A method and system for regulating real-time section consistency check of master and standby machines of a system

Abstract

A method and system for verifying the real-time cross-sectional consistency of a control system's primary and backup units. The method includes: a background verification module for collecting, extracting, and comparing real-time cross-sectional data from the primary and backup units across multiple dimensions; a front-end display module that integrates all verification results through a human-computer interaction interface; displays details of discrepancies by verification type; performs automatic verification at fixed times daily; allows querying historical reports and setting verification parameters; an alarm module that periodically acquires verification results and issues alarms for inconsistencies according to preset rules; configures alarm suppression and sets alarm levels based on the severity of discrepancies; monitors AGC input data, renewable energy active power, and command jumps in real time; sends alarms and switches the AGC state to locked state when a jump is detected or the AGC main control program is automatically restarted due to an anomaly; and a report generation module that automatically generates standardized electronic reports; stores the reports in a designated directory; and allows querying and exporting historical reports. This invention ensures the stable and reliable operation of the control system.

Description

Technical Field

[0001] This invention belongs to the field of power grid control system operation and maintenance technology, and specifically relates to a method and system for real-time cross-sectional consistency verification of the main and backup units of the control system. Background Technology

[0002] As power grid structures become increasingly complex and installed capacity continues to grow, smart grid dispatch and control systems have become the core support for the safe and stable operation of the power grid. Key applications such as SCADA, front-end systems, and AGC (Automatic Generation Control) all employ a dual-machine redundancy configuration. During normal operation, the main unit is responsible for providing external dispatch and monitoring screens, data analysis, and business interaction services. The backup unit synchronously receives data and completes internal processing, serving as a redundant backup to ensure rapid takeover of the main unit in case of failure or maintenance, guaranteeing uninterrupted service.

[0003] Currently, with the continuous expansion of power grid models and installed capacity, and the increasing service life of control system hardware equipment, operational risks arising from hardware failures, software and hardware maintenance and upgrades, and adjustments to AGC control strategies are becoming increasingly prominent. During long-term operation of the primary and backup units, inconsistencies in data such as models, formulas, parameters, program versions, and key configurations can easily occur due to factors such as differences in hardware performance, inconsistent operating system configuration parameters, and human error, leading to deviations in the data processing results of the primary and backup units.

[0004] To address the consistency issue between primary and backup machines, current technologies primarily employ manual inspections to randomly sample key data from both systems. However, this approach is limited by the sheer volume of data and the low efficiency of manual operations, making comprehensive and real-time consistency verification impossible. Furthermore, it struggles to generate standardized verification reports and fails to promptly identify potential consistency discrepancies, posing a threat to the stable operation of the control system. Existing verification methods suffer from low automation, narrow coverage, unintuitive result display, and lack of closed-loop management capabilities. In practical applications, the limited verification scope fails to cover critical data such as manual operations, AGC (Automatic Gauge Control), and AVC (Automatic Voltage Control), leading to the potential for missed verification of critical data. Moreover, the absence of automated alarm and reporting functions hinders maintenance personnel from quickly responding to consistency discrepancies, posing a significant threat to the stable operation of the control system. Specifically: (1) Narrow verification coverage and insufficient accuracy: Existing verification methods can only compare model data, SCADA real-time measurement data and key configuration files, and cannot cover key data such as manual operation data, custom data, AGC and AVC control parameters, which is prone to omission of key data; real-time data adopts a fixed deviation threshold comparison method without hierarchical threshold settings, and does not adopt the method of real-time library cross-section interception at the same time, which is prone to inaccurate comparison results due to the difference in data acquisition time; executable programs and dynamic libraries do not use MD5 code for accurate comparison, but only compare the full text of configuration files, which has low comparison accuracy and cannot adapt to the verification needs of different scenarios.

[0005] (2) Low level of automation and heavy maintenance burden: The existing acceptance method relies on manual labor and can only achieve semi-automation of data collection and comparison. Although the verification trigger supports simple timing, the rectification and re-verification need to be initiated manually. The verification results need to be checked line by line in the text log and the differences need to be sorted out manually, which cannot achieve full automation. There is no automated re-verification mechanism. After the rectification is completed, the verification process needs to be triggered manually again, which consumes a lot of manpower and resources, and the operation and maintenance efficiency is low, which cannot meet the needs of routine verification.

[0006] (3) The verification results are not intuitive and the risk response is delayed: The existing method outputs the verification results in the form of text logs. There is no unified front-end display interface. It is difficult for operation and maintenance personnel to quickly obtain the verification results and details of the differences. They need to check the logs line by line, which is inefficient. There is no automated alarm mechanism. For the consistency differences found, they can only be found by manually checking the logs. It is impossible to issue alarm prompts in a timely manner, which leads to a delay in risk response. Key applications such as AGC and AVC are not included in the verification scope. It is impossible to discover the consistency differences of such key applications in a timely manner and it is difficult to quickly locate the problem.

[0007] (4) Lack of standardized report generation function and poor traceability: It is impossible to automatically generate standardized verification reports. The verification results can only be stored through text logs. There is a lack of a unified recording format, making subsequent traceability and review difficult. Key information such as verification time, verification personnel, and rectification of differences are not recorded, making it impossible to form a complete verification closed-loop management. The verification results of the main and backup machines and the main and backup machines are not integrated and displayed, but are scattered in different text logs, which is not conducive to fully grasping the consistency status of the system.

[0008] (5) Unreasonable resource usage affects online services: The existing verification method reads data directly from the online real-time database of the primary and backup scheduling system, which is prone to competing with online services for real-time database resources, resulting in system lag and slow response, affecting the normal operation of the control system; and there is no offline comparison mechanism, the verification process interferes with online services, and the verification and services cannot be coordinated.

[0009] Therefore, there is an urgent need for a standardized and automated real-time cross-sectional consistency verification scheme for primary and backup machines, to streamline the consistency check scope of key applications such as AGC and AVC, and to achieve accurate verification of data across all dimensions of primary and backup machines. Summary of the Invention

[0010] To address the shortcomings of existing technologies, this invention provides a method and system for real-time cross-sectional consistency verification of the primary and backup machines in a control system, thereby solving the technical problems of narrow verification coverage, low automation, unintuitive result display, non-standard report generation, and unreasonable resource consumption in existing technologies.

[0011] To solve the above-mentioned technical problems, the present invention adopts the following technical solution.

[0012] This invention first discloses a real-time cross-sectional consistency verification system for the main and backup units of a control system, including a background verification module, a front-end display module, an alarm module, and a report generation module; The background verification module is used for the collection, interception, and multi-dimensional comparison of real-time cross-sectional data of the main and backup machines, including consistency comparison of power grid model data of the main and backup machines, consistency comparison of real-time data of SCADA application main and backup machines, consistency comparison of program version, dynamic library, configuration file, and graphic file of the main and backup machines, consistency comparison of manual operation data of SCADA application, consistency comparison of specified tables and domains of application main and backup machines, and special comparison of AGC and AVC. The front-end display module integrates all verification results of master-slave consistency verification and master-slave switching consistency verification through a unified human-computer interaction interface; displays difference details according to verification type; performs automatic verification at a fixed time every day; and allows querying of historical reports and setting of verification parameters. The alarm module periodically acquires the verification results and issues alarms for inconsistencies according to preset rules; it configures alarm suppression and sets alarm levels according to the severity of the differences; it detects AGC input data, new energy active power and command jumps in real time, and sends an alarm and switches the AGC state to locked when a jump or an abnormality in the AGC main control program is detected and automatically restarted. The report generation module automatically generates a standardized electronic report after verification is completed. The report template includes verification time, verification scope, comparison results of each module, details of differences, verification personnel information, database information set through configuration file, and report generation directory parameters. The report is stored in a specified directory, and historical reports can be queried and exported.

[0013] The present invention further includes the following preferred embodiments: The background verification module includes a model consistency verification submodule, which is used to realize the consistency comparison of the main and standby power grid model data, including the number of equipment models, key model parameters, and menus; it supports the comparison of main and standby models for specified applications and displays inconsistencies; and it enables accurate comparison of model data by setting the main and standby dispatch agent domain name, database information, and service port number parameters through the configuration file.

[0014] The background verification module includes a real-time data consistency verification submodule, which is used to realize the consistency comparison of real-time data of the SCADA application primary and backup machines, including measurement data, remote signaling data, and total measurement data; it supports offline comparison by capturing real-time database sections at the same time; it allows for custom setting of deviation thresholds for measurement data, single-point masking for remote signaling data, and cross-sectional comparison of total measurement data; and it allows specifying the telemetry and remote signaling IDs to be compared through a configuration file.

[0015] The background verification module includes a program configuration consistency verification submodule, which is used to compare the consistency of program versions, dynamic libraries, configuration files, and graphic files between the main and backup machines. The executable program and dynamic library are compared based on MD5 codes, and the configuration file adopts a full-text comparison method. The comparison directory, port number, and node information are specified through the configuration file, and the file name is filtered by substring to only display inconsistencies.

[0016] The background verification module includes a manual operation consistency verification submodule, which is used to set the domain names of the local and remote systems through the configuration file to realize the consistency comparison of manual operation data in SCADA applications, including tagging, blocking, and alarm suppression.

[0017] The background verification module includes a custom data consistency verification submodule, which is used to compare the consistency of specified tables and domains of specified application primary and backup machines according to the configuration; the verification parameters are set by table number and domain number through the configuration file, and the deviation threshold and single point masking settings are supported to adapt to different custom comparison scenario requirements.

[0018] The background verification module includes an AGC and AVC consistency verification submodule that performs a specific comparison of AGC and AVC based on a preset comparison range. It lists the AGC and AVC comparison items one by one, displays the specific values ​​of the main and backup machines, and marks the verification results as consistent or inconsistent, with inconsistent items highlighted. The AGC verification includes the comparison of control parameters, control areas, and control objects, while the AVC verification includes the comparison of control parameters, running data, number of control operations, adjustment step size, and adjustment upper and lower limits.

[0019] Accordingly, this application also discloses a terminal, including a processor and a storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the aforementioned control system primary and backup real-time cross-sectional consistency verification method.

[0020] Accordingly, this application also discloses a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the aforementioned method for real-time cross-sectional consistency verification of the main and backup control systems.

[0021] The beneficial effects of this invention are that, compared with the prior art, this invention provides a method and system for real-time cross-sectional consistency verification of the primary and backup units of a control system, which has the following advantages: (1) Improve the coverage and accuracy of verification: Achieve consistency verification of all dimensions of data, including model attributes, measurement data, remote information data, manual operation data, custom data, program configuration, AGC and AVC control parameters, without omissions; adopt real-time offline comparison of cross-sections at the same time to avoid resource contention and ensure the accuracy of comparison results; measurement data supports 6 levels of custom deviation thresholds, and AGC and AVC adopt topic-by-topic comparison, with comparison accuracy adapted to different scenarios, avoiding system failures caused by data deviations, making up for the narrow coverage of existing technologies, and ensuring that no verification is omitted.

[0022] (2) Improve automation and reduce maintenance burden: Offline comparison is performed by capturing real-time database sections at the same time to avoid occupying online business resources. The total measurement data supports custom setting of deviation thresholds. The executable program is based on MD5 code comparison. AGC and AVC are compared item by item to ensure the accuracy of the comparison results. Automatic verification is performed at fixed times every day. Manual triggering of verification is supported to realize full automation from verification triggering, data collection, comparison, alarm to report generation. There is no need to manually write scripts, manually check logs, and organize reports. Verification is completed automatically every day. Humans only need to handle differences and abnormal situations. The efficiency of operation and maintenance is significantly improved, the workload of operation and maintenance personnel is reduced, and the problems of low efficiency and easy omission of manual inspection are solved. (3) Improve response speed: The unified front-end human-machine interface integrates all verification results of the main and backup machines, displays the last verification time and difference details, and only shows the inconsistencies of the difference items (except AGC and AVC), which is intuitive and easy to understand. The inconsistencies of AGC and AVC are highlighted to facilitate quick problem location; the automated alarm mechanism ensures that the difference items are released in a timely manner, shortens the alarm response time, avoids the expansion of risks, and ensures system stability during the switchover of the main and backup machines.

[0023] (4) Report standardization: Each verification automatically generates a standardized electronic verification report, which includes complete verification information such as verification time, verification scope, details of differences, and comparison results. This facilitates subsequent tracing, review, and auditing, forming a closed-loop management of "verification-alarm-rectification-re-verification" to ensure timely rectification of consistency differences.

[0024] (5) Rationalization of resource usage: The real-time database data adopts an offline cross-sectional comparison method to avoid competing with online business for real-time database resources and ensure the normal operation of the control system; the verification program adopts a modular design, which can be started and stopped independently without affecting the overall system operation, reducing the risk of system lag and excessive load.

[0025] (6) Reduce maintenance costs: Full-process automated verification replaces manual inspection, reducing the investment of maintenance personnel. Based on the existing maintenance workload, it can reduce the maintenance hours related to main and backup machine verification, saving a lot of labor costs every year; avoids rectification costs caused by human operation errors, and reduces the total maintenance cost.

[0026] (7) Ensure the safe and stable operation of the power grid: promptly detect inconsistencies between the main and backup units, avoid data jumps, control strategy errors, system lags and other problems when the main unit fails and the backup unit is switched to the backup unit, reduce the failure rate of the control system, ensure uninterrupted power grid dispatching and monitoring services, and reduce economic losses caused by system failures.

[0027] (8) Improve the standardization of operation and maintenance: Standardized verification process, unified comparison rules and standardized report templates will realize the standardization and normalization of the main and backup machine verification work, improve the operation and maintenance management level of the power grid control system, and provide a replicable and scalable solution for subsequent verification work.

[0028] (9) Adapting to the needs of power grid development: As the scale of the power grid expands and the complexity of the control system increases, this invention can flexibly adapt to scenarios such as custom verification and special verification, and supports the customization of parameters such as deviation threshold and verification cycle. It can meet the verification needs of the long-term development of the power grid and has good scalability. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the hardware structure of the real-time cross-sectional consistency verification system of the main and backup control system in this invention.

[0030] Figure 2 This is a diagram of the main and backup machine real-time cross-sectional consistency verification system and alarm architecture of the control system in this invention.

[0031] Figure 3 This is a diagram showing the front-end interface of the real-time cross-sectional consistency verification system for the main and backup control systems in this invention.

[0032] Figure 4 This is the verification report of the real-time cross-sectional consistency verification system of the main and backup control systems in this invention.

[0033] Figure 5 This is a flowchart of the real-time cross-sectional consistency verification method for the main and backup control systems in this invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0035] The embodiments described in this application are merely some, not all, embodiments of the present invention. Based on the spirit of the present invention, other embodiments obtained by those skilled in the art without inventive effort are all within the protection scope of the present invention.

[0036] To address the shortcomings of existing technologies, this invention proposes a method and system for real-time cross-sectional consistency verification of primary and backup control systems. This method is applicable to scenarios with dual-machine redundancy configurations in smart grid dispatch and control systems. It automates, accurately verifies, and generates alarms and reports on real-time cross-sectional data such as models, real-time data, program configurations, and manual operations between the primary and backup machines, ensuring the stable and reliable operation of the control system. The real-time cross-section refers to the set of all data in the real-time database of the control system at a given moment, including models, real-time data, and configuration parameters, reflecting the current operating status of the system.

[0037] The system of this invention comprises two parts: hardware deployment and software functional modules. The hardware deployment relies on existing control system main and backup machines, source code machines, workstations, and other equipment. The software modules adopt a modular design, with each module working collaboratively to achieve fully automated verification. The specific structure is as follows: Figure 1 The diagram shows the system hardware architecture. Hardware deployment is based on the existing control system infrastructure, and programs are deployed on existing server nodes. Specific deployment nodes and requirements are shown in Table 1 below.

[0038] Table 1 The system hardware includes two application servers and two security operating systems (including agents), which are used to deploy modules such as primary and backup machine data consistency verification, custom periodic automatic verification and anomaly alarm, and core application data backup.

[0039] The software adopts a modular design, consisting of four core modules: a backend verification module, a frontend display module, an alarm module, and a report generation module, which perform the following functions: (1) Data consistency verification between primary and standby machines: Consistency verification is performed on data such as primary and standby machine models, telemetry, remote signaling, manual operation data, parameter definition data, and custom data; key information such as primary and standby machine program versions, platform key configurations, and operating system key configurations are compared; alarm rules are formulated, and alarms are issued for abnormal results. Among them, the consistency verification of real-time cross-section data between primary and standby machines is performed using the residual analysis method, and the specific calculation is as follows: Assume the host cross-sectional data is The standby section data is k represents the dimension of the cross-sectional data, and the residual sequence for the corresponding dimension is calculated. in:

[0040] Define a residual threshold ε (which can be dynamically adjusted according to the data type, such as taking 0.5% of the rated value for electrical quantities). Data consistency is determined when the following conditions are met:

[0041] (2) Custom periodic automatic verification and abnormal alarm: Set the verification period reasonably according to the data type of the consistency verification, generate consistency verification rules, trigger the execution of the consistency verification program, promptly alarm when abnormal results are found, and automatically generate a verification report with clear format, key information highlighted, and including timestamp and error details.

[0042] (3) Core application data backup: According to the defined source code machine source code, dynamic library, SCADA and other core application executable programs, basic platform configuration, table information, domain information and other important data storage locations and data storage methods, the backup is classified and backed up. The data of the most recent week is retained in a weekly cycle overwrite method, and the backup files of various types of data are transferred to the backup node.

[0043] The modules work together to achieve fully automated verification. The specific functions of each module are as follows: The background verification module is responsible for the collection, extraction, and multi-dimensional comparison of real-time cross-sectional data from the primary and backup machines. It comprises multiple sub-modules, each with independent functions and can be deployed and maintained independently. Among them: The model consistency verification submodule performs consistency comparison of power grid model data between primary and backup units, including the number of equipment models, key model parameters, menus, etc. It supports comparison of primary and backup models for specified applications. When the amount of comparison data is large, only inconsistencies are displayed to ensure intuitiveness and ease of understanding. Parameters such as the primary / backup dispatch agent domain name, database information, and service port number can be set through configuration files to achieve accurate comparison of model data.

[0044] The real-time data consistency verification submodule implements consistency comparison of real-time data from the primary and backup SCADA application machines, including measurement data, telemetry data, and total measurement data. It supports offline comparison of real-time database cross-sections captured at the same time, avoiding the occupation of online service resources. Measurement data supports customizable deviation threshold settings (6 levels of deviation thresholds can be set via configuration file), telemetry data supports single-point masking, and total measurement data supports cross-sectional comparison. The telemetry and telemetry IDs to be compared can be specified via configuration file to ensure targeted comparison. The cross-sectional comparison refers to capturing real-time cross-sectional data from the primary and backup machines at the same time and performing offline comparison to avoid competing with online services for real-time database resources and ensure accurate comparison results.

[0045] The threshold adjustment calculation method is based on the fluctuation variance of the cross-sectional data. The residual threshold ε is dynamically adjusted using the following formula:

[0046] in, The fluctuation sensitivity coefficient (range 1.5-2.5) Base threshold (set according to data type), standard deviation mean .

[0047]

[0048]

[0049] The program configuration consistency verification submodule performs consistency comparisons of program versions, dynamic libraries, configuration files, and graphical files between the primary and backup machines. Executable programs and dynamic libraries are compared based on MD5 hashes, while configuration files (including critical platform and operating system configurations) are compared using a full-text comparison method. The comparison directory, port number, and node information can be specified through the configuration file, and filename substring filtering is supported to display only inconsistencies.

[0050] The manual operation consistency verification submodule performs consistency comparisons of manual operation data in SCADA applications, including tagging, blocking, alarm suppression, and peer proxying. By configuring the local and remote system domain names in the configuration file, it enables real-time comparison of manual operation data, displaying only inconsistencies.

[0051] The custom data consistency verification submodule compares the consistency of specified tables and domains on the primary and backup machines of a specified application based on the configuration. Verification parameters can be set by table number and domain number through the configuration file, supporting deviation thresholds and single-point masking settings to adapt to different custom comparison scenarios.

[0052] The AGC and AVC consistency verification submodule performs a specific comparison of AGC and AVC based on the comparison scope outlined in the "Regulations for the Operation and Management of Dispatch Control Systems - Draft for Comments". It lists each AGC and AVC comparison item (regardless of whether they match), displays the specific values ​​of the primary and backup units, and marks the verification results as consistent or inconsistent, highlighting inconsistencies. AGC verification includes comparisons of control parameters, control areas, and controlled objects, while AVC verification includes comparisons of control parameters, operating data, control cycles, adjustment step size, and adjustment upper and lower limits, ensuring no anomalies during AGC and AVC switching.

[0053] The front-end display module provides a unified human-computer interaction interface, integrating all verification results. The interface displays the last verification time and the overall result, and is divided into two main modules: primary / standby machine consistency verification and primary / standby call consistency verification. (See [link]). Figure 3 Each module displays details of the differences (model, real-time data, program configuration, etc.) according to the verification type; it supports automatic verification at fixed times every day, manual verification can be initiated by clicking on the interface, and it supports functions such as historical report query and verification parameter setting.

[0054] The alarm module works in conjunction with the background verification module to periodically obtain verification results and issue alarms for inconsistencies according to preset rules. It supports both platform alarms and SMS alarms, and supports alarm suppression configuration, allowing alarm levels to be set according to the severity of the differences. At the same time, it monitors AGC input data, new energy active power, and command jumps in real time. When a jump is detected or the AGC main control program is automatically restarted due to an abnormality, an alarm is sent and the AGC state is switched to lockout to ensure the safe operation of AGC and AVC.

[0055] The report generation module is responsible for automatically generating a standardized electronic report after each verification. The report template is consistent with the front-end interface and includes key information such as verification time, verification scope, comparison results of each module, details of differences (device name, host value, standby value, deviation range, etc.), and verification personnel. Database information, report generation directory and other parameters are set through configuration files. The report is stored in a specified directory and supports historical report query and export, forming a closed-loop management of verification.

[0056] In a preferred embodiment, the model consistency verification submodule performs primary and backup machine model data consistency verification through the following steps: Step 1.1: Copy the source code package related to model verification to the specified node of the source code machine, decompress it, and then perform the compilation operation to complete the program compilation, ensuring that there are no compilation errors and the program can run normally; Step 1.2: Copy the compiled verification program to the program directory of the corresponding node on the primary and backup machines according to the deployment requirements, ensuring that the program version is consistent on each node; Step 1.3: On all primary and backup nodes, create a verification log storage directory, a verification result storage directory, and a configuration file storage directory respectively, and clarify the purpose of each directory to facilitate subsequent maintenance; Step 1.4: Copy the configuration file corresponding to the model verification to the configuration directory of each primary and backup node; modify the core parameters in the configuration file according to the actual primary and backup calling environment, including primary and backup calling agent information, database connection information, service port, etc., to ensure that the parameter configuration is accurate and meets the verification requirements; Step 1.5: Start the model verification module, perform basic verification operations, and confirm that the module is deployed normally and can collect model data normally. Collect model data such as the number of device models, key model parameters, and menus, perform verification, and store the verification results in the specified directory.

[0057] In a preferred embodiment, the real-time data consistency verification submodule performs real-time data consistency verification through the following steps: Step 2.1: Copy the source code package related to real-time data verification to the specified node of the source code machine, decompress it, and perform a regular compilation operation to complete the program compilation and ensure that the program can run normally; Step 2.2: Copy the compiled real-time data verification program to the program directory of the corresponding nodes of all primary and backup machines to ensure that the program is deployed completely without any omissions; Step 2.3: Copy all configuration files required for real-time data verification to the configuration directory of each primary and backup node to ensure that the configuration files match the program; Step 2.4: Based on the real-time data verification requirements, modify the core parameters in the configuration file, including the verification cycle, data deviation threshold, local and remote system information, and the list of data to be compared, and configure the default port to ensure that the parameters conform to the actual operation and maintenance scenario. Step 2.5: Start the real-time data verification module, simulate the collection of a small amount of real-time data for comparison, and confirm that the module can collect data and perform comparison operations normally. Perform consistency verification on the telemetry and telesignaling data of the SCADA application primary and backup machines, including the telemetry value, telemetry quality bit, telesignaling value, and telesignaling quality bit of the specified device, and store the verification results in the specified directory.

[0058] In a preferred embodiment, the program configuration consistency verification submodule performs program configuration consistency verification through the following steps: Step 3.1: Copy the program and configuration verification related source code packages to the specified node of the source code machine, decompress them one by one, and perform the normal compilation operation to complete the compilation of all related programs; Step 3.2: Copy all the compiled verification programs to the program directories of the corresponding nodes of all primary and backup machines to ensure that the programs on each node are deployed completely and the versions are consistent; Step 3.3: Copy the configuration files corresponding to the program comparison and system configuration comparison to the configuration directory of each primary and backup node to ensure that the configuration files cover all verification scenarios; Step 3.4: Modify the core parameters in the configuration file, including the directory range to be compared, service port, primary and backup node information, etc., set file comparison rules, and support filtering files that do not need to be compared as needed; Step 3.5: Start the program configuration verification module, select a small number of programs and configuration files for comparison testing, and confirm that the module can perform the comparison operation normally and accurately identify file differences: Comparison of program versions between primary and standby machines, including consistency comparison of program versions in the bin directory of primary and standby machine nodes and dynamic libraries in the lib directory, including platform programs and dynamic libraries, various applications and dynamic libraries, third-party programs and dynamic libraries, etc. The program versions of the primary and backup machines are compared with those of the source code machine. The consistency of the program and dynamic library versions in the bin directory and lib directory of the primary and backup machine nodes with those in the sbin and slib directories of the source code machine is compared, including platform programs and dynamic libraries, various application programs and dynamic libraries, third-party programs and dynamic libraries, etc. The platform's key configurations are compared, and the consistency of key platform configuration files in the conf directory of the primary and backup nodes is checked, including node application configurations, real-time library configurations, and communication bus configurations.

[0059] In a preferred embodiment, the manual operation consistency verification submodule performs manual operation consistency verification through the following steps: Step 4.1: Copy the source code package related to manual operation verification to the designated node of the source code machine, decompress it, and perform a regular compilation operation to complete the program compilation and ensure that the program can run normally; Step 4.2: Copy the compiled manual operation verification program to the program directory of the corresponding nodes of all primary and backup machines to ensure that the program is deployed in place; Step 4.3: Copy the configuration file corresponding to the manual operation verification to the configuration directory of each primary and backup node to ensure that the configuration file can be read by the program normally; Step 4.4: Modify the core parameters in the configuration file, including the local and remote system domain names, service ports, etc., to clarify the scope of comparison of manually operated data and ensure the accuracy of the comparison data; Step 4.5: Start the manual operation verification module, simulate a small amount of manual operation data, and test the module to collect data normally, perform comparison operations, and accurately identify differences in operation data. Apply manual operation data consistency comparison functions to SCADA, including tagging, blocking, alarm suppression, peer proxying, etc., and store the verification results in the specified directory.

[0060] In a preferred embodiment, the custom data consistency verification submodule performs custom data consistency verification through the following steps: Step 5.1: Copy the custom data verification source code package to the specified node of the source code machine, decompress it, and perform the regular compilation operation to complete the program compilation, ensuring that the program can run normally and adapt to different custom comparison scenarios; Step 5.2: Copy the compiled custom data verification program to the program directory of all primary and backup nodes to ensure that the program is deployed completely and the version is consistent on each node, so that it can work in conjunction with other verification modules; Step 5.3: Copy the core configuration file corresponding to the custom data verification to the configuration directory of each primary and backup node to ensure that the configuration file can be read by the program and matches the program parameters. Step 5.4: Modify the core parameters in the configuration file, set specific verification parameters according to table number and domain number, configure deviation threshold and single-point shielding parameters according to actual operation and maintenance needs, and clarify the application, data table and data domain to be compared to ensure the comparison is targeted. Step 5.5: Start the custom data consistency verification module, select a specified data table and data field for the specified application for comparison testing, and confirm that the module can normally collect custom data, perform comparison operations, accurately identify data differences, and adapt to custom comparison requirements. The main and backup machine parameter definition data includes a consistency comparison function for SCADA application parameter definition data, such as formula definitions and cross-section definitions. Custom data for primary and standby machines can be compared for consistency with specified tables and domains of specified applications based on the configuration. Thresholds and masking settings can be set.

[0061] In a preferred embodiment, the AGC and AVC consistency verification submodule performs AGC and AVC consistency verification through the following steps: Step 6.1: Based on the existing verification architecture, integrate the AGC and AVC verification logic to ensure that the verification module can work together with other verification modules without affecting the overall verification process; Step 6.2: Define the scope of AGC and AVC topic verification, configure a detailed comparison item list, clarify the comparison content of AGC and AVC respectively, and ensure that no key parameters are omitted; Step 6.3: Set the display rules for AGC and AVC verification results, and clarify the highlighting method for inconsistent items to facilitate maintenance personnel in quickly locating differences; Step 6.4: Confirm that the key parameters related to AVC (including the number of control cycles, adjustment step size, adjustment upper and lower limits, etc.) have been accurately written into the real-time library to ensure that relevant data can be collected normally during verification; Step 6.5: Start the AGC and AVC verification modules, perform comparison tests on the key parameters of AGC and AVC, and confirm that the modules can perform thematic verification normally and output the comparison results accurately.

[0062] See Figure 5 The fully automated verification process includes: Step 21: Configure the verification execution trigger method. One is automatic triggering, which automatically starts the verification process at a preset time (fixed time every day); the other is manual triggering, which starts the verification process immediately by clicking the manual verification button on the front-end interface. Step 22: After the verification is triggered, all verification sub-modules in the background start synchronously, and complete data collection and cross-section capture in the following manner to ensure the timeliness and integrity of the data without affecting online business: Real-time database data processing adopts a real-time database section capture method at the same time. Synchronous section capture is performed on the real-time databases of the primary and backup machines to generate offline section files. All real-time data comparisons are based on these offline files to avoid directly reading the online real-time database and prevent competition for resources with online services. Multiple data types are collected, with each sub-module in the background synchronously collecting corresponding types of data. This includes real-time collection of model data, program configuration data, manual operation data, custom data, and key parameters of AGC and AVC, ensuring consistency with the current system operating status. Invalid data is automatically filtered during the collection process to ensure the validity of the collected data.

[0063] Step 23: Each backend verification submodule performs a differential comparison on the collected primary and backup machine data according to the preset configuration, following the principles of classification comparison and accurate judgment. The specific comparison method is as follows: The model consistency verification submodule performs model consistency comparison, comparing the number of devices, key parameters, menus, etc. of the main and backup power grid models, and only displays inconsistencies to ensure that maintenance personnel can quickly locate differences. The real-time data consistency verification submodule performs real-time data consistency comparison. According to the six-level deviation threshold preset in the configuration file, it compares the measurement data, remote signaling data, and total measurement data. Remote signaling data supports single-point shielding, and total measurement data is based on offline cross-section comparison. The program configuration consistency verification submodule performs program configuration consistency comparison, including MD5 code comparison of executable programs and dynamic libraries, full-text comparison of configuration files, comparison by configured directory range, and supports file name substring filtering, only displaying inconsistencies; The manual operation consistency verification submodule performs manual operation consistency comparison, comparing manual operation data such as tagging, blocking, and alarm suppression of primary and backup machines, and only displays inconsistencies. The custom data consistency verification submodule performs custom data consistency comparison, comparing data for a specified application and a specified table domain according to the configured table number, domain number and deviation threshold, and supports single-point masking; The AGC and AVC consistency verification submodule performs AGC and AVC consistency comparison, lists all comparison items, displays the specific values ​​of the primary and backup machines, marks the consistent or inconsistent status, and highlights the inconsistent items. All comparison results (including consistent and inconsistent cases) are automatically recorded in the database, and information such as verification time and verification node are synchronously associated to provide a basis for subsequent traceability.

[0064] The alarm module implements alarms through the following steps: Step 31: The alarm module periodically (synchronized with the verification cycle) obtains all consistency inconsistencies and AGC safety verification anomaly information from the background verification module and AGC safety verification unit, automatically summarizes and organizes them, clarifies the difference type, involved nodes, anomaly details and occurrence time of each alarm, forms a standardized alarm information list, and removes duplicate alarm items. Step 32: According to the pre-set alarm rules, determine the level of each alarm message after aggregation: AGC safety verification anomalies (such as jump detection trigger, program abnormal restart) and inconsistencies in core parameters (model key parameters, AGC and AVC control parameters) are judged as high-level alarms; inconsistencies in ordinary configuration files, non-core program versions, etc. are judged as general-level alarms, and the specific level identifier of each alarm is marked. Step 33: Automatically match the corresponding alarm method according to the alarm level. High-level alarms will trigger both platform alarms and SMS alarms simultaneously to ensure that maintenance personnel are informed as soon as possible; general-level alarms will only trigger platform alarms to reduce redundancy and interference; at the same time, check the alarm suppression configuration list and automatically suppress alarms for minor inconsistencies (such as minor deviations in non-critical custom data) according to the rules, and not publish them to the public. Step 34: Platform alarms are directly pushed to the alarm zone on the front-end human-machine interface of the main workstation, highlighting high-level alarms and indicating the alarm level, anomaly details, and handling prompts; SMS alarms are automatically sent to the preset mobile phone numbers of maintenance personnel, with concise and clear content including alarm level, anomaly type, and involved nodes, so that maintenance personnel can be informed remotely.

[0065] The report generation module automatically generates standardized electronic reports through the following process: Step 41: Establish a report generation trigger mechanism. Once the entire process verification (multi-dimensional comparison, AGC safety verification) and automated alarm release are completed, the system will automatically trigger the report generation command without manual intervention. The trigger signal will be synchronously fed back to the report generation module to confirm the timing of report generation and avoid premature generation that could result in missing content. Step 42: The report generation module automatically collects the basic information required for the report from the database, including the time of this verification, the verification triggering method (automatic / manual), the verification coverage (primary and backup machines / primary and backup dispatch, various verification types), and the verification personnel information, to ensure that the basic information is complete, accurate, and consistent with the actual situation of this verification. Step 43: Automatically fill in the core content according to the preset standardized template (consistent with the front-end interface display format): sequentially enter the comparison results of each verification type (model, real-time data, program configuration, etc.), details of all inconsistencies (device name, host value, standby value, deviation range), AGC safety verification results (abnormal items / no abnormalities), alarm information (alarm level, quantity, handling status), to ensure that the content is clear and the data is accurate; Step 44: Standardize the format of the completed report, unify the font, layout and logo, clearly distinguish between consistent and inconsistent items, highlight inconsistent AGC and AVC items and AGC safety verification anomalies, add a report generation timestamp, and ensure that the report format is consistent, intuitive and easy to understand, and meets the requirements of operation and maintenance archiving and auditing. Step 45: After the report is generated, it is automatically stored in the preset report storage directory of the corresponding node and named according to "verification time-verification type" for easy retrieval; at the same time, the management and control service is linked to set access permissions for the report, which can only authorize operation and maintenance personnel to view and export the report, ensuring data security.

[0066] A specific embodiment of this application is based on a smart grid dispatch and control system. This system has deployed key applications such as SCADA, front-end, and AGC, and adopts a dual-machine redundancy configuration with primary and backup machines. The database uses DM database, and the operating system is Linux, which meets the hardware and software deployment requirements of this invention. Before implementation, the verification of the primary and backup machines of this system was carried out by manual inspection, which had problems such as incomplete verification, low efficiency, and delayed risk response. There is an urgent need to achieve automated and full-dimensional consistency verification through this invention.

[0067] First, complete the database creation and environment configuration: 1. Log in to the corresponding database client, import the relevant data files, create the necessary table structures for validation, and complete the preliminary preparations for the database.

[0068] 2. Add relevant applications in application information management, configure application running nodes, add corresponding operation menus and set core process attributes; update relevant configuration files, supplement application information and synchronize to all server nodes, and perform a restart operation to ensure the configuration takes effect.

[0069] 3. Copy the relevant runtime files and configuration files from the primary end to the corresponding directory on the secondary end to complete the deployment and configuration of the secondary end agent service.

[0070] Model Consistency Verification: This function compares the consistency of primary and backup power grid model data for a specified application. The primary and backup model data includes the number of equipment models, key model parameters, menus, etc. Verification ensures the accuracy, completeness, and validity of the model data. Before verification, the model data verification range needs to be set. Then, based on the verification range, the primary and backup model data are simultaneously acquired. Comparison is performed by traversing the same table for both primary and backup models. The primary and backup model data should meet strong consistency requirements. For any data inconsistencies that occur during verification, the results are output according to a pre-defined verification result format to ensure the accuracy, completeness, and validity of the model data.

[0071] Keyword and record count verification: This involves verifying the IDs and record data in the same table for both primary and backup systems. This includes retrieving data with the same table name from both systems, performing ID matching sequentially to identify discrepancies, and comparing the number of records in the table to determine the record count deviation. The verification scope includes standard power grid model tables such as substation tables, voltage level tables, bay tables, circuit breaker tables, disconnector tables, AC line segment tables, transformer tables, grounding disconnector tables, capacitor and reactance tables, and single-ended component tables, as well as business-defined tables such as calculation point tables and cross-section definition tables.

[0072] Equipment Attribute Verification: This function verifies the attributes of equipment in the same table for both primary and standby equipment. It primarily includes basic equipment attributes such as equipment name, dispatch number, associated substation information, voltage level, and bay name. Based on the domain information of the same equipment table for both primary and standby equipment, it compares the same domain names and outputs the differences in domain attributes one by one. The scope of equipment attribute verification includes power grid equipment such as circuit breakers, disconnectors, AC line segments, transformers, grounding disconnectors, capacitors, reactors, and single-ended components.

[0073] Nameplate parameter verification: This function verifies the nameplate parameter values ​​of devices in the main and backup machine model library. It compares parameter names based on the same device ID, and supports outputting inconsistent parameter names according to device ID. Nameplate parameter verification supports various parameters for different types of devices, including circuit breaker breaking capacity, line length, line resistance, line susceptance, long-term line current carrying capacity, short-term line current carrying capacity, transformer rated capacity, winding rated voltage, highest tap position, rated tap position, lowest tap position, tap difference, winding resistance, winding zero-sequence resistance, winding reactance, and winding zero-sequence reactance.

[0074] Real-time data consistency verification mainly includes telemetry data and remote signaling data from the SCADA application's primary and backup machines.

[0075] For telemetry data (telemetry records, telemetry values, telemetry quality bits): Record count and data quality verification are performed by sampling at the same time on the primary and backup nodes, according to configurable intervals, to obtain telemetry data for the primary and backup sequences. The number of telemetry records should maintain strong consistency. During verification, the configured number of telemetry records is first verified, and the record count deviation result is output. Telemetry data quality represents data acquisition quality and device status. The quality bit, defined through a menu, supports comparison of the final quality menu result combination values ​​for options such as acquisition anomaly, non-measured, flagged, blocked, alarm suppression, uninitialized, peer replacement, and normal, outputting the quality deviation result.

[0076] For remote signaling data (remote signaling records, remote signaling values, and remote signaling quality bits): a comprehensive comparison should be made considering the situation of remote signaling changes. That is, the comparison should be made in conjunction with the recent remote signaling change alarms. Due to its data characteristics, the remote signaling data of the primary and backup machines should maintain strong consistency under normal circumstances. Before verification, the table fields involved in the verification should be clearly defined (which can be configured through the configuration file). In particular, certain fields can be single-point shielded.

[0077] Next, we will perform consistency checks on the program versions, platforms, and key configurations of the operating systems of the primary and backup machines and the source code machine.

[0078] Primary and backup machine program version comparison: Executable program verification is performed by comparing the size, last modification time and MD5 code of the same program on the primary and backup machines, covering basic platform service programs, application resident processes and other ranges. Dynamic library version verification: By traversing and obtaining dynamic library files from the primary and backup machines, and comparing them based on files with the same name, this involves types such as operating system basic dynamic libraries and application-generated dynamic libraries. It verifies version differences for key modules such as system management, real-time libraries, and middleware services.

[0079] Based on the comparison of the program versions of the primary and backup machines and the source code machine, the executable programs and dynamic libraries of the primary and backup machine nodes are further compared with the corresponding files in the slib and sbin directories of the source code machine to identify version differences between the running nodes and the source code nodes, ensuring system stability and reliability.

[0080] Platform critical configuration comparison: For configuration files of core components such as application management and real-time libraries in the conf directory of the primary and backup nodes, the configuration information is obtained, parsed, and sent to the comparison node via the service bus framework for consistency verification. Differences in configuration files are logged and alerts are sent to prevent application malfunctions caused by configuration differences. Operating system critical configuration comparison focuses on core parameters such as the maximum number of threads, the maximum number of file descriptors, and TCP / UDP buffers. Parameter values ​​are obtained by executing system commands such as `limit` and parsing configuration files such as ` / etc / sysctl.conf` to determine if they are within reasonable ranges. Unreasonable configurations are logged and alerts are sent to optimize operating system performance and improve the overall system stability and reliability.

[0081] In the manual operation consistency verification, manual operation records from both the primary and backup ends are collected in real time, including key information such as operation type (tag, block, alarm suppression, peer proxy), operation time, operation content, and operation result. The operation records are time-synchronized and calibrated to ensure consistency in the comparison time dimension. The operation records from the primary and backup ends are matched and compared one by one according to the operation time sequence, with a focus on comparing the consistency of operation content and operation result. If there are inconsistencies in operation content or asynchronous operation results (successful operation on the primary end, failed operation on the backup end, or not executed), they are marked as inconsistencies, the operation details are recorded, and an operation comparison log is formed to complete the module deployment and process debugging.

[0082] In the custom parameter consistency verification, the system automatically reads the custom parameter configuration information (formula definition, section definition, specified table, specified threshold, etc.) from both the primary and backup ends according to a preset comparison frequency. The collected parameters are standardized and parsed to unify the parameter format and units. A combination of precise comparison and fuzzy comparison is used to compare the parameter values ​​of both the primary and backup ends one by one according to the custom parameter list. For numerical parameters, it is determined whether they are within the preset precision range, and for character parameters, a complete match comparison is performed. During the comparison process, the parameter comparison details are recorded in real time, and the names, primary end values, backup end values, and difference types of inconsistent parameters are marked to form a custom parameter comparison log. This log is then pushed synchronously to the front-end display and alarm module to complete the module deployment and process debugging.

[0083] In the consistency verification of AGC and AVC, the verification logic of AGC and AVC is integrated, and the specific comparison parameters and comparison item list are clearly defined. The AGC comparison items include control parameters (adjustment coefficient, response threshold, control mode, etc.), control area division, and control object list. The AVC comparison items include control parameters (voltage threshold, reactive power adjustment step size, etc.), real-time operating data (voltage, reactive power, etc.), and control frequency statistics. Inconsistency item display parameters are set, including highlighting inconsistencies, grading (severe, moderate, minor), and detailed remarks rules. It is confirmed that the relevant control parameters of AGC and AVC have been completely entered into the real-time database and can be read normally by the verification module.

[0084] Regularly collect AGC and AVC control parameters and operating data from both the primary and backup ends, and compare them one by one according to the comparison item list. The control parameters adopt the precise comparison method, the operating data adopts the interval comparison method, and the control times adopt the numerical consistency comparison method. After the comparison is completed, the inconsistencies are classified and sorted according to their severity, and pushed to the front-end display module and alarm module simultaneously to complete the deployment, configuration and process debugging of the modules.

[0085] The fully automated verification process includes: ① Configure automated verification parameters: Define the verification coverage (all backend verification modules), set the verification triggering method (automatic triggering on a set time, triggering in response to an anomaly), configure the timed triggering period (matching the verification period of each module to ensure collaborative verification), and the anomaly triggering rules (automatically triggering full-process review and verification when an anomaly occurs in a certain module).

[0086] ② Configure an automated data acquisition and transmission mechanism: Configure the data reporting path and reporting frequency for each module to ensure that information such as background verification results and device operating status can be automatically stored to the specified path.

[0087] The automated alarm release further includes: formulating and configuring alarm classification rules, clarifying the alarm methods for different types of differences, automated verification anomalies, and AGC security anomalies; setting alarm suppression conditions to avoid repeated alarms; configuring relevant anomaly detection thresholds and corresponding handling logic, linking the entire process automated verification system, ensuring that automatically triggered alarms can be pushed in a timely manner, and completing the alarm module configuration.

[0088] The standardized report generation further includes: copying relevant compressed files to the corresponding directory of the specified node, decompressing them, modifying the configuration file, and improving key parameters such as database connection and report storage path; adding a fully automated verification report generation function, supporting automatic report generation, archiving, and export, and linking with the automated verification system to synchronously acquire verification data and generate a complete report. See [link to documentation]. Figure 4Start the report generation and management services, restart the relevant bus services to ensure the configuration takes effect; set the automatic verification time, start the automatic verification script, and complete the module deployment.

[0089] The beneficial effects of this invention are that, compared with the prior art, this invention provides a method and system for real-time cross-sectional consistency verification of the primary and backup units of a control system, which has the following advantages: (1) Improve the coverage and accuracy of verification: Achieve consistency verification of all dimensions of data, including model attributes, measurement data, remote information data, manual operation data, custom data, program configuration, AGC and AVC control parameters, without omissions; adopt real-time offline comparison of cross-sections at the same time to avoid resource contention and ensure the accuracy of comparison results; measurement data supports 6 levels of custom deviation thresholds, and AGC and AVC adopt topic-by-topic comparison, with comparison accuracy adapted to different scenarios, avoiding system failures caused by data deviations, making up for the narrow coverage of existing technologies, and ensuring that no verification is omitted.

[0090] (2) Improve automation and reduce maintenance burden: Offline comparison is performed by capturing real-time database sections at the same time to avoid occupying online business resources. The total measurement data supports custom setting of deviation thresholds. The executable program is based on MD5 code comparison. AGC and AVC are compared item by item to ensure the accuracy of the comparison results. Automatic verification is performed at fixed times every day. Manual triggering of verification is supported to realize full automation from verification triggering, data collection, comparison, alarm to report generation. There is no need to manually write scripts, manually check logs, and organize reports. Verification is completed automatically every day. Humans only need to handle differences and abnormal situations. The efficiency of operation and maintenance is significantly improved, the workload of operation and maintenance personnel is reduced, and the problems of low efficiency and easy omission of manual inspection are solved. (3) Improve response speed: The unified front-end human-machine interface integrates all verification results of the main and backup machines, displays the last verification time and difference details, and only shows the inconsistencies of the difference items (except AGC and AVC), which is intuitive and easy to understand. The inconsistencies of AGC and AVC are highlighted to facilitate quick problem location; the automated alarm mechanism ensures that the difference items are released in a timely manner, shortens the alarm response time, avoids the expansion of risks, and ensures system stability during the switchover of the main and backup machines.

[0091] (4) Report standardization: Each verification automatically generates a standardized electronic verification report, which includes complete verification information such as verification time, verification scope, details of differences, and comparison results. This facilitates subsequent tracing, review, and auditing, forming a closed-loop management of "verification-alarm-rectification-re-verification" to ensure timely rectification of consistency differences.

[0092] (5) Rationalization of resource usage: The real-time database data adopts an offline cross-sectional comparison method to avoid competing with online business for real-time database resources and ensure the normal operation of the control system; the verification program adopts a modular design, which can be started and stopped independently without affecting the overall system operation, reducing the risk of system lag and excessive load.

[0093] (6) Reduce maintenance costs: Full-process automated verification replaces manual inspection, reducing the investment of maintenance personnel. Based on the existing maintenance workload, it can reduce the maintenance hours related to main and backup machine verification, saving a lot of labor costs every year; avoids rectification costs caused by human operation errors, and reduces the total maintenance cost.

[0094] (7) Ensure the safe and stable operation of the power grid: promptly detect inconsistencies between the main and backup units, avoid data jumps, control strategy errors, system lags and other problems when the main unit fails and the backup unit is switched to the backup unit, reduce the failure rate of the control system, ensure uninterrupted power grid dispatching and monitoring services, and reduce economic losses caused by system failures.

[0095] (8) Improve the standardization of operation and maintenance: Standardized verification process, unified comparison rules and standardized report templates will realize the standardization and normalization of the main and backup machine verification work, improve the operation and maintenance management level of the power grid control system, and provide a replicable and scalable solution for subsequent verification work.

[0096] (9) Adapting to the needs of power grid development: As the scale of the power grid expands and the complexity of the control system increases, this invention can flexibly adapt to scenarios such as custom verification and special verification, and supports the customization of parameters such as deviation threshold and verification cycle. It can meet the verification needs of the long-term development of the power grid and has good scalability.

[0097] Based on the spirit of this invention, those skilled in the art will readily conceive of obtaining a computer program product based on the aforementioned method for real-time cross-sectional consistency verification of the primary and backup control systems. The computer program product may include a computer-readable storage medium on which computer-readable program instructions are loaded to enable a processor to implement various aspects of this disclosure. That is, this application also includes a terminal comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps according to the aforementioned method for real-time cross-sectional consistency verification of the primary and backup control systems.

[0098] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0099] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0100] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A real-time cross-sectional consistency verification system for primary and backup control systems, characterized in that, It includes a backend verification module, a frontend display module, an alarm module, and a report generation module; The background verification module is used for the collection, interception, and multi-dimensional comparison of real-time cross-sectional data of the main and backup machines, including consistency comparison of power grid model data of the main and backup machines, consistency comparison of real-time data of SCADA application main and backup machines, consistency comparison of program version, dynamic library, configuration file, and graphic file of the main and backup machines, consistency comparison of manual operation data of SCADA application, consistency comparison of specified tables and domains of application main and backup machines, and special comparison of AGC and AVC. The front-end display module integrates all verification results of master-slave consistency verification and master-slave switching consistency verification through a unified human-computer interaction interface. Displays difference details by verification type; automatic verification at fixed times every day; historical report query; and verification parameter settings. The alarm module periodically acquires the verification results and issues alarms for inconsistencies according to preset rules. Configure alarm suppression and set alarm levels according to the severity of differences; monitor AGC input data, new energy active power and command jumps in real time; when a jump is detected or the AGC main control program is automatically pulled up due to an abnormality, send an alarm and switch the AGC status to lockout. The report generation module automatically generates a standardized electronic report after verification is completed. The report template includes verification time, verification scope, comparison results of each module, details of differences, verification personnel information, database information set through configuration file, and report generation directory parameters. The report is stored in a specified directory, and historical reports can be queried and exported.

2. The real-time cross-sectional consistency verification system for the main and backup control systems according to claim 1, characterized in that, The background verification module includes a model consistency verification submodule, which is used to realize the consistency comparison of the main and standby power grid model data, including the number of equipment models, key model parameters, and menus; it supports the comparison of main and standby models for specified applications and displays inconsistencies; and it enables accurate comparison of model data by setting the main and standby dispatch agent domain name, database information, and service port number parameters through the configuration file.

3. The real-time cross-sectional consistency verification system for the main and backup units of the control system according to claim 2, characterized in that, The background verification module includes a real-time data consistency verification submodule, which is used to realize the consistency comparison of real-time data of the SCADA application primary and backup machines, including measurement data, remote signaling data, and total measurement data; it supports offline comparison by capturing real-time database sections at the same time; it allows for custom setting of deviation thresholds for measurement data, single-point masking for remote signaling data, and cross-sectional comparison of total measurement data; and it allows specifying the telemetry and remote signaling IDs to be compared through a configuration file.

4. The real-time cross-sectional consistency verification system for the main and backup units of the control system according to claim 3, characterized in that, The background verification module includes a program configuration consistency verification submodule, which is used to compare the consistency of program versions, dynamic libraries, configuration files, and graphic files between the main and backup machines. The executable program and dynamic library are compared based on MD5 codes, and the configuration file adopts a full-text comparison method. The comparison directory, port number, and node information are specified through the configuration file, and the file name is filtered by substring to only display inconsistencies.

5. The real-time cross-sectional consistency verification system for the main and backup units of the control system according to claim 4, characterized in that, The background verification module includes a manual operation consistency verification submodule, which is used to set the domain names of the local and remote systems through the configuration file to realize the consistency comparison of manual operation data in SCADA applications, including tagging, blocking, and alarm suppression.

6. The real-time cross-sectional consistency verification system for the main and backup units of the control system according to claim 5, characterized in that, The background verification module includes a custom data consistency verification submodule, which is used to compare the consistency of specified tables and domains of specified application primary and backup machines according to the configuration; the verification parameters are set by table number and domain number through the configuration file, and the deviation threshold and single point masking settings are supported to adapt to different custom comparison scenario requirements.

7. The real-time cross-sectional consistency verification system for the main and backup units of the control system according to claim 6, characterized in that, The background verification module includes an AGC and AVC consistency verification submodule that performs a specific comparison of AGC and AVC based on a preset comparison range. It lists the AGC and AVC comparison items one by one, displays the specific values ​​of the main and backup machines, and marks the verification results as consistent or inconsistent, with inconsistent items highlighted. The AGC verification includes the comparison of control parameters, control areas, and control objects, while the AVC verification includes the comparison of control parameters, running data, number of control operations, adjustment step size, and adjustment upper and lower limits.

8. A method for verifying the real-time cross-sectional consistency of a control system's primary and backup units in any one of claims 1-7, characterized in that, Includes the following steps: The system collects, extracts, and performs multi-dimensional comparisons of real-time cross-sectional data from the main and backup machines, including consistency comparisons of power grid model data, real-time data from the main and backup machines for SCADA applications, consistency comparisons of program versions, dynamic libraries, configuration files, and graphic files from the main and backup machines, consistency comparisons of manual operation data from SCADA applications, consistency comparisons of specified tables and domains from the main and backup machines, and specific comparisons of AGC and AVC. The system integrates all verification results of primary and backup machine consistency verification and primary and backup dispatch consistency verification through a unified human-computer interaction interface, and displays the difference details according to the verification type; it automatically performs verification at a fixed time every day, and receives users' historical report queries and verification parameter settings; Periodically obtain verification results and issue alarms for inconsistencies according to preset rules; Configure alarm suppression and set alarm levels according to the severity of differences; monitor AGC input data, new energy active power and command jumps in real time; when a jump is detected or the AGC main control program is automatically pulled up due to an abnormality, send an alarm and switch the AGC status to lockout. A standardized electronic report is automatically generated after verification. The report template includes verification time, verification scope, comparison results of each module, details of differences, verification personnel information, database information settings through configuration files, report generation directory parameters, and stores the report in a specified directory. Historical reports can be queried and exported.

9. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the real-time cross-sectional consistency verification method for the main and backup units of the control system according to claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the real-time cross-sectional consistency verification method for the main and backup units of the control system as described in claim 8.

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