Data integration method, device and equipment and readable storage medium

Abstract

The invention discloses a data integration method, device and equipment and a readable storage medium, the method can obtain a rule table used for recording different power grid element equipment dump rules, each power grid element equipment dump rule corresponds to more than one model card dump rule, and each model card dump rule corresponds to a plurality of structure dump modes; obtaining a target power grid component model containing multiple pieces of parameter item information; converting the target power grid component model into a plurality of target structural bodies in combination with each piece of parameter item information in the target power grid component model and the rule table; and according to the rule table, splicing and combining the target structure bodies to form a model set corresponding to the target power grid component model. Therefore, according to the method, the power grid data of different sources and different formats are integrated into a unified and normative data structure, valuable information can be extracted from the power grid data, and powerful support is provided for stable operation and scientific decision making of a power system.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and more specifically, to a data integration method, apparatus, device, and readable storage medium. Background Art

[0002] With the continuous acceleration of the digital transformation process of the power grid, the power grid system generates a large amount of complex data during its daily operation. However, in the power grid system, different business systems adopt their own business standards in the process of data collection, storage, and processing, making it difficult for data to be interoperable; each department manages data independently for its own business needs, resulting in scattered and difficult-to-integrate data; and there are differences in data interfaces and communication protocols between different systems, hindering the effective transmission and sharing of data. Therefore, power grid data has the remarkable characteristics of diversity and heterogeneity. Diversity is reflected in the wide range of data sources, covering various data sources such as power grid monitoring devices, user metering terminals, and smart meters; heterogeneity is manifested as differences in data formats, storage methods, and semantic meanings. For example, the data formats collected by monitoring devices produced by different manufacturers are different.

[0003] This situation has led to a serious data island phenomenon. The data island problem has brought many adverse effects. For example, from the data level, it hinders the free flow of data, making the data of each business system unable to be fully utilized within the entire power grid system; from the business level, it affects the efficiency of power grid operation and the scientific nature of decision-making. For example, in the process of power grid fault repair decision-making, due to the inability to timely share and integrate the data of different departments, it may lead to delayed and inaccurate decisions. Summary of the Invention

[0004] In view of this, the present application provides a data integration method, apparatus, device, and readable storage medium for solving the problem of excessive heterogeneity of power grid data in the prior art.

[0005] To achieve the above object, the following solutions are proposed:

[0006] A data integration method includes:

[0007] Obtain a rule table for recording dump rules of different power grid component devices, where each power grid component device dump rule corresponds to one or more model card dump rules, and each model card dump rule corresponds to multiple structure dump methods;

[0008] Obtain a target power grid component model containing multiple parameter item information;

[0009] Combine each parameter item information in the target power grid component model and the rule table, process each parameter item information, and convert the target power grid component model into multiple target structures;

[0010] According to the said rule table, each target structure body is spliced and combined to form a model set corresponding to the target power grid component model.

[0011] Optionally, combining each parameter item information in the target power grid component model and the rule table, and processing each parameter item information to convert the target power grid component model into multiple target structure bodies, including:

[0012] Determine the target device type of the target power grid component model;

[0013] Based on the rule table, determine all target model card dump rules corresponding to the target device type;

[0014] Based on each target model card dump rule, adjust and reorganize each parameter item information to form multiple target structure bodies.

[0015] Optionally, the adjusting and reorganizing each parameter item information based on each target model card dump rule to form multiple target structure bodies includes:

[0016] Based on the model type of each target model card dump rule, determine the corresponding target structure body dump method;

[0017] According to each target structure body dump method, construct the corresponding structure item;

[0018] Write the parameter type and field data in each parameter item information into the corresponding structure item to form a target structure body.

[0019] Optionally, it further includes:

[0020] Write the model set into the database, and use a generation tool to connect to the database to generate an operation interface corresponding to the model set.

[0021] Optionally, the structure body dump method of the rule table is used to indicate the mapping conversion rules between different power grid parameter types and service requirement types.

[0022] Optionally, the rule table also records the splicing rules between each model card dump rule.

[0023] Optionally, the rule table also records the dependency relationships between different model card dump rules.

[0024] A data integration device, including:

[0025] A rule table acquisition module, configured to acquire a rule table for recording different power grid component device dump rules, wherein each power grid component device dump rule corresponds to one or more model card dump rules, and each model card dump rule corresponds to multiple structure body dump methods;

[0026] A model acquisition module, configured to acquire a target power grid component model including information of a plurality of parameter items;

[0027] An information processing module, configured to process each parameter item information in combination with the rule table in the target power grid component model, and convert the target power grid component model into a plurality of target structures;

[0028] A structure combination module, configured to splice and combine each target structure according to the rule table to form a model set corresponding to the target power grid component model.

[0029] A data integration device, comprising a memory and a processor;

[0030] The memory is configured to store a program;

[0031] The processor is configured to execute the program to implement each step of the above data integration method.

[0032] A readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each step of the above data integration method is implemented.

[0033] As can be seen from the above technical solutions, the data integration method provided in this application takes into account the wide variety of grid component devices, covering many component devices such as transformers, circuit breakers, and wires. The data dump requirements for different types of component devices may vary. Therefore, this method can obtain a rule table for recording the dump rules of different grid component devices. Among them, each grid component device corresponds to more than one model card dump rule, and each model card dump rule corresponds to multiple structure body dump methods. Based on this, the rule table of this application has a clear hierarchical structure. Through the rule table, this application provides a unified and standardized basis for subsequent data processing. The rule table can guide the dump process of different grid component devices, help ensure the consistency and accuracy of data during the dump process, avoid data chaos and errors caused by the lack of standards, and facilitate the unified management and processing of data for different grid component devices in the future. During use, a target grid component model containing multiple parameter item information can be obtained. Based on this, the target grid component model can reflect various operating states and attribute information of the grid component. Subsequently, each parameter item information in the target grid component model can be combined with the rule table to process each parameter item information, and the target grid component model can be converted into multiple target structure bodies. According to the rule table, each target structure body is spliced and combined to form a model set corresponding to the target grid component model. Based on this, this application can use the rule table to reorganize and sort each parameter item information into multiple target structure bodies, and then splice the multiple target structure bodies to form a model set. The original data with diverse formats and chaotic structures is converted into a model set according to a unified standard. Since the model set formed by splicing the target structure bodies has a clear structure and specification, compared with the original messy data, the computer system can perform operations such as storage, retrieval, and calculation more efficiently when processing these structured data, thereby improving the efficiency of subsequent data processing processes. It can be seen that this application can integrate grid data from different sources and in different formats into a unified and standardized data structure, which is convenient for subsequent storage, transmission, and analysis, helps extract valuable information from grid data, such as predicting grid faults and optimizing grid operation strategies, and provides strong support for the stable operation and scientific decision-making of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] 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 described below are only the embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on the provided drawings without creative efforts.

[0035] Figure 1 It is a flowchart of a data integration method disclosed in an embodiment of the present application;

[0036] Figure 2 Block diagram of a data integration device disclosed in an embodiment of the present application;

[0037] Figure 3 Hardware block diagram of a data integration device disclosed in an embodiment of the present application. Detailed implementation manners

[0038] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0039] The embodiment of the present application provides a data integration method. This data integration method can be applied to various power grid systems or data processing systems, and can also be applied to various computer terminals or intelligent terminals. Its execution subject can be the processor or server of a computer terminal or an intelligent terminal.

[0040] Next, in conjunction with Figure 1 The data integration method of the present application will be introduced in detail, including the following steps:

[0041] Step S1: Obtain a rule table for recording the dump rules of different power grid component devices.

[0042] Specifically, each power grid component device dump rule can correspond to more than one model card dump rule, and each model card dump rule can correspond to multiple structure dump methods.

[0043] Each structure dump method can be used to indicate the parameter name for recording the corresponding parameter item, the corresponding parameter data type, the data format, and the position in the file corresponding to the target power grid component model.

[0044] Each model card dump rule can be used to indicate the name of the corresponding model card category, all the sub-categories of the model cards corresponding to this category, and the model card ID splicing rule corresponding to this category.

[0045] The structure dump method of the rule table can also be used to indicate the mapping conversion rule between different power grid parameter types and service requirement types.

[0046] For example, the structure dump method can include service requirement types such as CardType, ParaName, DataType, SWIType, SWILocation, and isName.

[0047] Among them, the CardType field can be used to indicate the type of the corresponding structure, the ParaName field can be used to represent the name of the parameter item, the DataType field can be used to represent the storage type when the parameter is mapped into the slice, the SWIType field can be used to represent the type of the corresponding parameter, the SWILocation field can be used to represent the location positioning of the corresponding parameter in the relevant file of the target power grid component model, and the isName field can be used to represent which parameters the name of the target structure after mapping consists of.

[0048] The rule table may also record the splicing rules between various model card dump rules.

[0049] Different power grid component devices can correspond to different model card ID splicing rules.

[0050] After the aggregates formed by different model card dump rules are spliced, component devices with different functions are combined.

[0051] Therefore, the splicing rules can be custom-written into the rule table to achieve more flexible data integration.

[0052] The part corresponding to the model card dump rules in the rule table is presented in the form of a sub-table. The table headers of this sub-table can be, from left to right, the functional type of the power equipment, the English category, the set of model card categories to which it belongs, and the splicing rules between various model card dump rules. Due to different splicing specifications for different equipment types, and the data structures of different model card parameters are also different, and their storage forms are also different.

[0053] The rule table may also record the dependency relationships between different model card dump rules. For example, as shown in Table 1, for the aggregate formed by combining the model card dump rules corresponding to each model card identifier, a splicing operation needs to be performed.

[0054]

[0055] The rule table can record the summary information of each model card corresponding to different service requirement types.

[0056] Step S2, obtain the target power grid component model containing multiple parameter item information.

[0057] Specifically, the target power grid component model can be the data of power grid component devices that need data integration, such as wire data, generator data, transformer data, or motor data, etc.

[0058] The target power grid component model containing multiple parameter item information can be obtained through an automated program conversion.

[0059] What can be stored in the target power grid component model is model card data, and each row of data contains several nodes, and each node contains specific floating-point parameters corresponding to the detailed data of each field of the model card.

[0060] There can be 83 types of model cards.

[0061] Taking the model card type belonging to the motor as an example, each model card contains floating-point parameters, and the position information of the model card parameters is known. Taking the first row of model card data as an example, its model card type is "MS", the parameter name of the 4th - 11th bytes is "BusName", and the data is "Gui Yuchai G1"; the parameter name of the 12th - 15th bytes is "BaseVoltage", and the value is 0.4; the parameter name of the 16th byte is "Code", and the value is null; the parameter name of the 23rd - 25th bytes is "Pper", and the value is null; the parameter name of the 26th - 28th bytes is "Qper", and the value is null; the parameter name of the 29th - 32nd bytes is "MVA", and the value is 1.05; the parameter name of the 33rd - 37th bytes is "T", and the value is 15; the parameter name of the 38th - 42nd bytes is "Uoc", and the value is 44.8; the parameter name of the 43rd - 47th bytes is "Isc", and the value is 8.33; the parameter name of the 48th - 52nd bytes is "Um", and the value is 35.2; the parameter name of the 53rd - 57th bytes is "Im", and the value is 7.95; the parameter name of the 58th - 61st bytes is "Nshunt", and the value is 127; the parameter name of the 62nd - 65th bytes is "Nser", and the value is 28; the parameter name of the 66th - 71st bytes is "Cf", and the value is 200; the parameter name of the 78th - 80th bytes is "NM", and the value is 195.

[0062] Step S3: Combine each parameter item information in the target power grid component model and the rule table, process each parameter item information, and convert the target power grid component model into multiple target structures.

[0063] Specifically, the target power grid component model can be matched with each model card dump rule, and according to the matched model card dump rule, each parameter item information is integrated into multiple target structures.

[0064] Among them, each target structure contains multiple parameter item information, and all parameter item information of the target power grid component model is integrated into each target structure.

[0065] Each parameter item information in the target power grid component model and the rule table can be combined in various ways to process each parameter item information and convert the target power grid component model into multiple target structures.

[0066] For example, the parameter categories of each line of the model card can be extracted from the target power grid component model and compared with the existing category records to determine whether the model card parameter category matches the corresponding category in each model card dump rule in the rule table;

[0067] If not, no processing is performed.

[0068] If the match is successful, read the model card dump rule corresponding to the model card in the rule table. Store the parameter information in the map according to the mapping relationship. Taking the model card MF as an example, this model card has 18 parameters, which respectively correspond to positions of different lengths within 80 bytes of the row data in the target power grid component model. For example, the bus name is recorded in bytes 4 - 11, and the corresponding information is "Guiguangpo G4", and the voltage reference value is recorded in bytes 12 - 15, and the corresponding data is "24". The parameter data of this model card can be mapped to the database table.

[0069] Another example is that the model card dump rule matching can be performed according to the device type of the target power grid component model, and the generation of the target structure can be carried out.

[0070] A corresponding map can be established to temporarily store each target structure. Its key is the special case name, and the key value is an array of string types of all model card types corresponding to this case. When its category is retrieved, it will enter the process corresponding to its category. For example, in the process of the model card with uncertain type, the field splicing step will be ignored.

[0071] The parameter information of each line will be temporarily stored in the program memory in the type of map[string]interface{}. Among them, string is the parameter name of the model card data of this line, and interface{} is the specific data corresponding to this parameter.

[0072] Step S4, according to the rule table, splice and combine each target structure to form a model set corresponding to the target power grid component model.

[0073] Specifically, since the data related to the target power grid component model can be converted into multiple target structures, and there can be a certain dependency relationship between each target structure, the splicing rules formed based on the dependency relationship between each target structure can be recorded in the rule table.

[0074] Therefore, according to the rule table, each target structure can be spliced and combined, and after splicing and combining, a model set corresponding to the target power grid component model is obtained.

[0075] The model set can be stored in the corresponding database,

[0076] Or the model set can be analyzed and processed for power flow planning.

[0077] As can be seen from the above technical solution, the data integration method provided by this application takes into account the wide variety of power grid component devices, covering many component devices such as transformers, circuit breakers, wires, etc. The data dump requirements for different types of component devices may vary. Therefore, this method can obtain a rule table for recording the dump rules of different power grid component devices. Among them, each power grid component device corresponds to more than one model card dump rule, and each model card dump rule corresponds to multiple structure body dump methods. Based on this, the rule table of this application has a clear hierarchical structure. Through the rule table, this application provides a unified and standardized basis for subsequent data processing. The rule table can guide the dump process of different power grid component devices, helping to ensure the consistency and accuracy of data during the dump process, avoiding data chaos and errors caused by the lack of standards, and facilitating the unified management and processing of data of different power grid component devices in the future. During use, a target power grid component model containing multiple parameter item information can be obtained. Based on this, the target power grid component model can reflect various operating states and attribute information of the power grid component. Subsequently, each parameter item information in the target power grid component model can be combined with the rule table to process each parameter item information, and the target power grid component model can be converted into multiple target structure bodies. According to the rule table, each target structure body is spliced and combined to form a model set corresponding to the target power grid component model. Based on this, this application can use the rule table to reorganize and sort each parameter item information into multiple target structure bodies, and then splice the multiple target structure bodies to form a model set. The original data with diverse formats and chaotic structures is converted into a model set according to a unified standard. Since the model set spliced by the target structure bodies has a clear structure and specification, compared with the original messy data, the computer system can perform operations such as storage, retrieval, and calculation more efficiently when processing these structured data, thereby improving the efficiency of subsequent data processing processes. It can be seen that this application can integrate power grid data from different sources and in different formats into a unified and standardized data structure, facilitating subsequent storage, transmission, and analysis, helping to extract valuable information from the power grid data, such as predicting power grid faults and optimizing power grid operation strategies, and providing strong support for the stable operation and scientific decision-making of the power system.

[0078] In some embodiments of this application, the process of step S3, combining each parameter item information in the target power grid component model with the rule table to process each parameter item information and converting the target power grid component model into multiple target structure bodies, is described in detail as follows:

[0079] S30. Determine the target device type of the target power grid component model.

[0080] Specifically, each power grid component model has a corresponding device type. Therefore, the device type of the target power grid component model can be determined as the target device type.

[0081] S31. Based on the rule table, determine all target model card dump rules corresponding to the target device type.

[0082] Specifically, according to the rule table, all model card dump rules matching the target device type can be found as each target model card dump rule.

[0083] S32. Based on each target model card dump rule, adjust and reorganize each parameter item information to form multiple target structures.

[0084] Specifically, based on each target model card dump rule, each parameter item information can be disassembled and reorganized, and multiple target structures are obtained after reorganization.

[0085] It can be seen from the above technical solution that this embodiment provides an optional method for processing each parameter item information in combination with the target power grid component model and the rule table, converting the target power grid component model into multiple target structures. Through the above method, the adjustment and reorganization of parameter item information can be better carried out, and the reliability of this application can be improved.

[0086] In some embodiments of this application, the process of step S32, based on each target model card dump rule, adjusting and reorganizing each parameter item information to form multiple target structures, is described in detail as follows:

[0087] S320. Based on the model type of each target model card dump rule, determine the corresponding target structure dump method.

[0088] Specifically, based on the model type of each target model card dump rule, a matching structure dump method can be found as the target structure dump method.

[0089] S321. According to each target structure dump method, construct the corresponding structure item.

[0090] Specifically, according to each target structure dump method, a structure item composed of multiple structure parameter identifiers can be constructed.

[0091] For example, DataElement structure items and DataTable structure items can be constructed to efficiently process and integrate the information of each parameter item. The DataElement structure item is used to represent the detailed information of a single parameter item, including its original name Name, alias name AliasName, Chinese name SubName, data type Type, format SWIType, location Location, and whether it is part of the device name IsName. These fields together describe the attributes of the parameter item information and its positioning in the target power grid component model, providing precise guidance for data parsing and mapping. The DataTable structure item is used to represent the structure of the entire corresponding model card, including the original name Name, alias name AliasName, Chinese name SubName of the model card, and a slice Struct of the DataElement structure, which stores all the parameter items belonging to the model card. Such a design enables the DataTable to act as a container to organize and manage all the parameter data elements belonging to the same model card, facilitating the creation of tables and organization of data in the database. These two data structures are used to store the parameter information of all model cards without including the specific parameter data.

[0092] S322. Write the parameter type and field data in each parameter item information into the corresponding structure item to form a target structure.

[0093] Specifically, based on each parameter item information, parameter values corresponding to each structure parameter identifier in each structure item can be generated to form a target structure.

[0094] It can be seen from the above technical solution that this embodiment provides an optional way to adjust and reorganize each parameter item information based on the dump rules of each target model card to form multiple target structures. Through the above method, the construction of the target structure can be completed by writing each parameter item information into the structure item.

[0095] In some embodiments of the present application, considering that parameter information stored in the model set may be needed when performing load forecasting or power grid layout optimization, the integrated model set can be stored in the database for subsequent reuse. Next, the storage process will be described in detail as follows:

[0096] S5. Write the model set into the database, and use a generation tool to connect to the database to generate an operation interface corresponding to the model set.

[0097] Specifically, the model set can be stored in a MySQL database. The GEN generation tool is used to connect to the MySQL database, and operation interfaces such as addition, deletion, modification, and query are added to each database so that the required field data can be retrieved from the database through the query interface.

[0098] As can be seen from the above technical solution, compared with the previous embodiment, this embodiment newly adds a process for storing the model set. Through the above process, when it is necessary to query or update the model set subsequently, the operation interface can be directly used for query or update, better maintaining the model set and integrating the latest information into the model set. Thus, not only can the work efficiency be significantly improved, but also the integrity, accuracy, and timeliness of the model set can be better maintained fundamentally, ensuring that the model set always meets the requirements of the power grid business.

[0099] Next, Figure 2 the data integration device provided in this application will be introduced in detail. The data integration device provided below can be compared with the data integration method provided above.

[0100] See Figure 2 It can be found that the data integration device may include:

[0101] A rule table acquisition module 10, configured to acquire a rule table for recording dump rules of different power grid component devices, where each power grid component device dump rule corresponds to one or more model card dump rules, and each model card dump rule corresponds to multiple structure dump methods;

[0102] A model acquisition module 20, configured to acquire a target power grid component model including multiple parameter item information;

[0103] An information processing module 30, configured to process each parameter item information in combination with the rule table and the target power grid component model, and convert the target power grid component model into multiple target structures;

[0104] A structure combination module 40, configured to splice and combine each target structure according to the rule table to form a model set corresponding to the target power grid component model.

[0105] Further, the information processing module 30 may include:

[0106] A target device type determination unit, configured to determine the target device type of the target power grid component model;

[0107] A target model card dump rule determination unit, configured to determine all target model card dump rules corresponding to the target device type based on the rule table;

[0108] A target structure generation unit, configured to adjust and reorganize each parameter item information based on each target model card dumping rule to form a plurality of target structures.

[0109] Further, the target structure generation unit may include:

[0110] A target structure dumping method determination subunit, configured to determine a corresponding target structure dumping method based on the model type of each target model card dumping rule;

[0111] A structure item construction subunit, configured to construct corresponding structure items according to each target structure dumping method;

[0112] A field data writing subunit, configured to write the parameter type and field data in each parameter item information into the corresponding structure item to form a target structure.

[0113] Further, the data integration device may further include:

[0114] An operation interface generation unit, configured to write the model set into a database, and connect to the database using a generation tool to generate an operation interface corresponding to the model set.

[0115] The data integration device provided in the embodiments of the present application can be applied to data integration devices, such as PC terminals, cloud platforms, servers, and server clusters, etc. Optionally, Figure 3 shows a hardware structure block diagram of a data integration device. Referring to Figure 3 , the hardware structure of the data integration device may include: at least one processor 1, at least one communication interface 2, at least one memory 3, and at least one communication bus 4;

[0116] In the embodiments of the present application, the number of the processor 1, the communication interface 2, the memory 3, and the communication bus 4 is at least one, and the processor 1, the communication interface 2, and the memory 3 complete mutual communication through the communication bus 4;

[0117] The processor 1 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention, etc.;

[0118] The memory 3 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory;

[0119] Among them, the memory stores a program, and the processor can call the program stored in the memory. The program is used for:

[0120] Obtain a rule table for recording dump rules of different power grid component devices, where each power grid component device dump rule corresponds to more than one model card dump rule, and each model card dump rule corresponds to multiple structure dump methods;

[0121] Obtain a target power grid component model containing multiple parameter item information;

[0122] Combine each parameter item information in the target power grid component model and the rule table, process each parameter item information, and convert the target power grid component model into multiple target structures;

[0123] According to the rule table, splice and combine each target structure to form a model set corresponding to the target power grid component model.

[0124] Optionally, the refinement function and expansion function of the program can be referred to the above description.

[0125] An embodiment of the present application also provides a readable storage medium, which can store a program suitable for execution by a processor, and the program is used for:

[0126] Obtain a rule table for recording dump rules of different power grid component devices, where each power grid component device dump rule corresponds to more than one model card dump rule, and each model card dump rule corresponds to multiple structure dump methods;

[0127] Obtain a target power grid component model containing multiple parameter item information;

[0128] Combine each parameter item information in the target power grid component model and the rule table, process each parameter item information, and convert the target power grid component model into multiple target structures;

[0129] According to the rule table, splice and combine each target structure to form a model set corresponding to the target power grid component model.

[0130] Optionally, the refinement function and expansion function of the program can be referred to the above description.

[0131] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article or device comprising said element.

[0132] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the various embodiments, reference may be made to each other.

[0133] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. The various embodiments of the present application can be combined with each other. Therefore, the present application will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A data integration method, characterized in that: include: Obtaining a rule table for recording dump rules of different power grid component devices, wherein each power grid component device dump rule corresponds to more than one model card dump rule, and each model card dump rule corresponds to multiple structure dump modes; Acquire a target power grid component model including information of multiple parameter items; Combining each parameter item information in the target power grid component model and the rule table, processing each parameter item information, and converting the target power grid component model into a plurality of target structures; According to the rule table, each target structure is spliced ​​and combined to form a model set corresponding to the target power grid component model.

2. The data integration method according to claim 1, characterized in that: The combining each parameter item information in the target power grid component model and the rule table, processing each parameter item information, and converting the target power grid component model into a plurality of target structures, includes: Determining a target device type of the target power grid component model; Based on the rule table, determine all target model card dump rules corresponding to the target device type; Based on the dumping rules of each target model card, the information of each parameter item is adjusted and reorganized to form multiple target structures.

3. The data integration method according to claim 2, characterized in that: Based on the dumping rules of each target model card, each parameter item information is adjusted and reorganized to form multiple target structures, including: Based on the model type of each target model card dump rule, determine the corresponding target structure dump method; According to the dumping method of each target structure, build the corresponding structure item; Write the parameter type and field data in each parameter item information into the corresponding structure item to form the target structure.

4. The data integration method according to claim 1, characterized in that: Also includes: The model set is written into a database, and a generation tool is used to connect the database to generate an operation interface corresponding to the model set.

5. The data integration method according to any one of claims 1 to 4, characterized in that: The structure dumping method of the rule table is used to indicate the mapping conversion rules between different power grid parameter types and business demand types.

6. The data integration method according to any one of claims 1 to 4, characterized in that: The rule table also records the splicing rules between the dump rules of each model card.

7. The data integration method according to any one of claims 1 to 4, characterized in that: The rule table also records the dependency relationships between different model card dump rules.

8. A data integration device, characterized in that: include: A rule table acquisition module is used to acquire a rule table for recording dump rules of different power grid component devices, wherein each power grid component device dump rule corresponds to more than one model card dump rule, and each model card dump rule corresponds to multiple structure dump modes; A model acquisition module is used to acquire a target power grid component model including information of multiple parameter items; An information processing module, used to combine each parameter item information in the target power grid component model and the rule table, process each parameter item information, and convert the target power grid component model into multiple target structures; The structure combination module is used to combine and splice each target structure according to the rule table to form a model set corresponding to the target power grid component model.

9. A data integration device, characterized in that: including memory and processor; The memory is used to store programs; The processor is used to execute the program to implement each step of the data integration method as described in any one of claims 1-7.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, each step of the data integration method according to any one of claims 1 to 7 is implemented.

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