A method and device for constructing a digital twin data model of a low-voltage distribution substation area

Abstract

The present application discloses a method and device for constructing a digital twin data model of a low-voltage distribution substation area. The method provided by the present application is based on the entity objects in the target low-voltage distribution substation area, collects the characteristic data of the entity objects, and then, based on the characteristic data of the entity objects, combines the corresponding relationship between the preset characteristic data types and the characteristic association information, and establishes an association relationship for different characteristic data according to the characteristic association information corresponding to different characteristic data. Finally, based on the associated characteristic data, a substation area digital twin model corresponding to the target low-voltage distribution substation area is constructed. The substation area digital twin model constructed by the method of the present application is more in line with the actual situation of the low-voltage distribution network, and solves the technical problem that the existing digitalized model of the low-voltage distribution network substation area has low accuracy.

Description

Technical Field

[0001] The present application relates to the field of power technology, and in particular, to a method and device for constructing a digital twin data model of a low-voltage distribution substation area. Background Art

[0002] In recent years, in order to achieve the national goals of carbon peak and carbon neutrality, power grid companies have actively built a new power system with new energy as the main body, and the digital power grid is the best form to carry the new power system. The low-voltage distribution substation area is an important part of the power grid. At present, the digitalization level of the high-voltage main grid is relatively mature. Especially at the end of the power grid, the digitalization level of the low-voltage distribution substation area is even lower. In order to better manage the low-voltage distribution substation area, building a digital substation area model to realize the digital management of the low-voltage distribution network has become one of the key development projects of power grid companies at present.

[0003] However, there are many types of facilities and equipment in the low-voltage distribution network, and the data relationships are complex and intertwined, making it difficult to digitalize. The traditional construction of the digital model of the low-voltage distribution network does not consider the intertwined association between different characteristic data of physical entity objects, which does not conform to the actual situation of the low-voltage distribution network, resulting in the technical problem of low accuracy in the existing digital models of low-voltage distribution substation areas. Summary of the Invention

[0004] The present application provides a method and device for constructing a digital twin data model of a low-voltage distribution substation area, which is used to solve the technical problem of low accuracy in the existing digital models of low-voltage distribution substation areas.

[0005] The first aspect of the present application provides a method for constructing a digital twin data model of a low-voltage distribution substation area, including:

[0006] Collecting characteristic data of entity objects based on the entity objects in the target low-voltage distribution substation area;

[0007] Based on the characteristic data, associating different characteristic data in combination with the corresponding relationship between the preset characteristic data types and characteristic association information;

[0008] Based on the associated characteristic data, constructing a substation area digital twin model corresponding to the target low-voltage distribution substation area.

[0009] Preferably, the entity objects specifically include: power facilities, electrical equipment, and power lines.

[0010] Preferably, the characteristic data includes: static attribute data, three-dimensional model data, document data, topology data, monitoring and metering point data, dynamic monitoring data, and power flow simulation data.

[0011] Preferably, the associating different feature data based on the feature data in combination with the corresponding relationship between the preset feature data types and feature association information specifically includes:

[0012] When the feature data to be associated are static attribute data and 3D model data, the static attribute data and the 3D model data are associated according to the model identifier, where the model identifier is used to indicate the model parameters of the entity object so as to correspond to the model identifier of the 3D model data;

[0013] When the feature data to be associated are static attribute data and topology data, the static attribute data and the topology data are associated according to the topology identifier, where the topology identifier is used to indicate the topological connection relationship between the entity object and other entity objects;

[0014] When the feature data to be associated are static attribute data and document data, the static attribute data and the document data are associated according to the asset identifier, where the asset identifier is used to refer to the entity object;

[0015] When the feature data to be associated are monitoring and metering point data and static attribute data, the static attribute data and the static attribute data are associated according to the asset identifier;

[0016] When the feature data to be associated are monitoring and metering point data and document data, the static attribute data and the document data are associated according to the asset identifier;

[0017] When the feature data to be associated are monitoring and metering point data and dynamic monitoring data, the monitoring and metering point data and the dynamic monitoring data are associated according to the monitored quantity identifier, where the monitored quantity identifier is used to indicate the monitoring variable in the dynamic monitoring data;

[0018] When the feature data to be associated are topology data and power flow simulation data, the topology data and the power flow simulation data are associated according to the variable identifier, where the variable identifier is an identifier used to indicate the power flow calculation solution, and the power flow calculation solution is the unique solution obtained through basic power flow simulation calculation.

[0019] Preferably, it further includes:

[0020] Obtain the map data within the target low-voltage distribution substation area;

[0021] Associate the static attribute data and the map data according to the geographical location information, where the geographical location information is used to indicate the geographical location of the entity object.

[0022] The second aspect of the present application provides a device for constructing a digital twin data model of a low-voltage distribution substation area, including:

[0023] A feature data acquisition unit, configured to collect feature data of the entity objects based on the entity objects in the target low-voltage distribution substation area;

[0024] A feature data association processing unit, configured to associate different feature data based on the feature data in combination with the corresponding relationship between the preset feature data types and feature association information;

[0025] A model construction unit, configured to construct a substation area digital twin model corresponding to the target low-voltage distribution substation area based on the associated feature data.

[0026] Preferably, the entity objects specifically include: power facilities, electrical equipment, and power lines.

[0027] Preferably, the feature data includes: static attribute data, three-dimensional model data, document data, topology data, monitoring and metering point data, dynamic monitoring data, and power flow simulation data.

[0028] Preferably, the feature data association processing unit is specifically configured to:

[0029] When the feature data to be associated is static attribute data and three-dimensional model data, the static attribute data and the three-dimensional model data are associated according to the model identification, where the model identification is used to indicate the model parameters of the entity object so as to correspond to the model identification of the three-dimensional model data;

[0030] When the feature data to be associated is static attribute data and topology data, the static attribute data and the topology data are associated according to the topology identification, where the topology identification is used to indicate the topological connection relationship between the entity object and other entity objects;

[0031] When the feature data to be associated is static attribute data and document data, the static attribute data and the document data are associated according to the asset identification, where the asset identification is used to refer to the entity object;

[0032] When the feature data to be associated is monitoring and metering point data and static attribute data, the static attribute data and the static attribute data are associated according to the asset identification;

[0033] When the feature data to be associated is monitoring and metering point data and document data, the static attribute data and the document data are associated according to the asset identification;

[0034] When the feature data to be associated are monitoring measurement point data and dynamic monitoring data, the monitoring measurement point data and the dynamic monitoring data are associated according to the measurement identifier, where the measurement identifier is used to indicate the monitoring variable in the dynamic monitoring data;

[0035] When the feature data to be associated are topology data and power flow simulation data, the topology data and the power flow simulation data are associated according to the variable identifier, where the variable identifier is an identifier used to indicate the solution of the power flow calculation, and the solution of the power flow calculation is the unique solution obtained through the basic power flow simulation calculation.

[0036] Preferably, it further includes:

[0037] A map data acquisition unit, configured to acquire map data within the scope of the target low-voltage distribution substation area;

[0038] A map data association processing unit, configured to associate the static attribute data and the map data according to the geographical location information, where the geographical location information is used to indicate the geographical location of the entity object.

[0039] From the above technical solutions, it can be seen that the present application has the following advantages:

[0040] The method provided by the present application is based on the entity objects in the target low-voltage distribution substation area, collects the feature data of the entity objects, and then, based on the feature data of the entity objects, combines the corresponding relationship between the preset feature data types and the feature association information, and establishes an association relationship for different feature data according to the feature association information corresponding to different feature data. Finally, based on the associated feature data, a substation area digital twin model corresponding to the target low-voltage distribution substation area is constructed. The substation area digital twin model constructed by the method of the present application is more in line with the actual situation of the low-voltage distribution network, and solves the technical problem that the existing digital models of low-voltage distribution substation areas have low accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0042] Figure 1 It is a schematic flowchart of the first embodiment of a method for constructing a digital twin data model of a low-voltage distribution substation area provided by the present application.

[0043] Figure 2Schematic flowchart of the second embodiment of the method for constructing a digital twin data model of a low-voltage distribution substation area provided by this application.

[0044] Figure 3 Schematic diagram of the characteristic data association relationship of the method for constructing a digital twin data model of a low-voltage distribution substation area provided by this application.

[0045] Figure 4 Schematic structural diagram of an embodiment of the device for constructing a digital twin data model of a low-voltage distribution substation area provided by this application. Detailed implementation manners

[0046] The embodiments of this application provide a method, device, terminal, and medium for constructing a digital twin data model of a low-voltage distribution substation area, which are used to solve the technical problem that the existing digital models of low-voltage distribution network substation areas have low accuracy.

[0047] To make the invention objectives, features, and advantages of this application more obvious and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Obviously, the embodiments described below are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0048] The following is a detailed description of the first embodiment provided by this application.

[0049] Please refer to Figure 1 , this embodiment provides a method for constructing a digital twin data model of a low-voltage distribution substation area, including:

[0050] Step 101: Based on the entity objects in the target low-voltage distribution substation area, collect the characteristic data of the entity objects.

[0051] It should be noted that, first, based on the target low-voltage distribution substation area for which a digital model needs to be constructed, according to the entity objects in the target low-voltage distribution substation area, and collect the characteristic data of these entity objects.

[0052] Step 102: Based on the characteristic data, in combination with the corresponding relationship between the preset characteristic data types and characteristic association information, associate different characteristic data.

[0053] Among them, the characteristic association information mentioned in this embodiment is usually some specific field information included in the characteristic data.

[0054] It should be noted that in the process of associating different feature data, according to the feature association information corresponding to the type of feature data to be associated, and based on the common feature association information in the feature data to be associated, an association relationship is established for two or more different types of feature data.

[0055] Step 103: Based on the associated feature data, construct a digital twin model corresponding to the target low-voltage distribution area.

[0056] It should be noted that after the association process in Step 102, a digital twin model corresponding to the target low-voltage distribution area can be constructed based on the associated feature data.

[0057] The method provided in this application is based on the entity objects in the target low-voltage distribution area, collects the feature data of the entity objects, then based on the feature data of the entity objects, combines the corresponding relationship between the preset feature data types and feature association information, and according to the feature association information corresponding to different feature data, establishes an association relationship for different feature data. Finally, based on the associated feature data, a digital twin model corresponding to the target low-voltage distribution area is constructed. The digital twin model constructed by the method of this application is more in line with the actual situation of the low-voltage distribution network, and solves the technical problem that the existing digital models of low-voltage distribution network areas have low accuracy.

[0058] The above content is the detailed description of the first embodiment of the method for constructing a digital twin data model of a low-voltage distribution area provided by this application. The following content is the detailed description of the second embodiment of the method for constructing a digital twin data model of a low-voltage distribution area provided by this application.

[0059] Please refer to Figure 2 , the second embodiment of this application, on the basis of the content of the first embodiment mentioned above, further includes the following features:

[0060] Further, the entity objects specifically include: power facilities, electrical equipment, and power lines.

[0061] Further, the feature data includes: static attribute data, three-dimensional model data, document data, topology data, monitoring and metering point data, dynamic monitoring data, and power flow simulation data.

[0062] In this embodiment, the physical entities in the digital twin area include: power facilities, electrical equipment, wires, etc. Each physical entity corresponds to static attribute data, three-dimensional model data, and document data.

[0063] Among them, the static attribute data includes the parameters of the device itself, geographical location information, number, etc., mainly including the following items: model identification, rated voltage, geographical information, location information, operating status, manufacturer, operating tap position, number of phases, topology identification, asset identification, etc.; for wire types, it also includes: laying method, number of cores, voltage level, current-carrying capacity, length, whether it is the main line, property rights unit, construction unit, maintenance unit.

[0064] The 3D model data mainly covers important objects such as low-voltage distribution substation area equipment, overhead conductors, and underground cables. The main requirements for the model are as follows: First, the object should truly reflect the specific spatial form and mutual relationship of the object in the distribution network management environment through a 3D solid model, and have measurable 3D space; second, the 3D model can be assembled, and its position and size information can be modified. The 3D distribution model library is the intuitive presentation of the 3D design parameters of the main low-voltage distribution substation area equipment. In the 3D scene, when designers perform interactive operations on the 3D model, on the surface, it is the modification of vector points, lines, and surfaces, but actually the final changed object is the 3D model itself, rather than the 2D vector data.

[0065] The document data specifically refers to some document text data related to the entity object, mainly documents related to project management, including the overhead wire path agreement in the preliminary planning, underground cable design specifications, technical parameters of distribution equipment, etc.

[0066] In the digital substation area, the topological connection relationship between physical entities is stored by the topological data set, and the topological data set forms a one-to-one correspondence with the primary electrical wiring diagram.

[0067] The topological data set is a data set expressing the connection relationship of physical entity objects, including the primary connection relationship of electrical equipment, the secondary connection relationship of monitoring and control equipment, and the physical connection relationship of wires and equipment placement. In the topological data, the parent and child nodes of physical entities can be recorded, expressing a unique topological relationship, which is uniquely corresponding to the primary electrical wiring diagram of the GIS system.

[0068] Some physical entities have monitoring and metering points. For example, there are monitoring and metering devices at the transformer outlet, key branches, and user inlets, and the same monitoring and metering point may include the monitoring of multiple physical entities, which is a one-to-many relationship. For example, the same monitoring and metering point can monitor the electricity consumption information of multiple circuits. The monitoring and metering point data is a specific data set of secondary equipment, expressing the corresponding relationship between secondary equipment and primary equipment, the surrounding environment, and events. The monitoring and metering point data can record the dynamic monitoring data of multiple primary equipment or various environmental and equipment types.

[0069] Dynamic monitoring data includes all data types that can be monitored by the monitoring measurement points, not only including electricity consumption information, but also including dynamic change data such as environment and events. Dynamic monitoring data is a specific data set of monitoring measurement data, recording the dynamic monitoring data of the monitoring measurement points, with time stamps, including data that changes over time such as voltage, current, active power, reactive power, temperature, humidity, and leakage events.

[0070] The power flow simulation data provides a basic power flow calculation algorithm rule data set, specifically including only the power flow calculation method rules through the simulation calculation algorithm.

[0071] Furthermore, please refer to Figure 3 , the association of different feature data based on the feature data mentioned in this embodiment, in combination with the corresponding relationship between the preset feature data types and feature association information, specifically includes:

[0072] When the feature data to be associated are static attribute data and 3D model data, the static attribute data and 3D model data are associated according to the model identifier, where the model identifier is used to indicate the model parameters of the entity object so as to correspond to the model identifier of the 3D model data.

[0073] It should be noted that the static attribute data and 3D model data in this embodiment are associated through the model identifier, which can uniquely represent the 3D model corresponding to a certain physical entity. The attribute data also includes spatial information such as the placement location, orientation, and elevation angle of the physical entity, assisting the display of the 3D model in the map data.

[0074] When the feature data to be associated are static attribute data and topology data, the static attribute data and topology data are associated according to the topology identifier, where the topology identifier is used to indicate the topological connection relationship between the entity object and other entity objects.

[0075] It should be noted that the static attribute data and topology data are associated through the topology identifier. The topology identifier refers to the parent-child node numbers in the topology data set. In the topology data, the connection relationships between the topology identifiers form a complete topology graph, and the physical entity is uniquely pointed to through the topology identifier.

[0076] When the feature data to be associated are static attribute data and document data, the static attribute data and document data are associated according to the asset identifier, where the asset identifier is used to refer to the entity object.

[0077] It should be noted that the attribute data and document data are associated through the asset identifier. The asset identifier is the unique corresponding number of the physical entity, and the corresponding document data is pointed to through the asset identifier, mainly non-structured data, including instructions, contracts, videos, pictures, etc.

[0078] When the feature data to be associated are monitoring measurement point data and static attribute data, the static attribute data and the static attribute data are associated according to the asset identifier.

[0079] It should be noted that the attribute data and the monitoring measurement point data are associated through the asset identifier. One monitoring measurement point can correspond to multiple physical entities, which is a one-to-many relationship. The monitoring measurement point data points to the physical entity it monitors through the asset identifier.

[0080] When the feature data to be associated are monitoring measurement point data and document data, the static attribute data and the document data are associated according to the asset identifier.

[0081] When the feature data to be associated are monitoring measurement point data and dynamic monitoring data, the monitoring measurement point data and the dynamic monitoring data are associated according to the measurement identifier, where the measurement identifier is used to indicate the monitoring variable in the dynamic monitoring data.

[0082] It should be noted that the monitoring measurement point data and the dynamic monitoring data are associated through the monitoring identifier. One monitoring measurement point has multiple monitored physical quantities, which is a one-to-many relationship. Each dynamic monitoring data has a unique monitoring identifier, and different monitored physical quantities are pointed to through the monitoring identifier.

[0083] When the feature data to be associated are topology data and power flow simulation data, the topology data and the power flow simulation data are associated according to the variable identifier, where the variable identifier is an identifier used to indicate the solution of the power flow calculation, and the solution of the power flow calculation is the unique solution obtained through the basic power flow simulation calculation.

[0084] It should be noted that the power flow simulation data is associated with the topology data and the dynamic monitoring data through the variable identifier, where the variable identifier is the unique solution of the power flow calculation in the digital twin simulation calculation. Each simulation calculation algorithm points to the power flow node through the unique variable identifier and then points to the dynamic detection data of a certain time section.

[0085] Furthermore, it also includes:

[0086] Step 1001: Obtain the map data within the target low-voltage distribution substation area.

[0087] Among them, the map data includes vector data, DEM terrain data, raster image data, etc., and mainly includes the following items: basic geographic information data, human feature data, contour vector data in terrain information, and relative position information data between objects.

[0088] Step 1002: Associate the static attribute data and the map data according to the geographic location information, where the geographic location information is used to indicate the geographic location of the entity object.

[0089] It should be noted that the static attribute data and the map data are associated through the geographical location information field, which can uniquely represent the coordinate position of a certain physical entity on the map.

[0090] The above content is the detailed description of the second embodiment of a method for constructing a digital twin data model of a low-voltage distribution substation area provided by this application. The following content is the detailed description of an embodiment of a device for constructing a digital twin data model of a low-voltage distribution substation area provided by this application.

[0091] Please refer to Figure 4 , a third embodiment of this application provides a device for constructing a digital twin data model of a low-voltage distribution substation area, including:

[0092] A feature data acquisition unit 201, configured to collect feature data of an entity object based on the entity object in the target low-voltage distribution substation area;

[0093] A feature data association processing unit 202, configured to associate different feature data based on the feature data in combination with the corresponding relationship between the preset feature data type and the feature association information;

[0094] A model construction unit 203, configured to construct a substation area digital twin model corresponding to the target low-voltage distribution substation area based on the associated feature data.

[0095] Further, the entity object specifically includes: power facilities, electrical equipment, and power lines.

[0096] Further, the feature data includes: static attribute data, three-dimensional model data, document data, topology data, monitoring and metering point data, dynamic monitoring data, and power flow simulation data.

[0097] Further, the feature data association processing unit is specifically configured to:

[0098] When the feature data to be associated is static attribute data and three-dimensional model data, the static attribute data and the three-dimensional model data are associated according to the model identifier, where the model identifier is used to indicate the model parameters of the entity object so as to correspond to the model identifier of the three-dimensional model data;

[0099] When the feature data to be associated is static attribute data and topology data, the static attribute data and the topology data are associated according to the topology identifier, where the topology identifier is used to indicate the topological connection relationship between the entity object and other entity objects;

[0100] When the feature data to be associated is static attribute data and document data, the static attribute data and the document data are associated according to the asset identifier, where the asset identifier is used to refer to the entity object;

[0101] When the feature data to be associated is monitoring measurement point data and static attribute data, the static attribute data and the static attribute data are associated according to the asset identifier;

[0102] When the feature data to be associated is monitoring measurement point data and document data, the static attribute data and the document data are associated according to the asset identifier;

[0103] When the feature data to be associated is monitoring measurement point data and dynamic monitoring data, the monitoring measurement point data and the dynamic monitoring data are associated according to the measurement identifier, where the measurement identifier is used to indicate the monitoring variable in the dynamic monitoring data;

[0104] When the feature data to be associated is topology data and power flow simulation data, the topology data and the power flow simulation data are associated according to the variable identifier, where the variable identifier is an identifier used to indicate the solution of the power flow calculation, and the solution of the power flow calculation is the unique solution obtained through the basic power flow simulation calculation.

[0105] Furthermore, it further includes:

[0106] A map data acquisition unit 2001, configured to acquire map data within the range of the target low-voltage distribution area;

[0107] A map data association processing unit 2002, configured to associate the static attribute data and the map data according to the geographical location information, where the geographical location information is used to indicate the geographical location of the entity object.

[0108] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0109] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be in an electrical, mechanical or other form.

[0110] The terms "first", "second", "third", "fourth", etc. (if any) in the description of this application and the above-mentioned drawings are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of this application described here, for example, can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0111] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0112] In addition, each functional unit in various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0113] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0114] As described above, the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for constructing a digital twin data model of a low-voltage distribution substation area, characterized in that, Including: Based on the entity objects in the target low-voltage distribution area, collect the characteristic data of the entity objects. The entity objects specifically include: power facilities, electrical equipment, and power lines. The characteristic data includes: static attribute data, 3D model data, document data, topology data, monitoring and metering point data, dynamic monitoring data, and power flow simulation data; When the characteristic data to be associated are static attribute data and 3D model data, then associate the static attribute data and the 3D model data according to the model identification, where the model identification is used to indicate the model parameters of the entity object so as to correspond to the model identification of the 3D model data; When the characteristic data to be associated are static attribute data and topology data, then associate the static attribute data and the topology data according to the topology identification, where the topology identification is used to indicate the topological connection relationship between the entity object and other entity objects; When the characteristic data to be associated are static attribute data and document data, then associate the static attribute data and the document data according to the asset identification, where the asset identification is used to represent the entity object; When the characteristic data to be associated are monitoring and metering point data and static attribute data, then associate the static attribute data and the static attribute data according to the asset identification; When the characteristic data to be associated are monitoring and metering point data and document data, then associate the static attribute data and the document data according to the asset identification; When the characteristic data to be associated are monitoring and metering point data and dynamic monitoring data, then associate the monitoring and metering point data and the dynamic monitoring data according to the monitoring quantity identification, where the monitoring quantity identification is used to indicate the monitoring variables in the dynamic monitoring data; When the characteristic data to be associated are topology data and power flow simulation data, then associate the topology data and the power flow simulation data according to the variable identification, where the variable identification is the identification used to indicate the power flow calculation solution, and the power flow calculation solution is the unique solution obtained through basic power flow simulation calculation; Based on the associated characteristic data, construct a digital twin model of the area corresponding to the target low-voltage distribution area.

2. The method for constructing a digital twin data model of a low-voltage distribution substation area according to claim 1, wherein Also including: Obtain the map data within the scope of the target low-voltage distribution area; Associate the static attribute data and the map data according to the geographical location information, where the geographical location information is used to indicate the geographical location of the entity object.

3. A device for constructing a digital twin data model of a low-voltage distribution substation area, characterized in that, Including: A characteristic data acquisition unit, which is used to collect the characteristic data of the entity objects based on the entity objects in the target low-voltage distribution area. The entity objects specifically include: power facilities, electrical equipment, and power lines. The characteristic data includes: static attribute data, 3D model data, document data, topology data, monitoring and metering point data, dynamic monitoring data, and power flow simulation data; A characteristic data association processing unit, which is used to associate different characteristic data based on the characteristic data in combination with the corresponding relationship between the preset characteristic data types and characteristic association information. A model construction unit for constructing a digital twin model of the target low-voltage distribution area based on the associated feature data; The specific feature data association processing unit is used for: When the feature data to be associated are static attribute data and 3D model data, the static attribute data and the 3D model data are associated according to the model identifier, where the model identifier is used to indicate the model parameters of the entity object so as to correspond to the model identifier of the 3D model data; When the feature data to be associated are static attribute data and topology data, the static attribute data and the topology data are associated according to the topology identifier, where the topology identifier is used to indicate the topological connection relationship between the entity object and other entity objects; When the feature data to be associated are static attribute data and document data, the static attribute data and the document data are associated according to the asset identifier, where the asset identifier is used to refer to the entity object; When the feature data to be associated are monitoring measurement point data and static attribute data, the static attribute data and the static attribute data are associated according to the asset identifier; When the feature data to be associated are monitoring measurement point data and document data, the static attribute data and the document data are associated according to the asset identifier; When the feature data to be associated are monitoring measurement point data and dynamic monitoring data, the monitoring measurement point data and the dynamic monitoring data are associated according to the measurement identifier, where the measurement identifier is used to indicate the monitoring variable in the dynamic monitoring data; When the feature data to be associated are topology data and power flow simulation data, the topology data and the power flow simulation data are associated according to the variable identifier, where the variable identifier is an identifier used to indicate the solution of the power flow calculation, and the solution of the power flow calculation is the unique solution obtained through basic power flow simulation calculation.

4. The digital twin data model construction device for a low-voltage distribution substation area according to claim 3, wherein, It further includes: A map data acquisition unit for acquiring map data within the scope of the target low-voltage distribution area; A map data association processing unit for associating the static attribute data and the map data according to the geographical location information, where the geographical location information is used to indicate the geographical location of the entity object.

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