A power grid data asset management method, system, device and storage medium

Abstract

The application discloses a kind of power grid data asset management method, system, equipment and storage medium, wherein method includes: obtaining power grid data;Power grid data is extracted and integrated to obtain the entity data corresponding to power grid data, and entity data includes entity, entity attribute and entity relationship;According to the entity data of power grid data and the business category of power grid data, generate data asset directory structure rule, and construct the data asset directory corresponding to data asset directory structure rule, corresponding mapping is obtained by mapping relationship between power grid data and data asset directory;According to the entity data of power grid data, mapping relationship, asset directory constructs data map, and according to data map, power grid data is managed as an asset.This embodiment of the application associates power grid data with data asset directory by mapping relationship, and visualizes and displays power grid data by constructing data map, which can effectively improve the management efficiency of power grid data asset.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid information technology management, and in particular to a power grid data asset management method, system, device and storage medium. BACKGROUND

[0002] At present, with the gradual deepening of the informationization construction of State Grid Corporation of China, as an important asset of power grid enterprises, power big data has great social application value. The power data has a large amount of high-value data information such as power consumption data, user power consumption behavior and customer interaction. Among them, the power consumption data is an important indicator reflecting the economic and industry development situation, such as one of the indicators of the Keliang index, i.e. power consumption. The combination of power and customer data can provide data and service support for various policy decisions, social services and new business models. The informationization construction of power enterprises develops rapidly, and a large amount of power grid data is generated from various information systems. However, the existing electric data asset management method is difficult to effectively manage the power grid data, resulting in low efficiency of power grid data asset management. SUMMARY

[0003] The present application provides a power grid data asset management method, system, device and storage medium to solve the technical problem that the existing electric data asset management method is difficult to effectively manage the power grid data, resulting in low efficiency of power grid data asset management.

[0004] One embodiment of the present application provides a power grid data asset management method, comprising:

[0005] obtaining power grid data;

[0006] performing data extraction and integration on the power grid data to obtain entity data corresponding to the power grid data, the entity data including entities, entity attributes and entity relationships;

[0007] generating a data asset directory structure rule according to the entity data of the power grid data and the business category of the power grid data, and constructing a data asset directory corresponding to the data asset directory structure rule, and mapping the power grid data and the data asset directory to obtain a mapping relationship;

[0008] constructing a data map according to the entity data of the power grid data, the mapping relationship and the data asset directory, and performing asset management on the power grid data according to the data map.

[0009] Further, the power grid data includes unstructured power grid data and structured power grid data, and the performing data extraction and integration on the power grid data to obtain the entity data corresponding to the power grid data comprises:

[0010] The table structure of the structured power grid data is analyzed, and the entity data of the structured power grid data is obtained through the primary and foreign key information of the table structure.

[0011] Extract the entities and entity attributes from the unstructured power grid data, and perform data analysis on the unstructured power grid data to obtain the entity relationships of the unstructured power grid data.

[0012] Furthermore, after obtaining the entity data corresponding to the power grid data, the method also includes:

[0013] The entities corresponding to the unstructured power grid data are integrated so that the structure of the entities in the unstructured power grid data is the same as the structure of the entities in the structured power grid data.

[0014] Furthermore, the step of performing data analysis on the unstructured power grid data to obtain the entity relationships of the unstructured power grid data includes:

[0015] The entities and entity attributes of the unstructured power grid data are input into a pre-trained deep learning model, and the entity relationships of the unstructured power grid data are obtained through data analysis performed by the deep learning model.

[0016] Furthermore, the step of constructing a data map based on the entity data of the power grid data, the mapping relationship, and the data asset catalog includes:

[0017] If the data assets of the power grid data change, the data asset catalog is updated according to the data asset change information of the power grid data, and a data map is constructed based on the updated data asset catalog, the entity data, and the mapping relationship.

[0018] Furthermore, after performing asset management on the power grid data, the management method further includes:

[0019] A cost input comparison analysis is conducted on the equipment costs, equipment failure data, and maintenance records of each link in the power system, and the results of the comparison analysis are used to determine whether each piece of equipment should be scrapped or removed or retained.

[0020] Based on the comparison results, the cost investment distribution is obtained. Based on the cost investment distribution of each piece of equipment throughout its entire life cycle, it is predicted whether each piece of equipment meets the conditions for dismantling and scrapping.

[0021] Furthermore, the business categories include: operation and maintenance services, user services, billing services, electricity information collection services, and marketing services.

[0022] One embodiment of the present invention provides a power grid data asset management system, comprising:

[0023] The power grid data acquisition module is used to acquire power grid data.

[0024] The power grid data integration module is used to extract and integrate the power grid data to obtain the entity data corresponding to the power grid data. The entity data includes entities, entity attributes, and entity relationships.

[0025] The mapping relationship generation module is used to generate data asset catalog structure rules based on the entity data and business category of the power grid data, construct the data asset catalog corresponding to the data asset catalog structure rules, and map the power grid data to the data asset catalog to obtain the mapping relationship.

[0026] The data asset management module is used to construct a data map based on the entity data of the power grid data, the mapping relationship, and the data asset catalog, and to manage the power grid data assets based on the data map.

[0027] One embodiment of the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the power grid data asset management method described above.

[0028] One embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the power grid data asset management method described above.

[0029] This invention, through its embodiments, acquires entity data corresponding to power grid data and generates a data asset catalog structure based on the entity data and the business category of the power grid data. By constructing a data asset catalog corresponding to this structure, a mapping relationship is obtained by mapping power grid data to the data asset catalog. This mapping relationship links power grid data with the data asset catalog, enabling convenient retrieval of power grid data through the data asset catalog. Furthermore, data traceability can be performed based on this mapping relationship, which is beneficial for improving the efficiency of power grid data asset management. This invention also visualizes power grid data assets by constructing a data map, improving the convenience of power grid data asset management and further enhancing its efficiency. Attached Figure Description

[0030] Figure 1 This is a flowchart illustrating the power grid data asset management method provided in an embodiment of the present invention;

[0031] Figure 2 This is a schematic diagram of the structure of the power grid data asset management system provided in an embodiment of the present invention;

[0032] Figure 3 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0034] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "multiple" means two or more.

[0035] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0036] This invention can be implemented based on a data middle platform, which is a mechanism located between the underlying data platform and the upper-layer business applications. The power grid data middle platform is a logical concept that aggregates and governs cross-domain data, abstracts and encapsulates data into services, and provides them to the front end with business value. This invention, based on a data middle platform, implements power grid data asset management, effectively reducing the technical complexity of the underlying platform. It enables the establishment of enterprise data assets to form a data system through data access and development via the data middle platform; and it can transform data assets into different data service capabilities through data asset management, thereby serving various businesses of the power company.

[0037] Please see Figure 1 The first embodiment of the present invention provides a power grid data asset management method, comprising:

[0038] S1. Obtain power grid data;

[0039] It should be noted that power grid data includes data from various business areas such as user service and relationship data, electricity fee management data, electricity metering information collection data, and market and demand-side data; it also includes equipment ledger management information, which needs to be retrieved from PMS, OMS, ERP, GIS, and marketing business systems. Power grid data is classified by structure into structured power grid data, unstructured power grid data, and semi-structured power grid data. The power grid data acquired in this embodiment can be power grid data from multiple power systems. After acquiring the power grid data, it can be processed according to a preset data mapping table to obtain power grid data in a unified data standard format. Compared to existing power grid data, which is independently developed with different database types and even different entity representations and descriptions, requiring significant manpower to create mapping relationships during integration, this embodiment effectively reduces the time and manpower costs in the power grid data integration process, thereby effectively improving the management efficiency of power grid data.

[0040] In one embodiment, the power grid data also includes power grid equipment information, power grid operation status information data, power equipment operation status data, graphic files and operation logs, voltage levels, basic power user profile data, business work order information, electricity bill record information, channel contact records, electricity consumption collection information, and electricity bill payment time and method; unstructured power grid data includes text data, image data, voice data, and video data.

[0041] S2. Extract and integrate power grid data to obtain entity data corresponding to the power grid data. Entity data includes entities, entity attributes, and entity relationships.

[0042] In this embodiment of the invention, the data resource table for power grid data includes an entity table and a relation table. The entity data of the structured power grid data is obtained through the primary and foreign key information of the table structure.

[0043] S3. Generate data asset catalog structure rules based on the entity data and business categories of power grid data, construct the data asset catalog corresponding to the data asset catalog structure rules, and map the power grid data to the data asset catalog to obtain the mapping relationship.

[0044] In this embodiment of the invention, the relationship between the source and transmission path of power grid equipment security data is determined based on power grid data. Combined with this relationship, the category of entity data and the description paradigm of entity data, data asset catalog structure rules are formulated.

[0045] S4. Construct a data map based on the entity data, mapping relationships, and data asset catalog of the power grid data, and perform asset management on the power grid data based on the data map.

[0046] This invention, through its embodiments, acquires entity data corresponding to power grid data and generates a data asset catalog structure based on the entity data and the business category of the power grid data. By constructing a data asset catalog corresponding to this structure, a mapping relationship is obtained by mapping power grid data to the data asset catalog. This mapping relationship links power grid data with the data asset catalog, enabling convenient retrieval of power grid data through the data asset catalog. Furthermore, data traceability can be performed based on this mapping relationship, which is beneficial for improving the efficiency of power grid data asset management. This invention also visualizes power grid data assets by constructing a data map, improving the convenience of power grid data asset management and further enhancing its efficiency.

[0047] In one embodiment, the power grid data includes unstructured power grid data and structured power grid data. Data extraction and integration of the power grid data yields the corresponding entity data, including:

[0048] The table structure of structured power grid data is analyzed, and the entity data of the structured power grid data is obtained through the primary and foreign key information of the table structure.

[0049] In this embodiment of the invention, a rule-based relation extraction method analyzes the table structure of the data resource table of structured power grid data, including obtaining the entity data of the structured power grid data from information such as the primary and foreign keys of the table structure.

[0050] Extract entities and entity attributes from unstructured power grid data, and perform data analysis on the unstructured power grid data to obtain entity relationships.

[0051] In this embodiment of the invention, entities and their corresponding attributes of unstructured power grid data can be extracted by sequence labeling. Then, the entities and entity attributes of the unstructured power grid data are input into a pre-trained deep learning model, and the entity relationships of the unstructured power grid data are obtained by data analysis of the unstructured power grid data through the deep learning model.

[0052] In one embodiment, the power grid data includes unstructured power grid data and structured power grid data. After obtaining the entity data corresponding to the power grid data, it further includes:

[0053] The entities corresponding to unstructured power grid data are integrated so that the structure of the entities in the unstructured power grid data is the same as that in the structured power grid data.

[0054] In this embodiment of the invention, it should be noted that structured power grid data is data represented and stored using a relational database, and is presented in a two-dimensional form; unstructured power grid data is data without a fixed structure. This embodiment of the invention integrates the entities of unstructured power grid data, making the structure of the entities of unstructured power grid data identical to that of structured power grid data entities. This facilitates the accuracy of subsequent generation of data asset catalog structure rules based on entity data, thereby improving the efficiency of power grid data asset management.

[0055] In one embodiment, a data map is constructed based on entity data, mapping relationships, and asset catalogs of power grid data, including:

[0056] If the data assets of the power grid data change, the data asset catalog is updated according to the changes in the data assets of the power grid data, and a data map is constructed based on the updated data asset catalog, entity data, and mapping relationships.

[0057] In one embodiment, after asset management of the power grid data, the management method further includes:

[0058] A cost input comparison analysis is conducted on the equipment costs, equipment failure data, and maintenance records of each link in the power system, and the results of the comparison analysis are used to determine whether each piece of equipment should be scrapped or removed or retained.

[0059] It should be noted that a power system contains multiple devices, each with a different lifespan. The usage of a device affects its lifespan, including depreciation, failures, maintenance, and downtime. Since each type of device incurs corresponding costs, reliable lifecycle management of power grid data assets requires analysis of the costs at each stage. This invention compares and analyzes the cost distribution data for various equipment types, including costs at each stage, costs over different operating years, failure costs, and maintenance costs. Devices meeting the dismantling / scrapping threshold are marked and dismantled / scrapped. Devices not meeting the dismantling / scrapping criteria will enter the next round of evaluation after a predetermined time, such as one month, six months, or one year.

[0060] Based on the comparison results, the cost investment distribution is obtained. Based on the cost investment distribution of each piece of equipment throughout its entire life cycle, a prediction is made as to whether each piece of equipment meets the conditions for dismantling and scrapping.

[0061] In this embodiment of the invention, further comparative analysis and visualization are conducted based on cost inputs from dimensions such as equipment type, years of operation, failures and maintenance, cost distribution throughout the entire lifecycle of various types of equipment, operating cost inputs for individual equipment, and operating and dismantling / scrapping cost inputs under different cost distributions. Furthermore, predictions are made for equipment reaching dismantling / scrapping conditions at preset time intervals, yielding corresponding prediction results, thereby providing support for power grid data asset management decisions. The preset time interval can be set according to actual work needs, and can be one week, one month, two months, etc.

[0062] In one embodiment, the business categories include: operation and maintenance business, user business, billing business, electricity information collection business, and marketing business.

[0063] In this embodiment of the invention, there are multiple business categories of power grid data. By classifying power grid data according to business categories and generating data asset catalog structure rules from the classified power grid data and entity data, the characteristics of power grid data of different business categories are fully considered in generating data asset catalog structure rules, which helps to improve the accuracy and reliability of the generated data asset catalog structure rules.

[0064] Implementing the embodiments of the present invention has the following beneficial effects:

[0065] This invention, through its embodiments, acquires entity data corresponding to power grid data and generates a data asset catalog structure based on the entity data and the business category of the power grid data. By constructing a data asset catalog corresponding to this structure, a mapping relationship is obtained by mapping power grid data to the data asset catalog. This mapping relationship links power grid data with the data asset catalog, enabling convenient retrieval of power grid data through the data asset catalog. Furthermore, data traceability can be performed based on this mapping relationship, which is beneficial for improving the efficiency of power grid data asset management. This invention also visualizes power grid data assets by constructing a data map, improving the convenience of power grid data asset management and further enhancing its efficiency.

[0066] Furthermore, this embodiment of the invention also analyzes the cost distribution of various equipment throughout the entire life cycle of the power system to predict whether each piece of equipment will meet the conditions for dismantling and scrapping. This can effectively improve the safe operation of equipment while effectively reducing the investment costs of various aspects of equipment in the power system.

[0067] Based on the same technical concept as the above embodiments, one embodiment of the present invention provides... Figure 2 The power grid data asset management system shown includes:

[0068] The power grid data acquisition module 10 is used to acquire power grid data;

[0069] The power grid data integration module 20 is used to extract and integrate power grid data to obtain entity data corresponding to the power grid data. The entity data includes entities, entity attributes, and entity relationships.

[0070] The mapping relationship generation module 30 is used to generate data asset catalog structure rules based on the entity data and business categories of power grid data, construct the data asset catalog corresponding to the data asset catalog structure rules, and map the power grid data to the data asset catalog to obtain the mapping relationship.

[0071] The data asset management module 40 is used to construct a data map based on the entity data, mapping relationship, and asset catalog of the power grid data, and to manage the power grid data assets based on the data map.

[0072] In one embodiment, the power grid data includes unstructured power grid data and structured power grid data. The power grid data integration module 20 is used for:

[0073] The table structure of structured power grid data is analyzed, and the entity data of the structured power grid data is obtained through the primary and foreign key information of the table structure.

[0074] Extract entities and entity attributes from unstructured power grid data, and perform data analysis on the unstructured power grid data to obtain entity relationships.

[0075] In one embodiment, after obtaining the entity data corresponding to the power grid data, the method further includes:

[0076] The entities corresponding to unstructured power grid data are integrated so that the structure of the entities in the unstructured power grid data is the same as that in the structured power grid data.

[0077] In one embodiment, the power grid data integration module 20 is further configured to:

[0078] The entities and entity attributes of unstructured power grid data are input into a pre-trained deep learning model. The deep learning model then performs data analysis on the unstructured power grid data to obtain the entity relationships within the unstructured power grid data.

[0079] In one embodiment, the data asset management module 40 is used for:

[0080] If the data assets of the power grid data change, the data asset catalog is updated according to the changes in the data assets of the power grid data, and a data map is constructed based on the updated data asset catalog, entity data, and mapping relationships.

[0081] In one embodiment, the management system further includes an equipment obsolescence prediction module, used for:

[0082] A cost input comparison analysis is conducted on the equipment costs, equipment failure data, and maintenance records of each link in the power system, and the results of the comparison analysis are used to determine whether each piece of equipment should be scrapped or removed or retained.

[0083] Based on the comparison results, the cost investment distribution is obtained. Based on the cost investment distribution of each piece of equipment throughout its entire life cycle, a prediction is made as to whether each piece of equipment meets the conditions for dismantling and scrapping.

[0084] In one embodiment, the business categories include: operation and maintenance business, user business, billing business, electricity information collection business, and marketing business.

[0085] One embodiment of the present invention provides a computer device including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the power grid data asset management method described above.

[0086] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor A01, a network interface A02, a memory (not shown), and a database (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02, and a database (not shown). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A04. The database stores data such as advertising images and their parameters. The network interface A02 communicates with external terminals via a network connection. When the computer program B02 is executed by the processor A01, it implements a power grid data asset management method.

[0087] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0088] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: acquiring power grid data; extracting and integrating the power grid data to obtain entity data corresponding to the power grid data, wherein the entity data includes entities, entity attributes, and entity relationships; generating data asset catalog structure rules based on the entity data and business categories of the power grid data, and constructing a data asset catalog corresponding to the data asset catalog structure rules, mapping the power grid data to the data asset catalog to obtain a mapping relationship; constructing a data map based on the entity data, mapping relationship, and asset catalog of the power grid data, and performing asset management on the power grid data based on the data map.

[0089] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described power grid data asset management method.

[0090] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0091] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0092] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0093] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0094] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0095] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0096] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0097] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0098] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

[0099] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for managing power grid data assets, characterized in that, include: Acquire power grid data; Data extraction and integration are performed on the power grid data to obtain entity data corresponding to the power grid data. The entity data includes entities, entity attributes, and entity relationships. Data asset catalog structure rules are generated based on the entity data and business categories of the power grid data, and a data asset catalog corresponding to the data asset catalog structure rules is constructed. The power grid data is then mapped to the data asset catalog to obtain a mapping relationship. A data map is constructed based on the entity data of the power grid data, the mapping relationship, and the data asset catalog; and asset management of the power grid data is performed based on the data map. The power grid data includes unstructured power grid data and structured power grid data. The process of extracting and integrating the power grid data to obtain the corresponding entity data includes: The table structure of the structured power grid data is analyzed, and the entity data of the structured power grid data is obtained through the primary and foreign key information of the table structure. Extract the entities and entity attributes from the unstructured power grid data, and perform data analysis on the unstructured power grid data to obtain the entity relationships of the unstructured power grid data; After obtaining the entity data corresponding to the power grid data, the process also includes: The entities corresponding to the unstructured power grid data are integrated so that the structure of the entities in the unstructured power grid data is the same as the structure of the entities in the structured power grid data. A data map is constructed based on the entity data of the power grid data, the mapping relationship, and the data asset catalog, including: If the data assets of the power grid data change, the data asset catalog is updated according to the data asset change information of the power grid data, and a data map is constructed based on the updated data asset catalog, the entity data, and the mapping relationship.

2. The power grid data asset management method as described in claim 1, characterized in that, The process of analyzing the unstructured power grid data to obtain the entity relationships of the unstructured power grid data includes: The entities and entity attributes of the unstructured power grid data are input into a pre-trained deep learning model, and the entity relationships of the unstructured power grid data are obtained through data analysis performed by the deep learning model.

3. The power grid data asset management method as described in claim 1, characterized in that, After performing asset management on the power grid data, the following is also included: A cost input comparison analysis is conducted on the equipment costs, equipment failure data, and maintenance records of each link in the power system, and the results of the comparison analysis are used to determine whether each piece of equipment should be scrapped or removed or retained. Based on the comparison results, the cost investment distribution is obtained. Based on the cost investment distribution of each piece of equipment throughout its entire life cycle, it is predicted whether each piece of equipment meets the conditions for dismantling and scrapping.

4. The power grid data asset management method as described in claim 1, characterized in that, The business categories include: operation and maintenance services, user services, billing services, electricity information collection services, and marketing services.

5. A power grid data asset management system, characterized in that, include: The power grid data acquisition module is used to acquire power grid data. The power grid data integration module is used to extract and integrate the power grid data to obtain the entity data corresponding to the power grid data. The entity data includes entities, entity attributes, and entity relationships. The mapping relationship generation module is used to generate data asset catalog structure rules based on the entity data and business category of the power grid data, construct the data asset catalog corresponding to the data asset catalog structure rules, and map the power grid data to the data asset catalog to obtain the mapping relationship. The data asset management module is used to construct a data map based on the entity data of the power grid data, the mapping relationship, and the data asset catalog, and to perform asset management on the power grid data based on the data map. The power grid data includes unstructured power grid data and structured power grid data. The process of extracting and integrating the power grid data to obtain the corresponding entity data includes: The table structure of the structured power grid data is analyzed, and the entity data of the structured power grid data is obtained through the primary and foreign key information of the table structure. Extract the entities and entity attributes from the unstructured power grid data, and perform data analysis on the unstructured power grid data to obtain the entity relationships of the unstructured power grid data; After obtaining the entity data corresponding to the power grid data, the process also includes: The entities corresponding to the unstructured power grid data are integrated so that the structure of the entities in the unstructured power grid data is the same as the structure of the entities in the structured power grid data. The data asset management module is used to construct a data map based on the entity data of the power grid data, the mapping relationship, and the data asset catalog, including: If the data assets of the power grid data change, the data asset catalog is updated according to the data asset change information of the power grid data, and a data map is constructed based on the updated data asset catalog, the entity data, and the mapping relationship.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the power grid data asset management method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the power grid data asset management method according to any one of claims 1 to 4.

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