A data interaction system for supporting different container groups

Abstract

The present invention relates to the field of data interaction technology, and specifically discloses a data interaction system for supporting different container groups, including a demand acquisition module, a cloud-edge interaction management module, a test optimization module, a human-computer interaction module and an API interface; the present invention obtains indicators through literature research and field investigations, and clarifies the needs of the data interaction system, schedules communication and data interaction between the cloud and edge clusters through the cloud-edge interaction management module, performs real-time detection of data interaction quality and establishes a data interaction delay detection model, and the monitoring factors of data interaction quality include power imbalance detection value, current imbalance detection value, voltage detection value, intelligent detection value and error detection value, which help to easily process a large number of concurrent messages, meet the needs of massive data interaction between different container groups, reduce the dependency between various application modules, and improve the flexibility and maintainability of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of data interaction, and more particularly, to a data interaction system supported by different container groups. Background Art

[0002] With the rapid development of containerization technology, encapsulating applications and services into containers has become a standard practice in modern cloud computing environments. This containerization approach helps achieve higher scalability, elasticity, and resource utilization. However, in an environment supported by multiple container groups, data interaction between containers becomes complex. Therefore, an effective data interaction system is needed to meet the needs of different application scenarios. When interacting between the scheduling cloud and edge clusters, data interaction is currently mostly carried out through shared databases and storage. This interaction method has the disadvantages of high latency and low throughput, and is very prone to performance bottlenecks. Data interaction through the message bus provided by the scheduling cloud can solve this problem. To address the above problems, a technical solution is now provided. Summary of the Invention

[0003] In order to overcome the above-mentioned defects of the prior art, the present invention provides a data interaction system for supporting different container groups. Indicators are obtained through literature research and field investigations, and the needs of the data interaction system are clarified. The communication and data interaction between the cloud and edge clusters are scheduled through the cloud-edge interaction management module, and the data interaction quality is detected in real time and a data interaction delay detection model is established. The monitoring factors of the data interaction quality include power imbalance detection value, current imbalance detection value, voltage detection value, intelligent detection value and error detection value, which help to easily process a large number of concurrent messages, meet the needs of massive data interaction between different container groups, reduce the dependence between various application modules, improve the flexibility and maintainability of the system, and improve the efficiency of point-to-point work of engineering site protection information, so as to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A data interaction system for supporting different container groups, including a demand acquisition module, a cloud-edge interaction management module, a test optimization module, a human-computer interaction module, and an API interface. Its specific functions are:

[0006] The requirements acquisition module is used to obtain indicators through literature research and field investigations, and to clarify the requirements of the data interaction system;

[0007] The cloud-edge interaction management module is responsible for scheduling communication and data interaction between the cloud and edge clusters, including the registration management unit, the base service unit, the application interaction service unit, and the edge cluster monitoring center;

[0008] The test optimization module is used to perform real-time detection of data interaction quality. The monitoring factors of data interaction quality include power imbalance detection value, current imbalance detection value, voltage detection value, intelligent detection value, and error detection value. A data interaction delay detection model is established. The formula of the data interaction delay detection model is:

[0009]

[0010] Where: G MN is the data interaction delay time, P ML is the power imbalance detection value, P MW is the current unbalance detection value, P MC is the voltage imbalance detection value, P MS is the intelligent detection value, P MX is the error detection value;

[0011] The human-computer interaction module is divided into a client and a server, which are used to implement remote screen calls between the cloud and edge clusters in a vertical environment;

[0012] The API interface is used for data interaction between modules.

[0013] As a further solution of the present invention, the demand acquisition module is connected to the cloud-edge interaction management module, the cloud-edge interaction management module is connected to the data security module, the data security module is connected to the test optimization module, and the test optimization module is connected to the human-computer interaction module.

[0014] As a further solution of the present invention, the cloud-edge interaction management module collects network, provincial and local edge cluster forwarding adjustment demand and edge cluster operation information through cloud-edge interaction services in the vertical environment; in the horizontal environment, it adds microservices by building multi-source data, uses data synchronization, data extraction and data subscription, extracts external horizontal data to the cloud, and establishes a cloud data pool.

[0015] As a further solution of the present invention, the cloud data pool includes a real-time database, a historical library, a graphic model library and an offline model library. The real-time database is established based on the scheduling cloud table storage OTS to store real-time operation data and online model data; the historical library is established based on the scheduling cloud time series library TSDB to store historical alarm data and change data; the graphic model library is established based on the scheduling cloud object storage OSS to store graphic files and model files; the offline model library is established based on the scheduling cloud relationship library RDS to store offline model data.

[0016] As a further solution of the present invention, the deployment requirements of the cloud-edge interaction management module for realizing data interaction include deployment environment, security assurance, horizontal interaction, vertical interaction, service interaction, relationship library interaction and file storage construction. The deployment environment requirement is to be deployed in a containerized manner; the security assurance requirement is to provide security protection components through the scheduling cloud to ensure comprehensive security protection; the service interaction requirement is that data interaction is realized by the cloud service bus provided by the regulation cloud; the relationship library interaction requirement is to realize model library construction by the cloud service bus provided by the regulation cloud, and use the cloud-based unified database service to realize the storage of application models and extended models; the file storage construction requirement is to use the cloud-based unified object storage to realize the storage of files, graphics and CIM file model files.

[0017] As a further solution of the present invention, horizontal interaction requires the use of the message bus MQ provided by the control cloud for data interaction between cloud applications, building a message sending and receiving mechanism between business application functions, and realizing data subscription interaction between cloud applications by customizing different topics. The data is pushed to the cloud data center, and the cloud data center customizes data services, which are then used to provide application data services to the outside world; vertical interaction requires data interaction between cloud applications and edge clusters, which is realized by the application interaction services provided by the cloud system platform and implemented by the application interaction agents of each cloud.

[0018] As a further solution of the present invention, the protection information automatic point-to-point subsystem includes an information interaction module with the protection information main station, including an interactive communication unit, a data reading unit and a data conversion unit; the protection device simulation module includes a third communication framework construction unit, a third message processing unit, a third data storage unit and a third human-computer interaction unit; the automatic point-to-point management module includes a substation information triggering unit, a main station information monitoring unit, a main-substation information verification unit and a result display and export unit.

[0019] As a further solution of the present invention, the power imbalance detection value is obtained by establishing a power imbalance detection model through the bus active balance detection value, the bus reactive balance detection value, the line's opposite end active balance detection value, the line's opposite end reactive balance detection value, the transformer active balance detection value and the transformer reactive balance detection value; the current imbalance detection value is obtained by establishing a current imbalance detection model through the bus phase current deviation value and the line's opposite end current balance detection value; the voltage imbalance detection value is obtained by establishing a voltage imbalance detection model through the bus voltage, the bus phase voltage deviation value, the bus line voltage and the transformer neutral point voltage; the intelligent detection value is obtained by establishing an intelligent detection model through the unreasonable value of the main transformer gear, the reactive error value of the capacitor, the unreasonable value of the telesignal and the knife switch and bus detection value; the error detection value is obtained by establishing an error detection model through the multi-source data error and the forwarding source missing value.

[0020] As a further solution of the present invention, the formula of the power imbalance detection model is:

[0021]

[0022] Where: Y WL is the busbar active power balance detection value, Y FL is the busbar reactive balance detection value, Y HL Y is the active balance detection value of the line end, NL Y is the reactive balance detection value of the line end, ML is the transformer active balance detection value, Y DL is the reactive balance detection value of the transformer;

[0023] The formula of the current imbalance detection model is:

[0024]

[0025] Where: W TW is the bus phase current deviation value, W XW It is the current balance detection value of the opposite end of the line;

[0026] The formula of the voltage unbalance detection model is:

[0027]

[0028] Where: V EC is the bus voltage, V RC is the bus phase voltage deviation value, V ZC is the bus line voltage, V SC is the transformer neutral point voltage.

[0029] As a further solution of the present invention, the formula of the intelligent detection model is:

[0030]

[0031] Where: P YS The unreasonable value of the main gear position, P ES is the reactive error value of the capacitor, P QS is the unreasonable value of remote signal, P HS The detection value of the knife switch and busbar;

[0032] The formula of the error detection model is:

[0033]

[0034] Where: D NX is the multi-source data error, R NX Missing value for forwarding source.

[0035] The technical effects and advantages of the data interaction system supported by different container groups of the present invention are as follows:

[0036] 1. The present invention can easily process a large number of concurrent messages through the message bus provided by the scheduling cloud, meeting the needs of massive data interaction between different container groups;

[0037] 2. By using the message bus provided by the scheduling cloud, the present invention can achieve loose coupling in data interaction between different container groups, reduce the dependencies between various application modules, and improve the flexibility and maintainability of the system;

[0038] 3. The present invention can ensure that messages are not lost in the event of a network or system failure, thereby improving the reliability and stability of the system, and helping to simplify the data interaction process between different container groups, reducing development difficulty and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 The figure is a structural diagram of a data interaction system supported by different container groups according to the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0041] A data interaction system for supporting different container groups, including a demand acquisition module, a cloud-edge interaction management module, a test optimization module, a human-computer interaction module, and an API interface. Its specific functions are:

[0042] The requirements acquisition module is used to obtain indicators through literature research and field investigations, and to clarify the requirements of the data interaction system;

[0043] The cloud-edge interaction management module is responsible for scheduling communication and data interaction between the cloud and edge clusters, including the registration management unit, the base service unit, the application interaction service unit, and the edge cluster monitoring center;

[0044] The test optimization module is used to perform real-time detection of data interaction quality. The monitoring factors of data interaction quality include power imbalance detection value, current imbalance detection value, voltage detection value, intelligent detection value, and error detection value. A data interaction delay detection model is established. The formula of the data interaction delay detection model is:

[0045]

[0046] Where: GMN is the data interaction delay time, P ML is the power imbalance detection value, P MW is the current unbalance detection value, P MC is the voltage imbalance detection value, P MS is the intelligent detection value, P MX is the error detection value;

[0047] The formula for the data interaction delay detection model comprehensively considers multiple factors, including power imbalance, current imbalance, voltage imbalance, intelligent detection, and error detection. By taking these factors into account, it can more comprehensively evaluate the data interaction delay duration, improving the accuracy of the model. Because the formula integrates multiple detection values, the flexibility of the formula enables it to adapt to various situations when different detection parameters are involved in different scenarios. The formula of the data interaction delay detection model that comprehensively considers multiple factors helps to improve the understanding and evaluation of data interaction delay duration and provides a useful tool for decision-making, optimization, and standardization. It can adapt to various situations, quantify problems, support decision-making, and help improve system performance.

[0048] The human-computer interaction module is divided into a client and a server, which are used to implement remote screen calls between the cloud and edge clusters in a vertical environment;

[0049] The API interface is used for data interaction between modules.

[0050] The human-computer interaction module is divided into a client and a server, and is used to implement remote screen calls between the cloud and edge clusters in a vertical environment. The client connects to the server via JMS, obtains standard SVG screen files and displays them in the client browser, receives data packets in real time, and refreshes the screen. The server responds to client requests and provides standard SVG screen files and screen-related DL476 extended data packets via JMS. Remote screen calls are based on the SVG and DL476 standards and JMS services, where SVG serves as the standard for screen content definition and DL476 serves as the standard for data transmission protocol. The JMS service is responsible for communication and data exchange between the browsing and browsing ends.

[0051] Among them, the client functions include the client screen remote call browser and client gateway service. The screen remote call browser is mainly used to view the screen information from various edge clusters vertically and various other systems horizontally. The browser sends open screen, data refresh, and stop refresh requests to the gateway of each screen call server according to the operation. It also displays the screen file sent by the other end in the browser window and refreshes the relevant data in real time on the screen to ensure that its screen display result is basically consistent with the screen of the other end system. The client gateway service sends various browser requests to the server gateway machine through the JMS data service, receives various data returned by it, and forwards it to the corresponding browser end.

[0052] The server needs to convert the local screen into a standard SVG screen file and be able to upload the correct SVG screen file according to the open screen request sent by the client. After the screen file transmission is completed, it responds to the data refresh request and sends the corresponding data of the screen to the client in real time in the format of the extended DL476 protocol, and can also upload the changed data in the screen in real time.

[0053] The interface display of the human-computer interaction module client must have the following functions: the client browser has the function of classifying all servers by area and type; the client browser has the function of zooming in, out, and panning the currently open screen; the client browser has the function of recording the list of recently opened screens; the client browser has the function of forward and backward; the client browser has the function of jumping to the corresponding screen through the photosensitive points in the screen; the client browser has the function of selecting different layers to display in the current screen; the screen call service has the function of displaying the current channel status on the interface.

[0054] In the embodiment of the present invention, the demand acquisition module is connected to the cloud-edge interaction management module, the cloud-edge interaction management module is connected to the data security module, the data security module is connected to the test optimization module, and the test optimization module is connected to the human-computer interaction module.

[0055] Through the data interaction delay detection model, the system operation data of power plants and substations collected by telecontrol are obtained for correlation analysis, prompts are given for data that does not meet the basic laws of power grid operation, and quantitative evaluation is performed on the data of each plant and substation.

[0056] In the embodiment of the present invention, the cloud-edge interaction management module collects network, provincial and local edge cluster forwarding adjustment demand and edge cluster operation information through cloud-edge interaction services in the vertical environment; in the horizontal environment, it adds microservices by building multi-source data, uses data synchronization, data extraction and data subscription, extracts external horizontal data to the cloud, and establishes a cloud data pool.

[0057] In the embodiment of the present invention, the cloud data pool includes a real-time database, a history library, a graphic model library and an offline model library. The real-time database is established based on the scheduling cloud table storage OTS to store real-time operation data and online model data; the history library is established based on the scheduling cloud time series library TSDB to store historical alarm data and change data; the graphic model library is established based on the scheduling cloud object storage OSS to store graphic files and model files; the offline model library is established based on the scheduling cloud relationship library RDS to store offline model data.

[0058] In the embodiment of the present invention, the deployment requirements of the cloud-edge interaction management module to realize data interaction include deployment environment, security assurance, horizontal interaction, vertical interaction, service interaction, relationship library interaction and file storage construction. The deployment environment requirement is to be deployed in a containerized manner; the security assurance requirement is to provide security protection components through the scheduling cloud to ensure comprehensive security protection; the service interaction requirement is that data interaction is realized by the cloud service bus provided by the regulation cloud; the relationship library interaction requirement is to realize model library construction by the cloud service bus provided by the regulation cloud, and use the cloud unified database service to realize the storage of application models and extension models; the file storage construction requirement is to use the cloud unified object storage to realize the storage of files, graphics and CIM file model files.

[0059] In the embodiment of the present invention, the horizontal interaction requirement is that the data interaction between cloud applications uses the message bus MQ provided by the control cloud to build a message sending and receiving mechanism between business application functions, and by customizing different topics, realize data subscription interaction between cloud applications, push data to the cloud data center, customize data services with the help of the cloud data center, and provide application data services to the outside world; the vertical interaction requirement is the data interaction between cloud applications and edge clusters, which is realized by the application interaction services provided by the cloud system platform and the application interaction agents of each cloud.

[0060] In the embodiment of the present invention, the automatic point-to-point subsystem of protection information includes an information interaction module with the protection information main station, including an interactive communication unit, a data reading unit and a data conversion unit; the protection device simulation module includes a third communication framework construction unit, a third message processing unit, a third data storage unit and a third human-computer interaction unit; the automatic point-to-point management module includes a substation information triggering unit, a main station information monitoring unit, a main-substation information verification unit and a result display and export unit.

[0061] In the embodiment of the present invention, the power imbalance detection value is obtained by establishing a power imbalance detection model through the bus active balance detection value, the bus reactive balance detection value, the line's opposite end active balance detection value, the line's opposite end reactive balance detection value, the transformer active balance detection value, and the transformer reactive balance detection value; the current imbalance detection value is obtained by establishing a current imbalance detection model through the bus phase current deviation value and the line's opposite end current balance detection value; the voltage imbalance detection value is obtained by establishing a voltage imbalance detection model through the bus voltage, the bus phase voltage deviation value, the bus line voltage, and the transformer neutral point voltage; the intelligent detection value is obtained by establishing an intelligent detection model through the unreasonable value of the main transformer gear, the reactive error value of the capacitor, the unreasonable value of the telesignal, and the knife switch and bus detection value; and the error detection value is obtained by establishing an error detection model through the multi-source data error and the forwarding source missing value.

[0062] The formula of the power imbalance detection model in the embodiment of the present invention is:

[0063]

[0064] Where: Y WL is the busbar active power balance detection value, Y FL is the busbar reactive balance detection value, Y HL Y is the active balance detection value of the line end, NL Y is the reactive balance detection value of the line end, ML is the transformer active balance detection value, Y DL is the reactive balance detection value of the transformer;

[0065] The power imbalance detection model's formula integrates multiple factors, including busbar active power balance, busbar reactive power balance, line active power balance, line reactive power balance, transformer active power balance, and transformer reactive power balance. By incorporating these factors, power imbalance detection values can be more comprehensively evaluated, improving the model's accuracy and contributing to a better understanding and assessment of power imbalance detection values. It also provides a useful tool for decision-making, optimization, and standardization, adapting to various situations, quantifying issues, supporting decision-making, and contributing to improved system performance.

[0066] The formula of the current imbalance detection model is:

[0067]

[0068] Where: W TW is the bus phase current deviation value, W XW It is the current balance detection value of the opposite end of the line;

[0069] The formula of the current imbalance detection model combines the bus phase current deviation value and the line end current balance detection value to calculate the current imbalance detection value, which reduces complexity, helps to quantify and evaluate current balance problems, and provides a convenient tool to monitor and analyze the performance of the power system. It can help power system operators more easily identify current balance problems and take necessary measures to maintain the normal operation of the system.

[0070] The formula of the voltage unbalance detection model is:

[0071]

[0072] Where: V EC is the bus voltage, V RC is the bus phase voltage deviation value, V ZC is the bus line voltage, V SC is the transformer neutral point voltage.

[0073] The formula of the voltage unbalance detection model comprehensively considers multiple factors, including bus voltage, bus phase voltage deviation value, bus line voltage and transformer neutral point voltage. By taking these factors into account, the value of the voltage unbalance detection value can be more comprehensively evaluated, and a useful tool for decision-making, optimization and standardization can be provided. The voltage unbalance detection model can adapt to various situations, quantify problems, support decision-making, and help improve power system performance.

[0074] The formula of the intelligent detection model in the embodiment of the present invention is:

[0075]

[0076] Where: P YS The unreasonable value of the main gear position, P ES is the reactive error value of the capacitor, P QS is the unreasonable value of remote signal, P HS The detection value of the knife switch and busbar;

[0077] The formula of the intelligent detection model comprehensively considers multiple factors, including unreasonable values of the main transformer gear position, the reactive power error value of the capacitor, unreasonable values of the remote signal, and the detection value of the knife switch and busbar. By taking these factors into account, the intelligent detection value can be evaluated more comprehensively. It can be used as a decision support tool to help power system operators identify potential problems and take appropriate measures to improve system performance.

[0078] The formula of the error detection model is:

[0079]

[0080] Where: D NX is the multi-source data error, RNX Missing value for forwarding source.

[0081] The formula of the error detection model includes two key parameters: multi-source data error and forwarding source missing value, which makes the calculation and analysis of error detection easier and more efficient. It can quickly calculate the error detection value, thereby quickly identifying potential problems or abnormal situations, helping to detect and deal with data errors early, improve data quality and reliability, and help to quickly and effectively identify and quantify data errors, improve data quality, and support data analysis and decision-making processes.

[0082] The power imbalance detection value is obtained by establishing a power imbalance detection model based on the busbar active power balance detection value, busbar reactive power balance detection value, line end active power balance detection value, line end reactive power balance detection value, transformer active power balance detection value, and transformer reactive power balance detection value. For the busbar active power balance detection value, under normal circumstances, the accumulated value of the active power flowing into the busbar and the active power flowing out of the busbar tends to 0. For each device connected to the busbar, when the active power measurement of each device is valid, the active power measurement value of each device is accumulated. When the result exceeds the set busbar active power imbalance threshold, the plant station will list this indicator.

[0083] For the detection of busbar reactive power balance, under normal circumstances, the cumulative value of reactive power flowing into the busbar and the reactive power flowing out of the busbar tends to 0. For each device connected to the busbar, when the reactive power measurement of each device is valid, the reactive power measurement value of each device is accumulated. When the result exceeds the set busbar reactive power imbalance threshold, the plant will list this indicator.

[0084] For the detection of transformer active power balance, under normal circumstances, the active power flowing into the transformer and the active power flowing out should be accumulated to 0 after deducting the transformer loss. For each coil of the transformer, when the active power is measured and the measurement is normal, the measured values are accumulated. When the set transformer active power imbalance threshold is exceeded, the plant where the transformer is located will list this indicator;

[0085] For the detection of transformer reactive balance detection value, under normal circumstances, the reactive power flowing into the transformer and the reactive power flowing out should add up to 0 after deducting the transformer loss. For each coil of the transformer, when its reactive power is measured and the measurement is normal, the measured value is accumulated and the transformer loss is deducted. When it exceeds the set transformer reactive imbalance threshold value, the plant where the transformer is located will list this indicator.

[0086] The detection of the current balance detection value at the opposite end of the line is based on the average value of the measured bus phase current. When the deviation between the phase current and the reference value exceeds 5%, the plant station will list this indicator.

[0087] The intelligent detection value is obtained by establishing an intelligent detection model based on the unreasonable value of the main transformer gear, the reactive error value of the capacitor, the unreasonable value of the telemetering, and the detection value of the knife switch and busbar. For the detection of unreasonable main transformer gear value, when the difference between the estimated gear and the measured gear of the transformer exceeds the specified range, the plant station will list this indicator. When the on-load tap changer gear exceeds the highest gear or is lower than the lowest gear, this indicator will be listed at the plant station; for the detection of the reactive error value of the capacitor, when the error between the calculated reactive value and the actual measured value of the capacitor is large, the plant station will list this indicator; for the detection of unreasonable telemetering value, when the telemetering value information shows that the switch or knife switch is closed or open, which is inconsistent with the telemetering value, it means that the telemetering value or telemetering value is incorrect, and the plant station will list this indicator; for the detection of the knife switch and busbar detection value, when two knife switches are connected to the busbar in parallel, the plant station will list this indicator.

[0088] The error detection value is obtained by establishing an error detection model based on multi-source data errors and missing forwarding source values. For the detection of multi-source data errors, the local RTU data of each measuring point of each plant station is compared with the ground-tuning forwarding data. When the telesignaling is inconsistent or the telemetry error is large, the plant station will list this indicator; for the detection of missing forwarding source values, when the measuring point data lacks a forwarding source, the plant station will list this item.

[0089] This embodiment obtains indicators through literature research and field investigations, and clarifies the requirements of the data interaction system. It schedules communication and data interaction between the cloud and edge clusters through the cloud-edge interaction management module, performs real-time detection of data interaction quality, and establishes a data interaction delay detection model. The monitoring factors of data interaction quality include power imbalance detection value, current imbalance detection value, voltage detection value, intelligent detection value, and error detection value, which help to easily process a large number of concurrent messages, meet the needs of massive data interaction between different container groups, reduce the dependency between various application modules, and improve the flexibility and maintainability of the system.

[0090] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0091] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A data interaction system for supporting different container groups, including a demand acquisition module, a cloud-edge interaction management module, a test optimization module, a human-computer interaction module and an API interface, characterized in that: The requirements acquisition module is used to obtain indicators through literature research and field investigations, and to clarify the requirements of the data interaction system; The cloud-edge interaction management module is responsible for scheduling communication and data interaction between the cloud and edge clusters, including the registration management unit, the base service unit, the application interaction service unit, and the edge cluster monitoring center; The test optimization module is used to perform real-time detection of data interaction quality. The monitoring factors of data interaction quality include power imbalance detection value, current imbalance detection value, voltage detection value, intelligent detection value, and error detection value. A data interaction delay detection model is established. The formula of the data interaction delay detection model is: Where: G MN is the data interaction delay time, P ML is the power imbalance detection value, P MW is the current unbalance detection value, P MC is the voltage imbalance detection value, P MS is the intelligent detection value, P MX is the error detection value; The human-computer interaction module is divided into a client and a server, which are used to implement remote screen calls between the cloud and edge clusters in a vertical environment; The API interface is used for data interaction between modules; The demand acquisition module is connected to the cloud-edge interaction management module, the cloud-edge interaction management module is connected to the data security module, the data security module is connected to the test optimization module, and the test optimization module is connected to the human-computer interaction module; In the vertical environment, the cloud-edge interaction management module collects network and provincial edge cluster forwarding adjustment demand and edge cluster operation information through cloud-edge interaction services; in the horizontal environment, it builds multi-source data to join microservices, uses data synchronization, data extraction and data subscription, extracts external horizontal data to the cloud, and establishes a cloud data pool; The cloud data pool includes a real-time database, a historical database, a graphic model library, and an offline model library. The real-time database is based on the scheduling cloud table storage (OTS) to store real-time operation data and online model data. The historical database is based on the scheduling cloud time series database (TSDB) to store historical alarm data and change data. The graphic model library is based on the scheduling cloud object storage (OSS) to store graphic files and model files. The offline model library is based on the scheduling cloud relational database (RDS) to store offline model data. The power imbalance detection value is obtained by establishing a power imbalance detection model based on the bus active balance detection value, bus reactive balance detection value, line opposite end active balance detection value, line opposite end reactive balance detection value, transformer active balance detection value and transformer reactive balance detection value. The current imbalance detection value is obtained by establishing a current imbalance detection model based on the bus phase current deviation value and line opposite end current balance detection value. The voltage imbalance detection value is obtained by establishing a voltage imbalance detection model based on the bus voltage, bus phase voltage deviation value, bus line voltage and transformer neutral point voltage. The intelligent detection value is obtained by establishing an intelligent detection model based on the unreasonable value of the main transformer gear position, the reactive error value of the capacitor, the unreasonable value of the telesignal and the knife switch and bus detection value. The error detection value is obtained by establishing an error detection model based on the multi-source data error and the forwarding source missing value.

2. A data interaction system for supporting different container groups according to claim 1, characterized in that: The deployment requirements for data interaction in the cloud-edge interaction management module include deployment environment, security assurance, horizontal interaction, vertical interaction, service interaction, relationship library interaction, and file storage construction. The deployment environment is required to be deployed in a containerized manner; the security assurance requirement is to provide security protection components through the scheduling cloud to ensure comprehensive security protection; the service interaction requirement is that data interaction is implemented by the cloud service bus provided by the control cloud; the relationship library interaction requirement is that the cloud service bus provided by the control cloud is used to implement model library construction, and the unified database service on the cloud is used to implement the storage of application models and extended models; The file storage construction requirement is to use cloud-based unified object storage to realize the storage of files, graphics and CIM file model files.

3. A data interaction system for supporting different container groups according to claim 2, characterized in that: Horizontal interaction requires that data interaction between cloud applications use the message bus MQ provided by the control cloud, build a message sending and receiving mechanism between business application functions, and realize data subscription interaction between cloud applications by customizing different topics. The data is pushed to the cloud data center, and the cloud data center customizes data services, which are then used to provide application data services to the outside world. Vertical interaction requires data interaction between cloud applications and edge clusters, which is realized by the application interaction services provided by the cloud system platform and the application interaction agents of each cloud.

4. A data interaction system for supporting different container groups according to claim 1, characterized in that: The formula of the power imbalance detection model is: Where: Y WL is the busbar active power balance detection value, Y FL is the busbar reactive balance detection value, Y HL Y is the active balance detection value of the line end, HL Y is the reactive balance detection value of the line end, ML is the transformer active balance detection value, Y DL is the reactive balance detection value of the transformer; The formula of the current imbalance detection model is: Where: W TW is the bus phase current deviation value, W XW It is the current balance detection value of the opposite end of the line; The formula of the voltage unbalance detection model is: Where: V EC is the bus voltage, V RC is the bus phase voltage deviation value, V ZC is the bus line voltage, V SC is the transformer neutral point voltage.

5. A data interaction system for supporting different container groups according to claim 1, characterized in that: The formula of the intelligent detection model is: Where: P YS The unreasonable value of the main gear position, P ES is the reactive error value of the capacitor, P QS is the unreasonable value of remote signal, P HS The detection value of the knife switch and busbar; The formula of the error detection model is: Where: D NX is the multi-source data error, R NX Missing value for forwarding source.

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