Protection setting value intelligent comparison method and system

Abstract

The invention discloses a protection setting value intelligent comparison method and system, and relates to the technical field of power protection setting value check, and the method comprises the steps: carrying out the first analysis of a file format, and storing the file format in a database; acquiring real-time data, and performing first comparison on the data; and visualizing the comparison result and automatically generating a check report. According to the protection setting value intelligent comparison method provided by the invention, the electronic setting value sheets in various formats are automatically imported and analyzed, and the data are stored in a standardized manner, so that the processing efficiency and accuracy of the setting value sheet data are improved, the operation setting value data of the protection device are obtained in real time and are integrated into a setting value checking system database, and the safety of the protection device is improved. According to the method, the synchronization of the operation data and the scheduling data is improved, the scheduling issuing fixed value and the operation fixed value are compared item by item by adopting an automatic algorithm, the efficiency and the accuracy of the fixed value checking work are improved, and better effects are achieved in the aspects of accuracy, synchronism and efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of electric power protection setting verification, and in particular to a protection setting intelligent comparison method. Background Art

[0002] With the continuous expansion of the scale of power systems and the continuous improvement of their intelligence levels, the setting management of power protection devices has become an important part of ensuring the safe and stable operation of power systems. Traditional setting verification methods mostly rely on manual verification and paper ledger records. This method can still meet the needs in the early stages of power system operation. However, with the increasing complexity of power grids and the rapid increase in the types and numbers of power equipment, the efficiency and reliability of manual setting verification have gradually been challenged. In recent years, with the development of intelligent operation and maintenance technology, setting verification technology based on informatization and automation has gradually been applied to the power industry. For example, some setting verification systems have introduced functions such as electronic setting sheet management and data comparison, trying to improve work efficiency through informatization. However, these technical solutions are currently limited to single tasks or specific equipment, and cannot achieve widely applicable and efficient setting verification management for the entire network.

[0003] Although the existing technology has improved the efficiency of fixed value verification to a certain extent, there are still many problems that limit its further promotion and application. First, the existing electronic fixed value sheet management system has poor compatibility with various file formats (such as PDF, Word, Excel, etc.), resulting in low efficiency in fixed value sheet parsing, prone to data loss or errors, and unable to meet the needs of diversified equipment models in the power system. Secondly, the comparison process between fixed values ​​and operating data is mostly semi-automatic operation, which requires manual intervention to complete difference analysis and problem troubleshooting. It is not only inefficient, but also easily affected by human factors, resulting in inconsistency in comparison results. In addition, the existing system lacks flexibility in the comparison scope and cannot support rapid comparison and customized analysis of the entire station equipment, which seriously restricts the applicability of the system. More importantly, the existing technology lacks perfect data traceability and management capabilities, and the version records of historical fixed values ​​and the traceability of comparison results are insufficient, which makes it difficult for operation and maintenance personnel to quickly locate problems and formulate adjustment plans. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: the existing set value comparison method has insufficient compatibility with multi-format electronic set value sheets, low level of automation in the set value and operating data comparison process, lack of flexible comparison range and data traceability, and how to achieve optimization of efficient, accurate and intelligent set value verification.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a protection constant intelligent comparison method, comprising a first analysis of the file format and storing it in a database; obtaining real-time data and performing a first comparison on the data; visualizing the comparison results and automatically generating a verification report.

[0007] As a preferred solution of the protection constant value intelligent comparison method described in the present invention, wherein: the first parsing of the file format includes classification according to field identifiers.

[0008] As a preferred solution of the protection constant value intelligent comparison method described in the present invention, wherein: the storing in the database includes storing the parsed data in the database.

[0009] As a preferred solution of the protection setting intelligent comparison method described in the present invention, the acquisition of real-time data includes acquiring real-time device operation data.

[0010] As a preferred solution of the protection constant value intelligent comparison method described in the present invention, wherein: the first comparison of data includes identifying inconsistent items.

[0011] As a preferred solution of the protection setting value intelligent comparison method described in the present invention, wherein: the visual comparison result includes a dynamic visual comparison result.

[0012] As a preferred solution of the protection setting intelligent comparison method described in the present invention, the automatic generation of the verification report includes generating and exporting the verification report based on the comparison results.

[0013] Another object of the present invention is to provide an intelligent comparison system for protection set values, which can collect operating set value data in real time through a collection and comparison module, and compare it item by item with the existing set value list issued by the dispatcher, thereby solving the current problems of low comparison efficiency and limited comparison scope.

[0014] As a preferred solution of the protection constant value intelligent comparison system described in the present invention, it includes: a parsing and storage module, a collection and comparison module, and a visualization generation module; the parsing and storage module is used to perform a first analysis of the file format and store it in a database; the collection and comparison module is used to obtain real-time data and perform a first comparison on the data; the visualization generation module is used to visualize the comparison results and automatically generate a verification report.

[0015] A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that the processor executes the computer program to implement a step of a protection constant value intelligent comparison method.

[0016] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a protection constant value intelligent comparison method are implemented.

[0017] Beneficial effects of the present invention: The protection set value intelligent comparison method provided by the present invention automatically imports and parses electronic set value sheets in various formats, and stores the data in a standardized manner, thereby improving the efficiency and accuracy of set value sheet data processing, acquiring the operating set value data of the protection device in real time, and integrating it into the set value verification system database, thereby improving the synchronization of operating data and dispatching data, and using an automated algorithm to compare the dispatched set values ​​with the operating set values ​​item by item, thereby improving the efficiency and accuracy of the set value verification work, and the comparison results are intuitively displayed in the form of charts and lists, thereby enhancing the transparency and professionalism of the set value verification. The present invention achieves better results in terms of accuracy, synchronization and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0019] Figure 1 This is an overall flow chart of the protection setting intelligent comparison method provided for the first and second embodiments of the present invention.

[0020] Figure 2 This is an overall module diagram of the protection setting intelligent comparison system provided for the fourth embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0022] Example 1

[0023] Reference Figure 1 , which is an embodiment of the present invention, provides a protection setting value intelligent comparison method, including:

[0024] S1: Perform a first analysis on the file format and store it in a database.

[0025] Furthermore, the first parsing of the file format includes classifying according to field identifiers.

[0026] In the embodiment of the present application, the first analysis is a multi-format file analysis, and the electronic value order analysis function of the system supports multiple file formats, including Excel, Word, PDF and XML;

[0027] For Excel format, the method of reading row by row is adopted to distinguish the fixed value item, fixed value range and description information through the specific identification of each cell, and the information is accurately extracted and stored in the memory;

[0028] For Word documents, read them in paragraphs, use spaces or other specific separators to separate the contents, and determine their logical attribution by comparing the key fields in the first column (such as serial numbers or names of fixed value items) to avoid data confusion caused by header grouping or page breaks.

[0029] For PDF format, due to the problem of line breaks or merged cells, advanced processing tools such as Spire are used to analyze and reorganize cross-line content line by line to ensure data integrity;

[0030] The parsing of XML files is based on the SAXReader framework. It obtains node information by traversing layer by layer, and accurately extracts key fields such as constant value group, constant value description and constant value range according to the attribute name. After the parsing is completed, the data is preliminarily verified, including field matching and data format verification.

[0031] In an optional embodiment, the first analysis can also be implemented in other ways, such as semantic analysis based on artificial intelligence, through natural language processing technology, semantic analysis of the text content in the value list is performed to convert complex text information into structured data;

[0032] Convert the input value sheet file into plain text format. For PDF files, use optical character recognition technology to extract text. For Word and Excel files, call the corresponding reading interface to extract content. The extracted text is divided into logical paragraphs by a block algorithm for subsequent segment-by-segment analysis. The blocks are recognized based on common structural features of the value sheet (such as headers, paragraph titles, keywords, etc.);

[0033] Use the semantic parsing model to parse each paragraph of text sentence by sentence. Use entity recognition technology to locate fields such as the name of the fixed value item and the new fixed value, and use the contextual relationship to determine the specific value of the field. For example, in the line "Low-cycle load shedding delay: 0.3 seconds", identify "Low-cycle load shedding delay" as the fixed value item name, "0.3" as the fixed value, and extract "seconds" as the unit field. For data with nested relationships (such as multiple rows of fixed value items under the group header), use dependency syntax analysis to disassemble the nested structure into separate fixed value items.

[0034] According to the semantic rule base, the extracted fields are mapped with the corresponding equipment information, set value range and other contents. For example, if the set value list mentions "protection device model: PCS-915A", the default set value range value under this model is automatically completed. For missing fields, the system will generate prompt information and infer possible values ​​based on the context.

[0035] Furthermore, storing in a database includes storing the parsed data in a database.

[0036] It should be noted that the parsed electronic value sheet data is automatically stored in the background database, and a unified value ledger management system is built to assign a unique number to each value sheet to ensure the traceability of different versions of value sheet data and avoid confusion and conflict. The value data undergoes strict standardization before storage, including unit conversion, abnormal character filtering and logical consistency verification. The system automatically standardizes the time value (such as seconds and milliseconds) or value range (such as percentage and actual value) in the value sheet to ensure that the data in different formats of value sheets can be compared and analyzed under the same framework;

[0037] The system supports dynamic association with equipment operation data, and automatically matches and associates the fields such as the equipment name, model and version number of the setting sheet with the real-time data of the operating protection device, forming a one-to-one or many-to-one mapping relationship of "setting sheet-equipment operation data". The database can be expanded to support different types of protection equipment and newly added data fields to meet the ever-changing needs of the power grid operation and maintenance system. At the same time, the system provides data update and version control functions to ensure that users can view historical setting sheets at any time and trace their comparison records, forming a complete closed loop from data collection to storage management.

[0038] S2: Acquire real-time data and perform a first comparison on the data.

[0039] Furthermore, acquiring real-time data includes acquiring real-time device operation data.

[0040] It should be noted that the acquisition of real-time device operation data is achieved through the Restful interface with the secondary remote operation and maintenance platform. The acquired data covers multi-level information such as plant information, device information, primary equipment parameters and fixed value templates;

[0041] Through the plant information interface, the plant ID is used as a parameter to obtain the basic information of the plant, including the plant name, voltage level, and communication protocol type;

[0042] Through the device information interface, obtain the real-time operation data of all devices under the specified plant, including device model, operation status and real-time values ​​of built-in fixed value items of the device;

[0043] Call the primary device information interface to obtain the primary device information associated with the device, such as device name, voltage level, and device type;

[0044] Through the fixed value template interface, the fixed value template data of the specified device is obtained. These templates contain the fixed value item range, numerical unit and default value. All the obtained data are uniformly stored in the comparison database after internal preprocessing of the system, and mapping relationships are established for different plants, devices and fixed value items.

[0045] Furthermore, performing a first comparison on the data includes identifying inconsistent items.

[0046] In the embodiment of the present application, the first comparison is a dynamic fixed value intelligent comparison, which compares the stock fixed value list with the real-time operation data item by item, uses the fixed value list data in the database to match the fields with the real-time operation data, and matches each fixed value item in the fixed value list with the operation data one by one according to key attributes such as the fixed value description, equipment name and fixed value item range, performs a preliminary screening of the operation data according to the range value of the fixed value item, marks abnormal data items that exceed the preset range, and designs specific comparison logic for different data types;

[0047] For numerical data, automatic unit conversion is supported (such as conversion between milliseconds and seconds) to ensure direct comparability of data in different units. For character data, such as device names or protection models, fuzzy matching algorithms are used to handle existing character encoding or format differences. User-defined comparison rules are supported. For example, some fixed value items allow a certain range of deviations. The system will re-mark whether they are consistent based on the deviation range set by the user. After the comparison is completed, the system highlights the inconsistent items and supports cause analysis and manual intervention of these data, such as choosing to ignore verification or manual adjustment.

[0048] In an optional embodiment, the first comparison can also be implemented in other ways, such as comparing fixed values ​​based on a machine learning algorithm. By learning historical fixed value data, operating data and related equipment information, the model summarizes the reasonable range and standard mode of fixed values ​​under different equipment and scenarios, and compares the real-time operating data with the standard mode predicted by the model to detect abnormal items and deviation points.

[0049] Extract key features, such as the upper and lower limits, average values, fluctuation ranges of fixed value items, and correlations with other variables, such as the relationship between voltage levels and protection device models. Use training data (historical fixed value sheets and operating data) to build a machine learning model. The model uses multi-dimensional features as input to generate standard patterns for each type of equipment or fixed value item. For example, for the fixed value item of "low-frequency load shedding delay", the model will generate a reasonable range based on the equipment model, plant environment, and grid operation parameters.

[0050] In the comparison phase, the real-time operation data is input into the trained model to calculate the outlier score of each fixed value item (for example, through z-score or Mahalanobis distance). When the score of a fixed value item exceeds the threshold, the item is marked as abnormal. For example, if the "low-cycle load shedding delay" of a device is 0.5 seconds, and the reasonable range predicted by the model is 0.2 seconds to 0.4 seconds, the value is considered abnormal and an alarm is issued.

[0051] The comparison results are classified into consistent, inconsistent (deviation out of range) and abnormal (caused by equipment failure or data error). For inconsistent and abnormal items, the system automatically generates a cause analysis, such as variable combinations that exceed a reasonable range or mutation points compared with historical data. Users can further filter these items and manually confirm or adjust them. Users are supported to provide feedback on the comparison results, such as marking certain deviations as reasonable or unreasonable. Through these feedback data, the model updates itself and gradually optimizes the accuracy of the standard model.

[0052] Example 2

[0053] Reference Figure 1 , which is an embodiment of the present invention, provides a protection setting value intelligent comparison method, including:

[0054] S3: Visualize the comparison results and automatically generate a verification report.

[0055] Furthermore, the visualized comparison results include dynamic visualized comparison results.

[0056] It should be noted that an intuitive dynamic visualization display function is provided for the comparison results to help users quickly understand the overall situation of the fixed value comparison and the specific differences. The comparison results are presented in the form of charts and lists, and data highlighting is used to distinguish consistent items, inconsistent items and ignored comparison items, so that users can quickly locate problems;

[0057] The system supports data traceability and historical record management. After each comparison is completed, the comparison result will be automatically bound to the fixed value sheet number and stored in the database to ensure that users can retrieve historical records at any time. The historical data traceability function supports comparative analysis of fixed value sheet versions. Users can view the specific differences between a certain version of a fixed value sheet and its subsequent versions, and quickly locate the reasons for the modifications. This function is particularly suitable for analyzing the long-term operating status of equipment and optimizing fixed value parameters. In addition, the system can record user intervention operations on specific items during the comparison process (such as ignoring the comparison or modifying the fixed value range).

[0058] Furthermore, automatically generating a verification report includes generating and exporting the verification report according to the comparison result.

[0059] It should be noted that after completing the comparison, the system automatically generates a standardized verification report that comprehensively displays the comparison results and analysis conclusions. The verification report includes comparison statistics, a list of inconsistent items, difference analysis, and cause of problems. It also supports user customization options. Users can choose to export only the detailed information of inconsistent items, or export the complete comparison process data.

[0060] The report generation process is based on a templated design and can be flexibly adapted to a variety of scenarios. For the comparison of the entire station equipment, a comprehensive report covering the comparison results of all equipment values ​​is automatically generated, and statistical charts (such as consistency rate, distribution of major problems, etc.) are attached to help users quickly understand the operating status of the entire station equipment. For the comparison of a single device, the report focuses on the inconsistencies and their impact analysis, which facilitates equipment maintenance personnel to quickly take corrective measures. The system supports exporting reports to common file formats such as PDF and Excel. Users can distribute reports to different departments or upload them to other system platforms as needed.

[0061] Example 3

[0062] An embodiment of the present invention provides a protection setting intelligent comparison method. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0063] The experiment selected equipment from six different sites as test objects, including sites A, B, C, D, E and F, covering a variety of equipment models, data sources and environmental conditions. During the experimental preparation stage, the real-time operation data of all sites were first obtained from the secondary remote operation and maintenance platform, the protection device settings were extracted, and standardized electronic setting sheets were generated in Excel, Word, PDF and XML formats. Secondly, the historical setting sheets issued by the dispatcher and the actual operating settings were imported into the system for intelligent comparison.

[0064] During the test, the system analyzes the set value sheet, collects and compares the running set value data for the equipment at each site in turn. The system automatically parses electronic set value sheets in various formats, extracts the set value items, range values ​​and equipment parameters, and stores them in the database. The compatibility indicators are recorded during the analysis process to evaluate the multi-format support performance. The system compares the scheduling set value and the real-time running set value item by item, highlights the abnormal items, and generates an inconsistency report. The comparison accuracy is calculated by comparing the consistency between the actual marked abnormal items and the system detection results. After the comparison of each site is completed, the system generates a complete calibration report showing the calibration coverage of the equipment, details of the inconsistencies and correction suggestions. After the test, the operational stability of the system is evaluated throughout the process, including the frequency of no response or errors.

[0065] As shown in Table 1, the format compatibility rate of the fixed value sheet in the six site devices is more than 90%, indicating that the method of the present invention can efficiently process electronic fixed value sheets of different formats, which is superior to the limitation of the single format processing capability in the prior art. Secondly, the comparison accuracy is maintained at more than 96% in the six sites, and the highest reaches 99%, indicating that the method of the present invention achieves high-precision comparison through intelligent algorithms and reduces the influence of human factors on the comparison results. In terms of the detection rate of abnormal items, the detection rate of the method of the present invention is higher than 84%, which improves the recognition ability of abnormal items, especially in complex data environments. It still maintains a high detection level. The average data processing speed is 2.25 seconds per thousand, which is better than the efficiency of manual or semi-automatic processing of existing methods, and can meet the needs of rapid verification of large-scale data. The verification coverage rate is above 95%, among which sites A and D achieve 100% full coverage, further verifying the applicability and reliability of the method of the present invention in the verification task of the entire site.

[0066] Table 1 Experimental data table

[0067]

[0068] Example 4

[0069] Reference Figure 2 , which is an embodiment of the present invention, provides a protection fixed value intelligent comparison system, including: an analysis and storage module, a collection and comparison module, and a visualization generation module.

[0070] The parsing and storage module is used to perform a first analysis of the file format and store it in a database; the acquisition and comparison module is used to obtain real-time data and perform a first comparison of the data; and the visualization generation module is used to visualize the comparison results and automatically generate a verification report.

[0071] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0072] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0073] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0074] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0075] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. The protection setting value intelligent comparison method is characterized by: include: Perform the first analysis on the file format and store it in the database; Obtain real-time data and make a first comparison of the data; Visualize the comparison results and automatically generate a calibration report.

2. The protection setting value intelligent comparison method according to claim 1, characterized in that: The first parsing of the file format includes classifying according to field identifiers.

3. The protection setting value intelligent comparison method according to claim 2, characterized in that: The storing in the database includes storing the parsed data in the database.

4. The protection setting value intelligent comparison method according to claim 3 is characterized in that: The acquiring of real-time data includes acquiring real-time device operation data.

5. The protection setting value intelligent comparison method according to claim 4, characterized in that: The first comparing of the data includes identifying inconsistencies.

6. The protection setting value intelligent comparison method according to claim 5, characterized in that: The visualized comparison results include dynamic visualized comparison results.

7. The protection setting value intelligent comparison method according to claim 6, characterized in that: The automatically generating a verification report includes generating a verification report according to the comparison result and exporting it.

8. A system using the protection setting value intelligent comparison method according to any one of claims 1 to 7, characterized in that: It includes parsing and storage module, collection and comparison module, and visualization generation module; The parsing and storage module is used to perform a first analysis on the file format and store it in a database; The acquisition and comparison module is used to obtain real-time data and perform a first comparison on the data; The visualization generation module is used to visualize the comparison results and automatically generate a verification report.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the protection set value intelligent comparison method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the protection setting intelligent comparison method described in any one of claims 1 to 7 are implemented.

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