Storage and query method and device of relational data table based on DSP simulation model and medium

Abstract

The application discloses a data storage and query method based on a DSP simulation model, a computer device and a storage medium. The relational data table organization structure comprises a model mapping table, a model data table and a model logic table. The model mapping table is used for storing the mapping of the simulation model and the relational table and the corresponding relationship between the model parameter item and the relational table field, so as to support the automatic conversion process of the simulation model data and the relational table data. The model data table is used for storing the parameter information of the simulation model and forming a model object index, and comprises a plant station table, an inter-plant line table, a static model table and a dynamic model table. The model logic table is used for abstracting and integrating the topology and the organization relationship between the simulation models, so as to support the query scene based on the model relationship. The storage and query method is based on the data structure which has high readability, simple structure, is easy to maintain and can support complex query scenes.

Description

Technical Field

[0001] This invention belongs to the field of power system simulation data query and storage, and particularly relates to the storage and query method, computer device and storage medium of relational data tables based on DSP simulation models. Background Technology

[0002] Power system simulation is widely used in power grid planning, operation, and control, and is an important tool for power researchers to analyze power systems. As input to power system simulation, the simulation model data describes the attributes and connections of various power components, and is important data for characterizing the operating mode and state of the power system.

[0003] Existing simulation software organizes power system simulation model data in text format, representing a simulation model as an "identifier + parameter list." The identifier indicates the model type, and the parameter list specifies the model's parameters. While this structure is simple and easy to implement, it suffers from poor readability, lacks model organization and management, and cannot support complex query scenarios. Therefore, this text-based organization severely limits the application scenarios and efficiency of simulation model data.

[0004] To improve data query and sharing performance, a common approach is to convert text data into relational data and use mature relational databases for data storage and retrieval. Regarding simulation model data, most existing solutions convert text data into corresponding relational tables, generating a large number of tables in a one-to-one correspondence manner. While this method can convert text-based simulation model data into relational tables, it lacks proper table supplementation, management and indexing of model objects and relationships, and only supports single-parameter queries. It struggles with querying multi-model equipment or plant-level data. Summary of the Invention

[0005] To address the problems existing in the data structure of current DSP simulation models, this invention provides a data storage and query method based on relational data tables of DSP simulation models.

[0006] On the one hand, the present invention provides a data storage method based on a relational data table of a DSP simulation model, the method being:

[0007] Create a model mapping table;

[0008] Obtain the model data mapping relationship and store it in the model mapping table;

[0009] Based on the mapping relationship in the model mapping table, create a model data table and set a model mapping identifier code as the index of the model data table;

[0010] Create a model logic table;

[0011] After traversing the simulation model and assigning a model mapping identifier code to the simulation model, the model parameters are stored in the corresponding model data table according to the parameter correspondence in the model mapping table.

[0012] Traverse the topological and organizational relationships between simulation models, and store the relationship type, the objects involved in the relationship, and the relationship attributes into the model logical table according to the fields of the model logical table.

[0013] Furthermore, the model data mapping relationship includes:

[0014] Plant data mapping relationship, which includes plant type, plant table name, and the correspondence between plant parameter items and plant table fields;

[0015] Inter-plant line data mapping relationship, which includes inter-plant line type, inter-plant line table name, and the correspondence between inter-plant line parameter items and inter-plant line table fields;

[0016] The static model data mapping relationship includes the model type, model table name, and parameter correspondence for each type of static model. Each type of static model corresponds to a static model data table. By traversing all static model types of the simulation model, the static model parameter items are paired with the fields of the static model data table to form key-value pairs, which are then serialized into JSON to form the parameter correspondence.

[0017] The dynamic model data mapping relationship includes the integration and storage of all dynamic models into a single dynamic model table, and the storage of dynamic model parameter items and dynamic model parameter value key-value pairs into the parameter content field of the dynamic model table via JSON serialization.

[0018] Furthermore, storing the model data mapping relationship in the model mapping table includes: storing the mapping between the simulation model and the relation table, as well as the correspondence rules between model parameter items and relation table fields, in the model mapping table to support the automatic conversion process between simulation model data and relation table data; the model mapping table fields include model type, relation table name, and parameter correspondence; the model type is used to store the model card type of the simulation model; the relation table name is used to store the name of the data table where the model is mapped to the relation table; the parameter correspondence is used to store the result of JSON serialization of the key-value pair correspondence between model card parameter items and relation table fields, which describes the correspondence between model parameter items and table fields.

[0019] Furthermore, storing the model parameters into the corresponding model data table according to the parameter correspondence in the model mapping table includes: storing the parameter information of the simulation model into the model data table and forming a model object index; the model data table includes a plant table, an inter-plant line table, a static model table, and a dynamic model table, wherein the plant table and the inter-plant line table are used to store the management information, parameter information, and connection relationships of the power plants and substations in the simulation model; the static model table is used to store the management information and parameter information of static models such as AC nodes, DC nodes, AC lines, DC lines, transformers, phase shifters, node supplementary models, and branch supplementary models in the simulation model; the dynamic model table is used to store the management information and parameter information of dynamic models such as generators and loads in the simulation model.

[0020] Furthermore, storing the relationship type, the objects involved in the relationship, and the relationship attributes into the model logic table based on the model logic table fields includes: abstracting and integrating the corresponding relationships between simulation models, including topological relationships and organizational relationships, into the model logic table, thereby supporting query scenarios based on model relationships; the model logic table fields include relationship type, relationship object identifier code, and relationship attributes; the relationship type stores the type of relationship between simulation models, including topological relationships and organizational relationships, used to narrow the data retrieval scope when querying based on model relationships; the relationship object identifier code is used to store the identifier code of the simulation model involved in the relationship, serving as a general index of the model logic table; the relationship attributes store the result of JSON serialization of the attribute key-value pairs attached to the simulation model relationship.

[0021] Furthermore, the fields of the plant / station table include plant / station management fields and plant / station parameter fields; the plant / station management fields include plant / station identification codes, which are indexes of the plant / station table and are used to store system information of the plant / station in both time and space; the plant / station parameter fields include plant / station type, voltage level, geographical coordinates x, and geographical coordinates y, which are used to store specific parameters of the plant / station.

[0022] The inter-plant line table includes an inter-plant line management field and an inter-plant line parameter field. The inter-plant line management field includes an inter-plant line identification code, which is an index of the inter-plant line table and is used to store the system information of the inter-plant lines in time and space. The inter-plant line parameter field includes the inter-plant line type, voltage level, and number of line connections, and is used to store the specific parameters of the inter-plant lines.

[0023] The static model table includes a single-type static model data table; the fields of the single-type static model data table include a model management field and a model parameter field; the model management field includes a static model identifier code, which is an index of the single-type static model data table and is used to store the system information of the static model in time and space; the model parameter field corresponds one-to-one with the parameter items of the model parameter card, and the correspondence is consistent with the parameter correspondence in the mapping table.

[0024] The dynamic model table fields include dynamic model management fields and dynamic model parameter fields. The dynamic model management fields include dynamic model identifiers, which serve as indexes for the dynamic model data table and are used to store system information about the dynamic model in both time and space. The dynamic model parameter fields include model type and parameter content. The model type stores the model card type of the dynamic model, and the parameter content stores the result obtained by JSON serialization of the dynamic model parameter item-parameter value key-value pairs.

[0025] On the other hand, the present invention also provides a data query method based on a relational data table of a DSP simulation model, characterized in that the data query method includes equipment-level data query steps and plant-level data query steps; the equipment-level data includes static model data and dynamic model data connected to the static model; the plant-level data includes all static model data and dynamic model data within the plant; the relational data table stores the data through any of the data storage methods mentioned above.

[0026] Furthermore, the device-level data query step is as follows:

[0027] Use the model type of the device as a condition to query the model mapping table and obtain the model data table where the data of the queried device is located.

[0028] Using the device model identifier as a condition, perform a primary key query on the static model table to obtain static model parameter information;

[0029] Query the relationships in the logical table of the query model that are of the dynamic model electrical connection type;

[0030] Filter the relationships that contain the device model identifier code to obtain the identifier codes of all dynamic models connected to the device;

[0031] Using the dynamic model identifier as a condition, perform a primary key query on the dynamic model table to obtain the device-level dynamic model parameters;

[0032] The steps for querying plant-level data are as follows:

[0033] The query model's logical table contains relationships of subordinate plant / station type.

[0034] Filter the relationships that contain the plant data identifier code, and obtain the model data table name and static model identifier code corresponding to all static models in the plant.

[0035] Using the static model identifier as a condition, perform a primary key query on the corresponding static model data table to obtain the plant-level data static model parameters;

[0036] Query the relationships in the logical table of the query model that are of the dynamic model electrical connection type;

[0037] Filter the relationships that contain the static model identifier code, and obtain all dynamic model identifier codes connected to the static model;

[0038] Using the dynamic model identifier as a condition, perform a primary key query on the dynamic model table to obtain the dynamic model parameters of the plant-level data.

[0039] On the other hand, the present invention also provides a computer device, characterized in that it includes a memory and a processor, the memory being used to store at least one program, and the processor being used to load the at least one program to execute the above-described data storage of a relational data table based on DSP simulation, or to execute the above-described data query method of a relational data table based on DSP simulation.

[0040] On the other hand, the present invention also provides a computer-readable storage medium storing a processor-executable program, characterized in that the processor-executable program, when executed by a processor, is used to perform the above-described data storage of a relational data table based on DSP simulation, or to perform the above-described data query method of a relational data table based on DSP simulation.

[0041] The beneficial effects of this invention are as follows: Taking into account the characteristics of DSP simulation models, a relational data table organization structure for DSP simulation models is proposed, which is highly readable, simple in structure, easy to maintain, and supports complex query scenarios. Specifically, the model mapping table stores the mapping relationship and parameter correspondence between simulation models and model data tables, enabling automatic conversion between various DSP simulation models and model data tables. The model data table adopts a static model partitioning and dynamic model integration storage method, assigning unique identifiers to simulation model objects to form unique indexes, thereby managing simulation models and accelerating search speed. The model logic table abstracts the topological and organizational relationships between all simulation models, storing the relationship types, involved objects, and relationship attributes of all relationships, used to integrate and process complex relationship information between simulation models, thus supporting query scenarios based on model relationships. In this way, the relational data table structure possesses the ability to automatically store and convert DSP simulation models, form a system for managing model objects, handle relationships between models, and support complex query scenarios. Attached Figure Description

[0042] Figure 1 To represent intents for relational data;

[0043] Figure 2 Example diagram of the simulation model;

[0044] Figure 3 This is an example diagram of the organizational structure of a relational data table. Detailed Implementation

[0045] To provide a more complete and clear description of the technical solution and advantages of the relational data table organization structure, the data structure will be analyzed and explained below with reference to examples and accompanying drawings. Obviously, these examples are only used to explain the present invention and are not intended to limit the invention.

[0046] Figure 1 As intended for relational data representation in this invention, the data structure provided by this invention includes: a model data table, a model mapping table, and a model logic table. The model data table includes a plant table, an inter-plant data table, a static model table, and a dynamic model table. The model mapping table stores the simulation model type, model table name, and parameter correspondence rules. The model logic table stores the relation type, relation object identifier, and relation attributes.

[0047] The following is a specific example:

[0048] A certain simulation model, such as Figure 2 As shown, A i ( i =1, 2, 3) is the first i Factory station, C ij For A i A j Inter-factory lines between them, L 23 L 35 B represents the circuit in the static model. i ( i =1, 2, 3, 4, 5, 6) are nodes in the static model, T i ( i =1, 2, 3) represent the transformer in the static model, LD1 represents the load in the dynamic model, and G i ( i =1,2) represent the generator in the dynamic model, D i ( i =1,2) is a dynamic model, where B1, B2, T1, G1, D1 are within the space of plant A1, B3, B4, T2, LD1, D2 are within the space of plant A2, and B5, B6, T3, G2, D3 are within the space of plant A3.

[0049] Based on the relational data table and this embodiment, the data storage steps for the simulation model are as follows:

[0050] S101. Create a model mapping table, with fields including model type, relation table name, and parameter correspondence;

[0051] S102. Define the data mapping relationship between the plant and station, and store the plant and station type, plant and station table name, and the correspondence between plant and station parameter items and plant and station table fields into the model mapping table;

[0052] S103. Define the data mapping relationship between inter-plant lines, and store the inter-plant line type, inter-plant line table name, and the correspondence between inter-plant line parameter items and inter-plant line table fields into the model mapping table;

[0053] S104. Define the static model data mapping relationship. Each type of static model card corresponds to a static model data table. Traverse all static model card types of the simulation model, form key-value pairs between the model card parameter items and the fields of the model data table, perform JSON serialization to form the parameter correspondence, and store the model type, model table name, and correspondence of each type of static model into the model mapping table.

[0054] S105. Define the dynamic model data mapping relationship. All dynamic models are integrated and stored in a dynamic model table. Model card parameter items and parameter value key-value pairs are stored in the parameter content field of the dynamic model table through JSON serialization.

[0055] S106. Create all model data tables based on the parameter correspondence of the model mapping table, and add a unique identifier field as the unique index of the model data table;

[0056] S107. Create a model logical table with fields including relation type, unique identifier for relation object 1, unique identifier for relation object 2, and relation attributes;

[0057] S108. Traverse the simulation model, assign a unique identifier to the simulation model, and store the model parameters into the corresponding model data table according to the parameter correspondence in the model mapping table.

[0058] S109. Traverse the topological and organizational relationships between simulation models, and store the relationship type, the objects involved in the relationship, and the relationship attributes into the model logical table.

[0059] In this embodiment, the data structure after data storage is as follows: Figure 3 As shown, the tables include: Model Mapping Table, Plant / Site Table, Inter-plant Line Table, AC Node Table, AC Line Table, Transformer Table, Dynamic Model Table, and Model Logic Table. The following is a detailed description of each table:

[0060] F1. Model Mapping Table:

[0061] Fields:

[0062] Model_type: Model type, DSP simulation model card type

[0063] Table_name: The name of the relational table, the name of the model data table corresponding to this model type.

[0064] Rule: Parameter mapping relationship, the mapping relationship between simulation model card parameter items and corresponding model table fields, obtained by JSON serialization in key-value pair format.

[0065] F2. Plant / Station Table:

[0066] global_id: A unique identifier for the plant / station, ensuring the uniqueness of plant / station objects within the system and serving as a unique index for the plant / station table.

[0067] name: Common name of the plant / station

[0068] type: Type of plant

[0069] voltage: voltage level of the power plant

[0070] x: Geographic x-coordinate of the plant

[0071] y: Geographic coordinates of the plant / station

[0072] F3. Inter-factory wiring diagram:

[0073] global_id: A unique identifier for inter-plant lines, ensuring the uniqueness of inter-plant line objects within the system and serving as a unique index for the inter-plant line table.

[0074] name: Common name for inter-factory lines

[0075] The parameters in the inter-plant line table include:

[0076] type: AC / DC type of inter-factory lines

[0077] voltage: voltage level of inter-plant lines

[0078] num: Number of circuits in the inter-factory line

[0079] global1_id: A unique identifier for the first station in the inter-plant line connection.

[0080] global2_id: A unique identifier for the terminal station of the inter-plant line connection.

[0081] F4. Communication Node Table

[0082] Management fields:

[0083] global_id: A unique identifier for each node, ensuring its uniqueness within the system and serving as a unique index for the table.

[0084] Parameter fields:

[0085] The parameter fields correspond one-to-one with the communication node model parameter items in the simulation model file, and the correspondence is consistent with the parameter correspondence in the model mapping table.

[0086] F5. Transformer Meter

[0087] Management fields:

[0088] global_id: A unique identifier for the transformer, ensuring the uniqueness of the transformer and phase shifter within the system.

[0089] Parameter fields:

[0090] The parameter fields correspond one-to-one with the parameters in the simulation data file and the transformer model, and the correspondence is consistent with the parameter correspondence in the model mapping table.

[0091] F6. AC Line Table

[0092] Management fields:

[0093] global_id: A unique identifier for the line, ensuring the line's uniqueness within the system.

[0094] Parameter fields:

[0095] The parameter fields correspond one-to-one with the parameter items of the circuit model in the simulation data file, and the correspondence is consistent with the parameter correspondence in the model mapping table.

[0096] F7. Dynamic Model Table

[0097] Management fields:

[0098] global_id: A unique identifier for the dynamic model, ensuring its uniqueness within the system.

[0099] name: Common name for dynamic models

[0100] Parameter fields:

[0101] modelType: The model card type for dynamic models

[0102] parameters: Parameter content, including the parameter items and values ​​of the dynamic model card, obtained after JSON serialization of the parameter key-value pairs.

[0103] F8. Model Logic Table

[0104] Fields:

[0105] relation_type: The type of relationship, including topological and organizational relationships between simulation models.

[0106] global1_id: A unique identifier for relation object 1, a unique identifier for objects involved in the relation, and a regular index in the model's logical table.

[0107] global2_id: A unique identifier for relation object 2, a unique identifier for objects involved in the relation, and a regular index of the model's logical table.

[0108] relation_properties: Relational properties

[0109] In this embodiment of the invention, based on the data table organization structure after the implementation, the following query functions can be supported, but are not limited to:

[0110] S2. Device-level data query

[0111] Device-level data includes static model data and dynamic model data associated with that static model. The process for querying B4 data in this example is as follows:

[0112] S201. Use the B4 model type as a condition to query the model mapping table and obtain the communication node table of the model data table where the B4 model is located.

[0113] S202. Using the unique identifier B4 as a condition, perform a primary key query on the communication node table to obtain static model parameter information.

[0114] S203. Query the relation information of dynamic model electrical connection in the model logic table.

[0115] S204. Filter relations that contain the unique identifier B4, and obtain the unique identifiers of all dynamic models connected to B4.

[0116] S205. Using the unique identifier from step S204 as a condition, perform a primary key query on the dynamic model table to obtain the dynamic model parameters.

[0117] In this embodiment, step S202 can be queried Figure 2 In step S204, the parameter information of the static model B4 is retrieved, and the unique identifiers of the dynamic models LD1 and D2 connected to B4 can be found. In step S205, the parameter information of LD1 and D2 can be retrieved, thus completing the parameter query of the static model B4 and the dynamic models LD1 and D2 connected to B4.

[0118] S3. Plant / Station Level Data Query

[0119] Plant-level data includes all static and dynamic model data within the plant. The process for querying plant A1 data in this example is as follows:

[0120] S301. Query the relationships in the logical table of the query model that are of the subordinate plant type.

[0121] S302. Filter relationships containing the unique identifier of A1, and obtain the model data table name and model unique identifier of all static models within the A1 plant.

[0122] S303. Using the unique identifier from step S302 as a condition, perform a primary key query on the corresponding static model data table to obtain the static model parameters.

[0123] S304. Query the relation in the model logic table that is a dynamic model electrical connection.

[0124] S305. Filter the relational objects that contain the unique identifier code from step S302, and obtain the unique identifier codes of all dynamic models connected to the static model in step S302.

[0125] S306. Using the unique identifier from step S305 as a condition, perform a primary key query on the dynamic model table to obtain the dynamic model parameters.

[0126] In this example, step S302 can be used to query... Figure 2 The unique identifiers of B1, B2, and T1; step S303 allows querying the parameter information of B1, B2, and T1; step S305 allows querying... Figure 2 The unique identifiers of dynamic models G1 and D1 connected to B1, B2, and T1; step S306 can query... Figure 2 The system retrieves dynamic G1 and D1 parameter information, thereby enabling the querying of all static and dynamic model parameters within the plant.

[0127] As seen in the data storage process of this embodiment, the model mapping table defines the model mapping relationship, realizing the automatic conversion between the DSP simulation model and the model data table. During storage, all simulation models are assigned a unique identifier, serving as a unique index for the model data table. The model logic table abstractly stores the topology, organization, and other relationships of the simulation models, which can be used to integrate and process logical conditions in the query process. Furthermore, during the query process, the logical conditions involved in the query can be transformed from the model logic table into the primary key conditions of the model data table, converting complex logical queries into queries based on the primary keys of the model data table, thereby accelerating the query speed.

[0128] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A data storage method based on DSP simulation model relational data table, characterized in that, The method is: Creating a model mapping table; Obtaining a model data mapping relationship, and storing the model data mapping relationship into the model mapping table, the model data mapping relationship including a power station data mapping relationship, an inter-station line data mapping relationship, a static model data mapping relationship, and a dynamic model data mapping relationship; According to the mapping relationship of the model mapping table, creating a model data table and setting a model mapping identification code as an index of the model data table; Creating a model logic table; Iterating through simulation models, storing model parameters into corresponding model data tables according to a model mapping table parameter corresponding relationship after the simulation models are given the model mapping identification code; Iterating through topological relationships and organizational relationships between the simulation models, and storing relationship types, relationship involved objects, and relationship attributes into the model logic table according to model logic table fields; The storing of the relationship types, the relationship involved objects, and the relationship attributes into the model logic table according to the model logic table fields includes: abstracting and integrating corresponding relationships between the simulation models, including topological relationships and organizational relationships, into the model logic table, thereby supporting a query scenario based on model relationships; the model logic table fields include relationship types, relationship object identification codes, and relationship attributes; the relationship types store types of relationships between the simulation models, including topological relationships and organizational relationships, and are used to narrow a data retrieval range when a model relationship-based query is performed; the relationship object identification codes are used to store identification codes of the simulation models involved in the relationships, and are general indexes of the model logic table; and the relationship attributes store results obtained by JSON serialization of attribute key-value pairs accompanying the simulation model relationships; The storing of the model parameters into corresponding model data tables according to the model mapping table parameter corresponding relationship includes: storing parameter information of the simulation models into the model data tables, and forming model object indexes; the model data tables include a power station table, an inter-station line table, a static model table, and a dynamic model table, wherein the power station table and the inter-station line table are used to store management information, parameter information, and connection relationships of power plants and substations in the simulation models into the power station table and the inter-station line table; the static model table is used to store management information and parameter information of static models, such as alternating current nodes, direct current nodes, alternating current lines, direct current lines, transformers, phase shifters, node supplementary models, and branch supplementary models, in the simulation models into the static model table; and the dynamic model table is used to store management information and parameter information of dynamic models, such as generators and loads, in the simulation models into the dynamic model table.

2. The data storage method based on a DSP simulation model relational data table according to claim 1, wherein The power station data mapping relationship includes a power station type, a power station table name, and a corresponding relationship between power station parameter items and power station table fields; The inter-station line data mapping relationship includes an inter-station line type, an inter-station line table name, and a corresponding relationship between inter-station line parameter items and inter-station line table fields; The static model data mapping relationship includes a model type, a model table name, and a parameter correspondence of each type of static model; each type of static model corresponds to a static model data table; all static model types of the simulation model are traversed; a static model parameter item and a static model data table field form a key-value pair; and a parameter correspondence is formed by JSON serialization. The dynamic model data mapping relationship includes all dynamic model integrated storage to a dynamic model table; a dynamic model parameter item and a dynamic model parameter value key-value pair are stored in a parameter content field of the dynamic model table by JSON serialization.

3. The data storage method based on DSP simulation model relational data table according to claim 1, characterized in that, The model data mapping relationship stored in the model mapping table includes: the mapping of the simulation model and the relationship table and the corresponding rule of the model parameter item and the relationship table field are stored in the model mapping table to support the automatic conversion process of the simulation model data and the relationship table data; the model mapping table field includes a model type, a relationship table name, and a parameter correspondence; the model type is used to store the model card type of the simulation model; the relationship table name is used to store the data table name where the model is mapped to the relationship table; and the parameter correspondence is used to store the result of the model card parameter item-relationship table field key-value pair correspondence after JSON serialization, to describe the correspondence between the model parameter item and the table field.

4. The data storage method based on DSP simulation model relational data table according to claim 1, characterized in that, The fields of the plant station table include a plant station management field and a plant station parameter field; The plant station management field includes a plant station identification code, which is an index of the plant station table and is used to store the system information of the plant station in time and space; The plant station parameter field includes a plant station type, a voltage level, a geographic coordinate x, and a geographic coordinate y, and is used to store the specific parameters of the plant station; The inter-plant line table includes an inter-plant line management field and an inter-plant line parameter field; the inter-plant line management field includes an inter-plant line identification code, which is an index of the inter-plant line table and is used to store the system information of the inter-plant line in time and space; and the inter-plant line parameter field includes an inter-plant line type, a voltage level, and a line number, and is used to store the specific parameters of the inter-plant line; The single-type static model data table includes a model management field and a model parameter field; the model management field includes a static model identification code, which is an index of the single-type static model data table and is used to store the system information of the static model in time and space; and the model parameter field corresponds to the parameter item of the model parameter card one by one, and the correspondence relationship is consistent with the parameter correspondence of the mapping table; The fields of the dynamic model table include a dynamic model management field and a dynamic model parameter field; The dynamic model management field includes a dynamic model identification code, which is an index of the dynamic model data table and is used to store the system information of the dynamic model in time and space; and the dynamic model parameter field includes a model type and parameter content, the model type is used to store the model card type of the dynamic model, and the parameter content is used to store the result of the dynamic model parameter item-parameter value key-value pair after JSON serialization.

5. A data query method based on a DSP simulation model relational data table, characterized in that, The data query method comprises a device-level data query step and a station-level data query step; the device-level data comprises static model data and dynamic model data connected with the static model data; the station-level data comprises all static model data and dynamic model data in the station; and the relational data table organization structure stores data by the data storage method of any one of claims 1-4.

6. The method of claim 5, wherein the DSP simulation model relational data table is based on a DSP simulation model relationship table. The device-level data query step is: taking the model type of the device as a condition to query the model mapping table to obtain the model data table where the data of the queried device is located; taking the device model identification code as a condition to query the primary key of the static model table to obtain the static model parameter information; querying the relationship type in the model logic table which is an electrical connection of a dynamic model; filtering the relationship in the relationship object which contains the device model identification code to obtain the identification codes of all dynamic models connected with the device; taking the identification code of the dynamic model as a condition to query the primary key of the dynamic model table to obtain the device-level dynamic model parameter; The station-level data query step is: querying the relationship type in the model logic table which is a subordinate station; filtering the relationship in the relationship object which contains the station data identification code to obtain the model data table name and the static model identification code corresponding to all static models in the station; taking the static model identification code as a condition to query the primary key of the corresponding static model data table to obtain the station-level data static model parameter; querying the relationship type in the model logic table which is an electrical connection of a dynamic model; filtering the relationship in the relationship object which contains the static model identification code to obtain the identification codes of all dynamic models connected with the static model; taking the identification code of the dynamic model as a condition to query the primary key of the dynamic model table to obtain the station-level data dynamic model parameter.

7. A computer apparatus, comprising: The device comprises a memory and a processor, the memory is used to store at least one program, and the processor is used to load the at least one program to execute the data storage method of the DSP simulation model relational data table based on any one of claims 1-4 or the data query method of the DSP simulation model relational data table based on any one of claims 5-6.

8. A computer readable storage medium, in which a program executable by a processor is stored, characterized in that, The program executable by the processor is used to execute the data storage method of the DSP simulation model relational data table based on any one of claims 1-4 or the data query method of the DSP simulation model relational data table based on any one of claims 5-6 when executed by the processor.

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