data corresponding to the target abnormal area;

[0217] The target cable is determined based on the cable data.

[0218] Optionally, in terms of inspecting and maintaining the target cable based on the target laying path and the target power quality anomaly data, the above procedure includes instructions for performing the following steps:

[0219] Based on the target power quality anomaly data, several potential problems with the target cable are identified.

[0220] The target detection equipment is determined based on the aforementioned issues;

[0221] The target cable is detected by the target detection device according to the target laying path to obtain the target problem of the target cable;

[0222] Determine the target processing method corresponding to the target problem;

[0223] The target cable is maintained according to the target processing method to restore it to a normal state.

[0224] Optionally, in determining the target power quality anomaly data in the target power quality data, the above procedure includes instructions for performing the following steps:

[0225] The target power quality data is cleaned to remove useless data and obtain reference power quality data. The useless data includes at least one of the following: erroneous data, expired data, and duplicate data.

[0226] Select all non-compliant data from the reference power quality data to obtain the target power quality anomaly data.

[0227] This application also provides a computer storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments, wherein the computer includes a server.

[0228] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may include a server.

[0229] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0230] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0231] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0232] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0233] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0234] If the integrated units described above are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0235] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for locating abnormal power quality paths, characterized in that, Applied to a server, the method includes: Obtain target power quality data for the target distribution network; Identify the target power quality anomaly data in the target power quality data; Determine the target abnormal region corresponding to the target power quality abnormal data and the target cable corresponding to the target abnormal region; Obtain the theoretical magnetic field distribution data corresponding to the target cable; When the target anomalous area is located underground or in a cable tunnel, the target laying path of the target cable is determined based on the theoretical magnetic field distribution data. The target cable is inspected and maintained based on the target laying path and the target power quality anomaly data. The step of obtaining the theoretical magnetic field distribution data corresponding to the target cable includes: Obtain the target cable attribute data of the target cable; Establish a target cable model based on the target cable attribute data; Obtain the target laying environment data of the target cable; the laying environment data includes at least one of the following: environmental structural parameters, environmental material composition data; A laying environment model is established based on the target laying environment data; To determine the target positional relationship between the target cable model and the laying environment model, specifically, the coordinate systems of the target cable model and the laying environment model are made the same coordinate system, the actual positional relationship between the target cable and the laying environment in reality is obtained, and the target positional relationship between the target cable model and the laying environment model in the coordinate system is determined based on the actual positional relationship. Based on the target location relationship, the target cable model and the laying environment model are combined to form a target simulation model; The theoretical magnetic field distribution data of the target cable are determined based on the target simulation model.

2. The method as described in claim 1, characterized in that, The step of determining the theoretical magnetic field distribution data of the target cable based on the target simulation model includes: The target cable model in the target simulation model is meshed to obtain a meshed cable model; the mesh shape includes one of the following: triangle, quadrilateral, or hexagon; A first preset current signal is injected into the mesh cable model to generate a magnetic field in the mesh cable model; Finite element analysis was performed on the mesh cable model to obtain the theoretical magnetic field distribution data of the mesh cable model under the laying environment model.

3. The method as described in claim 1 or 2, characterized in that, Determining the target laying path of the target cable based on the theoretical magnetic field distribution data includes: A second preset current signal is injected into the target cable to generate a magnetic field in the target cable; Obtain a preset cable distribution map in the target abnormal area, and determine several possible paths of the target cable based on the preset cable distribution map; The actual magnetic field distribution data of the target cable on the first possible path is detected by a magnetic field detection device; the first possible path is any one of the plurality of possible paths; The actual magnetic field distribution data is compared with the theoretical magnetic field distribution data to obtain the target similarity value; When the target similarity value is greater than or equal to a preset similarity value, the first possible path is determined to be the target laying path; When the target similarity value is less than the preset similarity value, it is determined that the first possible path is not a path to the target.

4. The method as described in claim 3, characterized in that, The step of determining the target abnormal region corresponding to the target power quality abnormal data and the target cable corresponding to the target abnormal region includes: Multiple power quality anomaly location data are obtained from the target power quality anomaly data; A reference cable distribution map was drawn based on the data on the locations of the multiple power quality anomalies. The reference cable distribution map is compared with the preset cable distribution map to determine the target abnormal area; Obtain the cable data corresponding to the target abnormal area; The target cable is determined based on the cable data.

5. The method as described in claim 1 or 2, characterized in that, The step of inspecting and maintaining the target cable based on the target laying path and the target power quality anomaly data includes: Based on the target power quality anomaly data, several potential problems with the target cable are identified. The target detection equipment is determined based on the aforementioned issues; The target cable is detected by the target detection device according to the target laying path to obtain the target problem of the target cable; Determine the target processing method corresponding to the target problem; The target cable is maintained according to the target processing method to restore it to a normal state.

6. The method as described in claim 1 or 2, characterized in that, The step of determining the target power quality anomaly data in the target power quality data includes: The target power quality data is cleaned to remove useless data and obtain reference power quality data. The useless data includes at least one of the following: erroneous data, expired data, and duplicate data. Select all non-compliant data from the reference power quality data to obtain the target power quality anomaly data.

7. A device for locating abnormal power quality paths, used to perform the method as described in any one of claims 1-6, characterized in that, The power quality anomaly path location device includes: an acquisition unit, a determination unit, and a maintenance unit, wherein, The acquisition unit is used to acquire target power quality data of the target distribution network; The determining unit is used to determine target power quality anomaly data in the target power quality data; and to determine the target anomaly region corresponding to the target power quality anomaly data and the target cable corresponding to the target anomaly region. The acquisition unit is also used to acquire theoretical magnetic field distribution data corresponding to the target cable; The determining unit is further configured to determine the target laying path of the target cable based on the theoretical magnetic field distribution data when the target abnormal area is located underground or in a cable tunnel. The maintenance unit is used to inspect and maintain the target cable based on the target laying path and the target power quality anomaly data.

8. A server, characterized in that, include: A processor and a memory, the memory being used to store one or more programs and configured to be executed by the processor, the programs including instructions for performing the steps of the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, A computer program for storing electronic data interchange is provided, wherein the computer program causes a computer to perform the method as described in any one of claims 1-6.

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