Method, system, equipment and medium for centralized detection of fixed value transaction of relay protection device

Abstract

The invention discloses a method, a system, equipment and a medium for centralized detection of relay protection device constant value transaction, and belongs to the technical field of relay protection device transaction detection, and the method comprises the steps: obtaining constant value data from a plurality of protection devices through a substation, comprising first constant value data obtained through calling of a communication interface and second constant value data obtained through a printing interface; normalizing the two fixed value data to generate a first fixed value measuring point data set and a second fixed value measuring point data set; obtaining constant value notification list data, analyzing the constant value notification list data into constant value reference data, and binding the constant value reference data with the protection device; matching and comparing the two fixed value measuring point data sets with fixed value reference data respectively; and judging whether the two comparison results are consistent or not, and if not, outputting a data source abnormity alarm. According to the invention, through dual-source data acquisition and dual comparison result verification, data source abnormity can be identified; and the problem of difference of constant value formats of protection devices of different manufacturers is solved through standardized processing.

Description

Technical Field

[0001] This invention relates to the field of relay protection device anomaly detection technology, specifically to a method, system, equipment, and medium for centralized detection of relay protection device setting anomalies. Background Technology

[0002] The accuracy of relay protection settings is crucial for the safe, stable, and reliable operation of power systems. Incorrect settings can lead to relays failing to operate or malfunctioning, resulting in serious incidents such as equipment damage and grid instability. Relay protection settings must be set according to the specific protection device. Each relay protection device corresponds to one or more setting notification forms. For relay protection settings to take effect, two steps are required: calculating the setting to generate a setting notification form, and then setting the protection device according to the requirements of the setting notification form. Currently, the relay protection setting calculation stage is governed by strict principles and management of setting calculation tools, minimizing the possibility of errors in this stage. However, errors frequently occur during the protection device setting stage when settings are not set according to the setting notification form, leading to malfunctions or failures to operate. Therefore, ensuring consistency between the protection device settings and the requirements of the setting notification form is extremely important.

[0003] Currently, there are two main methods for checking the consistency between the protection device settings and the setting sheet. One method involves manually checking the device settings displayed on the protection device's human-machine interface panel and comparing them item by item with the setting notification sheet. The other method involves using a protection engineer station connected to the protection device's network to retrieve the protection device's settings, displaying them on the protection engineer station's computer, and then manually comparing them with the setting notification sheet. Traditional manual comparison methods are inefficient and susceptible to errors due to human factors. Given the wide geographical distribution of substations and the large number of protection devices in China's power grid, traditional manual verification methods suffer from difficulties in obtaining protection device operating setting data, the massive amount of protection setting data, and low efficiency. Therefore, there is an urgent need for an automated, centralized method to verify the protection setting sheet against the protection device settings. This method would detect inconsistencies between the protection device settings and the setting notification sheet, automatically push alarm information to maintenance personnel, and prevent power grid equipment damage and instability caused by incorrect protection device settings. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention provides a method, system, equipment and medium for centralized detection of abnormal settings of relay protection devices.

[0005] Therefore, the technical problem solved by this invention is: how to centrally acquire and standardize the setting data of protection devices in various substations under its jurisdiction, realize the rapid and automatic accurate matching from a large number of setting sheets and protection devices, automatically compare the setting notification sheet with the setting of the protection device item by item to find errors in the device setting and the setting notification sheet, and compare the erroneous setting to centrally alarm display and management.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for centralized detection of abnormal settings in relay protection devices, comprising, The setpoint data is obtained from multiple protection devices through a substation. The setpoint data includes first setpoint data obtained through a communication interface call and second setpoint data obtained through a printing interface. The first fixed value data and the second fixed value data are respectively normalized to generate a first fixed value measurement point dataset and a second fixed value measurement point dataset; Obtain the set value notification data and parse it into set value reference data, then bind the set value reference data to the protection device; The first fixed value measurement point dataset and the second fixed value measurement point dataset are matched and compared with the fixed value reference data respectively. When the fixed value measurement point data is inconsistent with the fixed value reference data, an anomaly alarm message is generated. Determine whether the comparison results based on the first fixed-value measurement point dataset and the comparison results based on the second fixed-value measurement point dataset are consistent. If they are inconsistent, output a data source abnormality alarm.

[0007] As a preferred embodiment of the method for centralized detection of setting anomalies in relay protection devices according to the present invention, the step of standardizing the first setting data and the second setting data to generate a first setting measurement point dataset and a second setting measurement point dataset includes: Obtain the substation identification information and protection device identification information corresponding to the set value data, perform source tracing and annotation processing on the set value data, and generate set value measurement point data containing data source information; The completeness of the setpoint measurement data is verified by referring to the setpoint benchmark data. If the setpoint measurement data is incomplete, the setpoint data of the protection device is re-acquired. The data of the fixed-value measurement points that have passed the verification are processed to standardize the data format and generate a fixed-value measurement point dataset.

[0008] As a preferred embodiment of the method for centralized detection of setting anomalies in relay protection devices according to the present invention, the step of performing source tracing and annotation processing on the setting data to generate setting measurement point data containing data source information includes: Data source tags are generated based on substation identification information and protection device identification information, respectively; Write the generated data source labels into the data structure of the fixed value data to establish a mapping relationship between the fixed value data and the data source; Based on the established mapping relationship, the fixed value measurement point data is output. The data structure of the fixed value measurement point data includes a data source identifier field and a fixed value information field.

[0009] As a preferred embodiment of the method for centralized detection of setting anomalies in relay protection devices according to the present invention, the standardization of the data format of the verified setting measurement point data includes: Extract the names of all setpoints from the setpoint data within the same protection device and create a setpoint name index table; Based on the defined value name index table, detect whether there are duplicate defined value names; When duplicate value names are detected, the data type of the corresponding value item is identified, and the duplicate value names are distinguished and marked according to the difference in data type.

[0010] As a preferred embodiment of the method for centralized detection of setting anomalies in relay protection devices according to the present invention, the standardization of the data format of the verified setting measurement point data further includes: Obtain the current unit of the fixed value item of the fixed value measurement point data, and determine the preset reference unit system; Calculate the unit conversion factor based on the dimensional relationship between the current unit and the corresponding reference unit in the reference unit system; The constant value of the constant value item is numerically converted according to the unit conversion factor to generate a constant value using the reference unit.

[0011] This preferred technical solution converts the setpoint values ​​by calculating a conversion factor between the current unit and the reference unit, thus achieving unified processing of setpoint values ​​with different units. Different manufacturers' protection devices use different units for setpoints; for example, time setpoints may use seconds or milliseconds. Traditionally, manual verification requires mental calculation of unit conversions. This solution automatically calculates the conversion factor to unify different units into the reference unit, solving the problem of comparison failures caused by inconsistent value units.

[0012] As a preferred embodiment of the method for centralized detection of setting anomalies in relay protection devices according to the present invention, the step of binding the setting reference data with the protection device includes: Based on the protection device identification information contained in the setting reference data, the corresponding protection device is retrieved, and the setting measurement point dataset of the protection device is obtained. Establish a binding relationship between the fixed value items of the fixed value benchmark data and the fixed value measurement point data in the fixed value measurement point dataset; Verify whether the fixed value items of the fixed value benchmark data and the fixed value measurement point data have been bound item by item. If there are any data items that have not been bound, generate a binding error flag.

[0013] As a preferred embodiment of the method for centralized detection of setting anomalies in relay protection devices according to the present invention, the step of matching and comparing the first setting measurement point dataset and the second setting measurement point dataset with the setting reference data includes: Perform a string-complete match between the name of the fixed value item in the fixed value benchmark data and the name of the fixed value in the fixed value measurement point data. If the strings are completely identical, the match is considered successful. When a complete string match fails, extract the value item name and the feature characters in the value name, and perform fuzzy matching based on the degree of repetition of the feature characters; When fuzzy matching fails, semantic matching is performed on the fixed value name and the fixed value name based on preset semantic association rules.

[0014] This preferred technical solution achieves automatic matching of setpoint items through a three-level progressive strategy: complete string matching, fuzzy matching of feature characters, and semantic matching. Different manufacturers' protection devices have different naming rules for setpoint items. Traditional manual verification requires judging the correspondence item by item. This solution, by combining full-scale matching technology with fuzzy matching technology and semantic association rules, achieves accurate matching of benchmark data with multiple setpoint data of the comparison object.

[0015] This invention provides a system for centralized detection of abnormal settings in relay protection devices.

[0016] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a system for centralized detection of abnormal settings of relay protection devices, comprising: a data acquisition module, used to acquire setting data including first setting data and second setting data from multiple protection devices through a substation; The normalization processing module is used to normalize the first fixed value data and the second fixed value data respectively, and generate a first fixed value measurement point dataset and a second fixed value measurement point dataset. The setting value processing module is used to acquire setting value notification data and parse it into setting value reference data, and to bind the setting value reference data with the protection device; The matching and comparison module is used to match and compare the first fixed value measurement point dataset and the second fixed value measurement point dataset with the fixed value reference data, respectively. The result verification module is used to determine whether the comparison results based on two fixed-value measurement point datasets are consistent, and to generate anomaly alarm information and data source anomaly alarm.

[0017] The present invention provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the method for centralized detection of abnormal settings of a relay protection device.

[0018] The present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method for centralized detection of abnormal settings of a relay protection device.

[0019] The beneficial effects of this invention are as follows: Using the setting sheet as the baseline data, and comparing the setting data summoned by the protection device from two sources with the setting data printed by the protection device, a combination of full-data matching and fuzzy matching techniques is employed to achieve precise matching of multiple setting data points between the baseline data and the comparison objects. Furthermore, the reliability of the test results is ensured through consistency verification of the dual comparison results. Traditional methods involve manually comparing the printed protection device settings or the settings displayed on the protection device's human-machine interface panel with the setting sheet. This relies on a single data source and is inefficient and prone to errors. This invention automatically matches and cross-verifies data from two sources, improving both work efficiency and accuracy.

[0020] In the protection device setting data acquisition stage, setting data traceability technology is used to generate setting measurement point data. This data is then standardized in naming, unit, and accuracy, resolving the problem of calculation and comparison failures caused by inconsistent naming, unit variations, and insufficient accuracy of setting values ​​from different manufacturers. Traditional methods cannot handle data format differences between different manufacturers' equipment; this invention achieves accurate comparison of heterogeneous data sources through standardization.

[0021] This invention enables centralized testing of protection device settings against setting sheets over a large area, accurately and efficiently identifying inconsistencies and preventing malfunctions or failures due to incorrect settings. Traditional methods require manual verification of each device individually, which is inefficient when dealing with geographically dispersed areas and a large number of protection devices. This invention provides automated comparison of setting sheets with protection devices on a large scale. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1The above is a flowchart of a method for centralized detection of abnormal settings in relay protection devices, provided as an embodiment of the present invention.

[0024] Figure 2 This is a schematic diagram of the setting data forwarding principle of a method for centralized detection of setting anomalies in relay protection devices, provided in one embodiment of the present invention.

[0025] Figure 3 This is a schematic diagram illustrating the principle of setting point data formation for a method for centralized detection of setting anomalies in relay protection devices, provided in one embodiment of the present invention.

[0026] Figure 4 This is a master station data verification logic diagram for a method of centralized detection of abnormal settings in relay protection devices, provided as an embodiment of the present invention. Detailed Implementation

[0027] To make the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0028] Example 1, referring to Figure 1 This is one embodiment of the present invention, which provides a method for centralized detection of abnormal settings in relay protection devices, comprising: Step 1: Obtain setting data from multiple protection devices through the substation. The setting data includes first setting data obtained through communication interface and second setting data obtained through printing interface. Step 2: Normalize the first fixed value data and the second fixed value data respectively to generate a first fixed value measurement point dataset and a second fixed value measurement point dataset; Step 3: Obtain the setting notification data and parse it into setting reference data, then bind the setting reference data to the protection device; Step 4: Match and compare the first fixed value measurement point dataset and the second fixed value measurement point dataset with the fixed value reference data respectively. When the fixed value measurement point data is inconsistent with the fixed value reference data, generate an anomaly alarm message. Step 5: Determine whether the comparison results based on the first fixed-value measurement point dataset and the comparison results based on the second fixed-value measurement point dataset are consistent. If they are inconsistent, output a data source abnormality alarm.

[0029] This embodiment provides a method for centralized detection of relay protection device setting anomalies, solving the problems of low efficiency and low accuracy in detecting the consistency between protection device setting settings and setting notification forms in power systems. This method establishes a three-layer architecture of master station-substation-protection device, achieving centralized automated detection of protection device settings for all substations within its jurisdiction. The substation, acting as a relay node, establishes communication connections with each protection device. It then obtains setting data sent from the protection device's station control layer via a communication interface call as the first setting data, and simultaneously obtains the setting data printed out by the protection device via a printing interface as the second setting data, forming a dual-source data acquisition mechanism. After receiving the setting data from the substation, the master station performs source tracing, completeness verification, and format standardization processing on the first and second setting data, generating a first and second setting point datasets containing data source information and unified format. The main station simultaneously acquires the setting notification data entered by maintenance personnel, parses the setting notification into setting benchmark data containing protection device identification information and setting item information, and establishes a binding relationship between the setting benchmark data and the corresponding protection device based on the protection device identification information. The main station matches and compares the two setting measurement point datasets with the setting benchmark data respectively. When the setting measurement point data and the setting benchmark data are inconsistent, an anomaly alarm is generated, and the main station determines whether the two comparison results are consistent. If they are inconsistent, a data source anomaly alarm is output to ensure the reliability of the detection conclusions.

[0030] In the standardization process of setpoint data, by acquiring the substation identification information and protection device identification information corresponding to the setpoint data, each setpoint data is tagged with a substation name and a protection device name, establishing a mapping relationship between the setpoint data and the data source, so that each setpoint measurement point data can be traced back to a specific substation and protection device. The completeness of the setpoint measurement point data is verified against the setpoint benchmark data, checking whether the setpoint measurement point data contains all the setpoint items required by the setpoint notification. When data loss is detected, a re-acquisition instruction is issued to the substation. The verified setpoint measurement point data undergoes data format standardization processing, including creating an index table for setpoint names to detect and eliminate duplicate names, calculating unit conversion factors to unify different units into a benchmark unit, and formatting according to data type requirements. In the matching and comparison process, firstly, a string-complete match is performed between the setpoint item names in the setpoint benchmark data and the setpoint names in the setpoint measurement data. When a complete match fails, feature characters are extracted for fuzzy matching based on the degree of repetition. When fuzzy matching fails, semantic matching is performed based on preset semantic association rules, achieving automatic identification of setpoint items. After successful matching, the system compares the setpoint values ​​of the baseline data and the measured data to see if they are consistent. If they are inconsistent, an anomaly alarm message is generated, including the protection device identifier, setpoint name, baseline value, and actual value. The system also checks if the comparison results based on the first setpoint dataset and the second setpoint dataset are consistent. If the two results are inconsistent, a data source anomaly alarm is output to remind maintenance personnel to check the data acquisition process.

[0031] Example 2, an embodiment of the present invention, provides a method for centralized detection of abnormal settings in relay protection devices based on the previous embodiment, comprising: Step 1: Obtain setting data from multiple protection devices via a substation. The setting data includes first setting data obtained through a communication interface and second setting data obtained through a printing interface, including the following steps A1-A3: A1: Establish a protection information substation as a relay node, and establish a communication connection between the protection information substation and each protection device of the substation under its jurisdiction; A2: The protection information substation sends a setting value call command to the communication interface of the protection device to obtain the setting value data sent by the station control layer of the protection device as the first setting value data. The protection information substation then sends the first setting value data to the main station. A3: The protection device prints out the setpoint data through its printing interface as the second setpoint data, and the protection information substation sends the second setpoint data to the main station.

[0032] Step 2: Normalize the first fixed value data and the second fixed value data respectively to generate the first fixed value measurement point dataset and the second fixed value measurement point dataset, including the following steps B1-B3: B1: Obtain the substation identification information and protection device identification information corresponding to the set value data, perform source tracing and annotation processing on the set value data, and generate set value measurement point data containing data source information; B2: The completeness of the setpoint measurement data is verified by referring to the setpoint benchmark data. If the setpoint measurement data is incomplete, the setpoint data of the protection device is re-acquired. B3: Standardize the data format of the verified fixed-value measurement points to generate a fixed-value measurement point dataset.

[0033] In this embodiment of the application, in step B2, the completeness check is passed: taking the fixed value items contained in the fixed value reference data as a reference, it is checked whether the fixed value measurement point data contains the fixed value measurement point corresponding to the fixed value item. When the fixed value measurement point data is missing the corresponding fixed value measurement point, it is determined that the fixed value measurement point data is incomplete, and a re-acquisition instruction is sent to the information protection substation.

[0034] In an optional implementation, in step B2, the completeness verification can be performed by: counting the number of fixed value items contained in the fixed value benchmark data and the number of fixed value measurement points contained in the fixed value measurement point data. When the number of fixed value measurement points is less than the number of fixed value items, it is determined that the fixed value measurement point data is incomplete, a data defect record is generated, and the information protection substation is notified to re-collect the data.

[0035] In another optional implementation, in step B2, the completeness check can also be performed by: extracting the list of fixed value item names of the fixed value reference data and the list of fixed value name of the fixed value measurement point data, comparing the two lists, and determining that the fixed value measurement point data is incomplete when the list of fixed value name of the fixed value measurement point data is missing a fixed value item name from the fixed value reference data, marking the missing fixed value item name and triggering a re-acquisition process.

[0036] In this embodiment of the application, step B3 involves standardizing the data format by: extracting the names of all fixed value measurement points within the same protection device and establishing a fixed value name index table; detecting whether there are duplicate fixed value names based on the fixed value name index table; when duplicate fixed value names are detected, identifying the data type of the corresponding fixed value item and distinguishing and marking the duplicate fixed value names according to the differences in data types.

[0037] In an optional implementation, in step B3, the data format standardization process can be performed by: obtaining the current unit of the fixed value item of the fixed value measurement point data, determining the preset reference unit system; calculating the unit conversion factor based on the dimensional relationship between the current unit and the corresponding reference unit in the reference unit system; and performing numerical conversion on the fixed value of the fixed value item according to the unit conversion factor to generate a fixed value using the reference unit.

[0038] In another optional implementation, in step B3, the data format standardization process can also be performed by: identifying the data type of the fixed value of the fixed value measurement point data; determining the corresponding data precision requirements according to the data type; and formatting the fixed value according to the data precision requirements, wherein the numerical precision of the current type fixed value, voltage type fixed value, impedance type fixed value and time type fixed value is retained to three decimal places, the numerical precision of the engagement / disengagement type fixed value is 0 or 1, and the control word type fixed value is represented in hexadecimal.

[0039] It should be noted that the setpoint measurement data includes three types of setpoint measurement points: device parameters, setpoint items, and soft pressure plate. Device parameters include the protection device's model information, rated voltage, rated current, and communication settings. Setpoint items include numerical type setpoints and control word type setpoints. The numerical type setpoints include current setpoints, voltage setpoints, impedance setpoints, and time setpoints. The control word type setpoints are used to indicate the activation conditions or action logic of the protection function. The soft pressure plate is used to control the activation or deactivation status of the protection function; the value corresponding to the activation status is 1, and the value corresponding to the deactivation status is 0.

[0040] It should be noted that the process of tracing and labeling fixed-value data to generate fixed-value measurement point data containing data source information includes the following steps: Data source tags are generated based on substation identification information and protection device identification information, respectively; Write the generated data source labels into the data structure of the fixed value data to establish a mapping relationship between the fixed value data and the data source; Based on the established mapping relationship, the fixed value measurement point data is output. The data structure of the fixed value measurement point data includes a data source identifier field and a fixed value information field.

[0041] Furthermore, the data format of the verified fixed-value measurement point data is standardized, including deduplication of the fixed-value names: extract the fixed-value names of all fixed-value measurement point data within the same protection device and establish a fixed-value name index table; Based on the defined value name index table, detect whether there are duplicate defined value names; When duplicate value names are detected, the data type of the corresponding value item is identified, and the duplicate value names are distinguished and marked according to the difference in data type.

[0042] Furthermore, the data format of the verified fixed-value measurement point data is standardized, including the unified processing of the fixed-value units: obtaining the current unit of the fixed-value item of the fixed-value measurement point data and determining the preset benchmark unit system; Calculate the unit conversion factor based on the dimensional relationship between the current unit and the corresponding reference unit in the reference unit system; The constant value of the constant value item is numerically converted according to the unit conversion factor to generate a constant value using the reference unit.

[0043] It should be noted that the reference unit system includes: the reference unit for current-related values ​​is the ampere; the reference unit for voltage-related values ​​is the volt; the reference unit for impedance-related values ​​is the ohm; and the reference unit for time-related values ​​is the second.

[0044] Data format normalization also includes precision formatting of fixed values: Identify the data type of the fixed value of the fixed value measurement point data, including current type, voltage type, impedance type, time type, on / off type and control word type; The corresponding data precision requirements are determined based on the data types described. Specifically: the data precision requirements for current-type, voltage-type, impedance-type, and time-type settings are to retain 3 decimal places; the data precision requirements for on / off-type settings are integers 0 or 1; and the data precision requirements for control word-type settings are to be represented in hexadecimal. The settings are then formatted according to the described data precision requirements.

[0045] For example, the original value of the current setting is 2.5678A, and after precision formatting, it becomes 2.568A; the original value of the time setting is 0.12345S, and after precision formatting, it becomes 0.123S; the original value of the enable / disable setting is enable, and after precision formatting, it becomes 1; the original value of the control word setting is binary 11010101, and after precision formatting, it becomes hexadecimal D5.

[0046] It should be noted that the specific implementation of calculating the unit conversion factor is as follows: Obtain the dimensional conversion relationship between the current unit and the reference unit of the fixed value item; Calculate the unit conversion factor k, where k is equal to the ratio of the physical quantity value corresponding to the current unit to the physical quantity value corresponding to the reference unit. Multiply the constant value of the constant value item by the unit conversion factor k to obtain the constant value using the reference unit.

[0047] For example, when the current unit of the setpoint is milliseconds (ms) and the base unit is seconds (s), 1ms = 0.001s, then k = 0.001s / 1s = 0.001. If the setpoint is 500ms, then the setpoint after unit conversion is 500 × 0.001 = 0.5s.

[0048] For example, when the current unit of the setpoint is kiloampere (kA) and the base unit is ampere (A), 1kA = 1000A, then k = 1000A / 1A = 1000. If the setpoint is 2.5kA, then the setpoint after unit conversion is 2.5 × 1000 = 2500A.

[0049] Furthermore, the completeness check is specifically implemented as follows: Extract all names of the setpoint items contained in the setpoint benchmark data to form a benchmark setpoint item list; Extract all the fixed value names contained in the fixed value measurement point data to form a list of measurement point fixed value names; Check each item in the benchmark setting item list to see if there is a corresponding setting name in the measuring point setting name list; When all the names of the reference setpoints can be found in the list of measurement point setpoints, the measurement point data is considered complete. When at least one value item name in the benchmark value item list cannot be found in the measurement point value name list, it is determined that the value measurement point data is incomplete, and a data defect record is generated. The data defect record contains the missing value item name and the corresponding protection device identification information, and a re-acquisition instruction is sent to the protection information substation.

[0050] Step 3: Obtaining the setting notification data and parsing it into setting reference data, and binding the setting reference data with the protection device, includes the following steps C1-C3: C1: Retrieve the corresponding protection device based on the protection device identification information contained in the setting reference data, and obtain the setting measurement point dataset of the protection device; C2: Establish a binding relationship between the fixed value items of the fixed value benchmark data and the fixed value measurement point data in the fixed value measurement point dataset; C3: Verify whether the fixed value items of the fixed value benchmark data and the fixed value measurement point data have been bound item by item. If there are data items that have not been bound, generate a binding error flag.

[0051] In this embodiment of the application, step 3 involves binding the setting reference data with the protection device by: obtaining setting notification data; extracting basic information, device parameter information, and setting item information from the setting notification data; the basic information including the setting notification number, substation name, and protection device name; the device parameter information including the protection device model and rated parameters; and the setting item information including the setting item name and setting item value; and organizing the extracted basic information, device parameter information, and setting item information according to a preset setting reference data structure to generate setting reference data.

[0052] In an optional implementation, step 3, binding the setting reference data with the protection device can be achieved by: retrieving the corresponding protection device based on the protection device name in the setting reference data, and obtaining the setting measurement point dataset of the protection device; establishing a binding relationship between each setting item in the setting reference data and the setting measurement point data in the setting measurement point dataset; counting the total number of setting items in the setting reference data and the number of setting items with established binding relationships, and determining that the binding is complete when the number of setting items with established binding relationships equals the total number of setting items; and generating a binding anomaly flag when there are setting items without established binding relationships.

[0053] In another optional implementation, step 3, binding the setpoint reference data to the protection device can also be achieved by: extracting the protection device identification information contained in the setpoint reference data; querying the protection device database for matching protection device records based on the protection device identification information; obtaining the setpoint measurement point dataset corresponding to the protection device record; establishing an association index between the setpoint reference data and the setpoint measurement point dataset; verifying the validity of the association index; when the setpoint item of the setpoint reference data can find the corresponding setpoint measurement point in the setpoint measurement point dataset, the binding is deemed valid; otherwise, a binding failure record is generated and a manual review process is triggered.

[0054] Step 4: Matching and comparing the first and second fixed-value measurement point datasets with the fixed-value reference data, and generating an anomaly alarm when the fixed-value measurement point data is inconsistent with the fixed-value reference data, includes the following steps D1-D3: D1: Perform a string-based exact match between the name of the fixed value item in the fixed value benchmark data and the name of the fixed value in the fixed value measurement point data. If the strings are completely identical, the match is considered successful. D2: When a complete string match fails, extract the value item name and the feature characters in the value name, and perform fuzzy matching based on the degree of repetition of the feature characters; D3: When fuzzy matching fails, semantic matching is performed on the fixed value name and the fixed value name based on the preset semantic association rules.

[0055] In this embodiment, step 4 involves matching and comparing the following: The names of the fixed-value items in the fixed-value benchmark data and the fixed-value names in the fixed-value measurement point data are subjected to a complete string match. If the strings are identical, the match is considered successful and recorded. If the complete string match fails, feature characters are extracted from the fixed-value item names and the fixed-value names, and the degree of repetition of the feature characters is calculated. If the degree of repetition of the feature characters reaches a preset threshold, the fuzzy match is considered successful. If the fuzzy match fails, the fixed-value item names and the fixed-value names are decomposed into phrases based on preset semantic association rules. Synonyms are searched in a thesaurus, and if a synonym is found, the semantic match is considered successful.

[0056] In an optional implementation, in step 4, matching and comparison can be performed by: for successfully matched setting items, extracting the benchmark setting value of the setting reference data and the actual setting value of the setting measurement point data; determining whether the data types of the benchmark setting value and the actual setting value are consistent; when the data types are consistent, performing numerical comparison; when the values ​​are completely equal, determining that the comparison is consistent; when the values ​​are not equal, determining that the comparison is inconsistent and generating an anomaly alarm information; the anomaly alarm information includes the substation name, protection device name, setting item name, benchmark setting value, and actual setting value.

[0057] In another optional implementation, in step 4, the matching and comparison can also be performed by: for successfully matched fixed value items, obtaining the benchmark fixed value of the fixed value reference data and the actual fixed value of the fixed value measurement point data; when both the benchmark fixed value and the actual fixed value are numerical types, calculating the difference between the two, determining that the comparison is consistent when the absolute value of the difference is less than a preset allowable deviation threshold, and determining that the comparison is inconsistent when the absolute value of the difference is greater than or equal to the allowable deviation threshold; when the benchmark fixed value and the actual fixed value are control word type or string type, performing a string identicalness comparison, determining that the comparison is consistent when they are the same, and determining that the comparison is inconsistent when they are different.

[0058] It should be noted that the specific implementation of fuzzy matching based on the degree of repetition of feature characters is as follows: Extract the characteristic characters from the name of the fixed value item as the first set of characteristic characters, and extract the characteristic characters from the name of the fixed value item as the second set of characteristic characters; Calculate the number of identical characters in the first characteristic character set and the second characteristic character set, and denote it as the number of repeated characters N; Calculate the repetition rate R of the feature characters, where R = N / M, and M is the larger value of the total number of characters in the first feature character set and the second feature character set; When the repetition rate R of the feature character is greater than or equal to a preset threshold, it is determined that the fuzzy match is successful. The preset threshold is preferably 80%.

[0059] For example, if the setpoint name is "Overcurrent Section I Current Setpoint", the extracted feature characters are "overcurrent", "section", "current", and "setpoint". If the setpoint name is "Overcurrent Section I Current Setpoint", the extracted feature characters are also "overcurrent", "section", "current", and "setpoint". There are three identical characters: "overcurrent", "current", and "setpoint". The first feature character set has four characters, and the second feature character set also has four characters, so M=4. Therefore, R=3 / 4=75%. If the preset threshold is 80%, this example is determined to be a fuzzy match failure and needs to proceed to the semantic matching stage.

[0060] Step 5: Determine whether the comparison results based on the first fixed-value measurement point dataset and the comparison results based on the second fixed-value measurement point dataset are consistent. If they are inconsistent, output a data source abnormality alarm, including the following steps E1-E3: E1: Obtain the first comparison result obtained by comparing the first fixed value measurement point dataset with the fixed value benchmark data, and the second comparison result obtained by comparing the second fixed value measurement point dataset with the fixed value benchmark data; E2: Determine whether the first comparison result and the second comparison result are consistent. When both comparison results are determined to be consistent, the comparison results are considered to be consistent. When at least one of the two comparison results is determined to be inconsistent, the comparison results are considered to be inconsistent. E3: When the first comparison result is consistent with the second comparison result, the comparison result will be output to the power grid management platform. When the first comparison result is inconsistent with the second comparison result, an abnormal data source alarm will be output and the operation and maintenance personnel will be prompted to find out the problem.

[0061] Specifically, the implementation for determining whether the comparison results are consistent is as follows: Obtain the abnormality alarm information from the first comparison result and the second comparison result respectively; When neither the first comparison result nor the second comparison result contains any abnormality alarm information, it is determined that the two comparison results are consistent and the set value data is normal. When both the first comparison result and the second comparison result contain abnormal alarm information, and the name of the setpoint item, the benchmark setpoint and the actual setpoint in the two abnormal alarm information are exactly the same, it is determined that the two comparison results are consistent and the setpoint data is abnormal. If the first comparison result contains abnormal activity alarm information but the second comparison result does not contain abnormal activity alarm information, or the first comparison result does not contain abnormal activity alarm information but the second comparison result does contain abnormal activity alarm information, or the abnormal activity alarm information contained in the two comparison results is different, it is determined that the two comparison results are inconsistent and an abnormal data source alarm is output.

[0062] Example 3, referring to Figures 1-4 As an embodiment of the present invention, based on the previous embodiment, a method for centralized detection of abnormal settings in relay protection devices is provided, comprising: like Figure 1 As shown, the technical principle of this embodiment includes the following steps: First, dual-source setting data is obtained from the protection device through the substation; then, the setting data is standardized to form standard setting measurement point data; at the same time, setting notification data is obtained and parsed into setting benchmark data; finally, setting matching and comparison methods are used to compare the setting measurement point data with the setting benchmark data one by one, and inconsistencies are found and alarms are output.

[0063] like Figure 2 As shown, a communication connection is established, and a communication network is built according to a three-layer structure of protection device, protection information substation, and main station. The acquisition of protection device setting data is achieved through a layered communication acquisition method involving the protection device, protection information substation, and main station.

[0064] First, a protection and information transmission substation is configured on a per-substation basis. These substations are installed locally at each substation, serving as relay nodes for collecting setting data from the protection devices. Using a standardized communication protocol and based on a pre-configured information model mapping relationship, the protection and information transmission substation sends reading requests for setting data to the protection devices. It then parses the data returned by the protection devices according to the agreed-upon protocol specifications, ultimately obtaining the setting data from each protection device and temporarily storing the setting information at the substation.

[0065] The communication modes of the Baoxin substation support the IEC60870-5-103 and IEC61850 standard communication protocols widely used in substations. Depending on the actual application requirements of the project, the Baoxin substation can choose either an Ethernet interface or a fiber optic interface to communicate with the protection device. For protection devices requiring serial communication, the Baoxin substation node also provides RS232 and RS485 serial communication methods.

[0066] It should be noted that only one of the RS232 or RS485 modes can be selected for the same serial port communication mode; it cannot have both RS232 and RS485 modes simultaneously.

[0067] The core function of the information protection substation is to process and forward setpoint information. The collection of setpoint data by the information protection substation is completed collaboratively by the communication interface, application software, and data bus, and information interaction is completed between the module kernel and the application software.

[0068] After the communication links between the protection substation and the protection device, and between the protection substation and the master station are established, the protection substation can send setting information call commands to the connected protection devices in real time or periodically. After receiving the command, the protection device packages its own setting data and sends it to the protection substation using the agreed IEC60870-5-103 or IEC61850 communication protocol.

[0069] like Figure 3 As shown, in order to accurately distinguish which protection device in which substation the set value data comes from, it is necessary to perform traceability labeling on the set value data.

[0070] Specifically, the dual-source setting data collected from different communication interfaces are all tagged and named. After the setting data transmitted by each protection device to the protection information substation is successfully received by the protection information substation, each protection device setting data is tagged with the device name to record the protection device to which the specific setting item belongs.

[0071] The naming convention for protection devices consists of the voltage level of the primary equipment to which the protection device belongs, the Chinese name of the bay, and the name of the protection device. For example, the name of the protection device is "220kV XX Line Main Protection Device".

[0072] Similarly, to accurately distinguish which substation the setpoint data belongs to, each setpoint item is also labeled with the substation name. The substation name also follows the naming requirements of the power system standards, consisting of the substation's voltage level and its Chinese name. For example, the substation name might be 500kV XX Substation.

[0073] Through the above processing, the source of each fixed value data has been identified, forming a series of fixed value measurement point data with clear fixed value sources.

[0074] It should be noted that after obtaining the dual-source fixed-value measurement point data, the same method was used for all subsequent fixed-value data processing.

[0075] like Figure 4 As shown, due to the large number of manufacturers and models of protection devices, the rules for defining the name, value, and unit of each setting are not the same for different protection devices. Therefore, it is necessary to standardize the naming process of the setting measurement point data item by item.

[0076] Before standardizing the naming of the setpoint measurement data, the master station first uses a verification tool to check the completeness of the setpoint measurement data. The completeness verification of the setpoint measurement data is based on the setpoint notification form, and checks whether the protection device corresponding to the strain gauge substation has completely sent the setpoint measurement points required by the setpoint notification form to the master station.

[0077] If all the setting items required by the setting notification have corresponding setting measurement points, then the setting measurement point data of the protection device is considered complete; otherwise, the setting measurement point data of the protection device is considered incomplete.

[0078] The main station performs a full verification of the completeness of the fixed-value measurement point data and generates a station-wide data verification conclusion, accurately identifying protection devices with unqualified data. Based on the conclusion, the protection devices and data transmission substations are activated to eliminate data defects, the data is re-uploaded, and the data verification tool is restarted to check the received data until the data is qualified.

[0079] After the main station completes the collection of all setpoint measurement point data according to the baseline requirements of the setpoint notification, it will perform standardized processing on the setpoint measurement point data, using the protection device as the processing unit. This includes the following steps: The first step in standardizing the data of fixed-value measurement points is to standardize the naming of each fixed-value measurement point.

[0080] It should be noted that the setpoint measurement points are divided into three categories: device parameters, setpoint items, and soft pressure plates. Among them, the setpoint items include numerical type setpoints and control word type setpoints, and the same protection function may have both numerical type setpoints and control word type setpoints with the same name.

[0081] This requires separating each setpoint item into three parts: setpoint name, value, and unit, and then checking the setpoint name string for duplicates to detect whether there are duplicate setpoint name items for the same device's setpoint measurement points.

[0082] If there are duplicate value names, the measurement points with duplicate values ​​will be extracted for further value determination: If the value is a numerical fixed value, then the fixed value measuring point is a numerical fixed value measuring point, and its measuring point name is consistent with the standardized naming; if the value is a control word type, then the standardized naming of the fixed value measuring point is to distinguish it by adding a control word field to the original measuring point name, so as to eliminate the problem of duplicate fixed value items of the fixed value measuring point.

[0083] The second step in the standardization process of fixed-value measurement point data is to standardize the units of each fixed-value measurement point data item with units.

[0084] This embodiment uses the current unit ampere (A), voltage unit volt (V), impedance unit ohm (Ω), and time unit second (S) as the reference units to check whether there is a multiple relationship between the units of the data at each fixed measurement point and the reference units.

[0085] by To indicate a multiple relationship between two units, k is calculated by dividing the unit of the fixed measurement point value by the reference unit. For example, the relationship between 1ms and S is 1ms = 0.001S, used when unifying milliseconds to seconds. =0.001 seconds / 1 second = 0.001, thus obtaining After taking the value, multiply the measured point value by... This completes the standardization process for unified measurement point units, with This represents the value of the original measuring point. This represents the value of the fixed measurement point after normalization according to the reference unit. For example, if the current setting measurement point value for the overcurrent stage I is 2.5A, and its unit is A, then... The standardized overcurrent setting for stage I is 2.5 × 1 = 2.5 A. For example, the original setting value for stage I overcurrent with time limit 2 is... =500ms, Calculation coefficient After standardization =500mS×0.001=0.5S.

[0086] Different types of values ​​have different precision requirements during data processing, so the precision of the fixed measurement point data values ​​must also be standardized during data normalization.

[0087] The specific requirements are as follows: the data precision of current, voltage, impedance, and time values ​​must be retained to 3 decimal places; the enable / disable value must be an integer 0 or 1; and multi-digit control words must be standardized into hexadecimal data.

[0088] After the main station completes the standardized management of the fixed measurement points, it is also necessary to conduct statistics and evaluation on various data indicators of the protection device.

[0089] The statistical objects include measurement points of the setpoint type, verifying whether the setpoint measurement points meet the application requirements. Specific verification conclusions are output in a verification report; after exporting the acceptance report, the verification status of the setpoint measurement point data for the protection device can be obtained.

[0090] This mainly includes ensuring that all fixed-value measurement point names submitted by the data transmission substation are standardized, that numerical units are consistent, and that data accuracy meets the requirements. Based on data verification, statistical indicators for the corresponding measurement point types are compiled, and the results of data quality quantification are provided.

[0091] Furthermore, as the benchmark for checking setting value changes, the setting value notification form needs to obtain the data from the official setting value notification form after the setting calculation is completed.

[0092] After the setting notification import process is initiated, a setting notification is first parsed into three parts: basic setting notification data, device parameters, and setting items. The basic data includes the plant name, bay name, device name, device software information, execution date, and executor of the setting notification. The device parameters include rated voltage, rated current, the corresponding bay, communication settings, and other device parameters. The key setting item data includes numerical setting values, time setting values, soft pressure plates, control words, and other key setting items.

[0093] After the setting notification is parsed, the data in the setting notification needs to be bound to the corresponding protection device. Specifically, this is achieved by retrieving the corresponding protection device based on the protection device name obtained from the basic information in the setting notification.

[0094] If the retrieved protection device does not have an in-operation setting notification, it is considered a newly commissioned device, thus achieving item-by-item matching and binding between the setting notification data and the setting measurement point data of the protection device.

[0095] After the setting notification form and the protection device are matched and bound, verify whether the setting item binding is normal. The main verification content is to check whether the setting on the setting notification form, the soft pressure plate, the device parameters and the measuring points of the protection device are consistent.

[0096] If the setpoint notification forms match the device measurement points one by one, an approval process is initiated. The setpoint notification forms are then submitted and bound together, forming an approval process pending approval, which is sent to the reviewer for approval. The reviewer can reject the application if they have any comments. If rejected, the reviewer fills in their comments, and a pending task is pushed to the person who initiated the process. The status of the setpoint notification forms will then show as "approval process rejected." If the reviewer approves and confirms the application, the setpoint notification forms will automatically switch to the "running" status.

[0097] If any unbound device measurement points are detected in the parameters or items of the setting notification form, it is determined that the device measurement points are not fully uploaded. In this case, the device measurement point defect handling process is initiated, the setting notification form binding fails, and the setting notification form binding process is withdrawn. After the device measurement point incomplete upload defect handling is completed, the setting notification form binding process is initiated again until the setting notification form is successfully bound to the device.

[0098] If a new setting notification is found to indicate that the corresponding device already has an operating setting notification, it is necessary to determine whether the current operating setting notification of the protection device needs to be converted to a historical setting notification. If it is necessary to convert the current operating setting notification to historical, the newly added setting notification will be initiated into a binding and review process. After the review is completed, the original operating setting notification will be converted to historical and exit operation, and the newly added setting notification will be converted to an operating setting notification.

[0099] If it is determined that the current protection device's setting notification does not need to be transferred to the historical record, a new setting notification will be added, and it will be checked whether it is a multi-zone setting for the protection device. If so, the new setting notification will be stored and reserved for use when the protection device switches zones, initiating the corresponding zone number setting notification transfer and setting notification binding verification process.

[0100] Furthermore, after completing the parsing of the setting notification and matching and binding the setting notification data with the setting measurement point data of the protection device one by one, the conditions for setting comparison are met.

[0101] Specifically, the data in the setting notification form is defined as a baseline value for each item, and a string matching check is performed between the setting item name in the setting notification form and the setting measurement point name of the protection device. If the names are completely identical, the values ​​are compared. A correct comparison requires that the setting measurement point value of the protection device be completely consistent with the baseline value in the setting notification form. If they are inconsistent, an alarm is output indicating a discrepancy between the setting measurement point value and the setting notification form value.

[0102] If the name of the setting item on the setting notification form does not perfectly match the name of the setting measurement point on the protection device, fuzzy matching of key fields is used. Fuzzy matching is implemented by first assigning visual identifiers to the setting measurement points to facilitate matching between them and the setting reference. Fuzzy matching then identifies key characters based on these visual identifiers. A successful match is determined when the key characters in the setting measurement point name and the setting reference name have an 80% overlap.

[0103] If keyword repetition rate matching fails, similarity matching is then performed. Similarity matching first requires establishing a thesaurus of synonyms for setting values ​​based on commonly used terms in relay protection setting notifications, associating phrases with the same meaning within the thesaurus. Then, the setting measurement point name is segmented by phrase, and the resulting phrases are searched in the thesaurus for associated phrases. If a synonym associated with the setting measurement point is found to match the baseline setting value name, the match is successful.

[0104] If a match is successful, the process proceeds to the comparison stage, and the comparison result is output. If the similarity match fails again, the process switches to manual matching. If manual matching still fails, the measurement point data is deemed invalid, and the corresponding protection device is converted to a device with measurement point transmission defects. After the defects are eliminated, the protection device setting measurement points are re-collected, the setting notification is bound, and the comparison is repeated.

[0105] Furthermore, the output of the setting anomaly judgment results realizes a full display of the comparison results based on the setting items of the protection device. In the panoramic data interface, the setting notification form is used as the benchmark, and each line of data represents a comparison result. In the same line of data, the name of the setting measurement point of the protection device is used as the setting name, the value of the corresponding setting notification form data is used as the benchmark setting value, and the device value is used as the comparison object.

[0106] If the benchmark value matches the measured value, the comparison conclusion is correct; if the device value does not match the benchmark value, the comparison conclusion is incorrect, the entire row of data will be highlighted as incorrect, and the error row information will be proactively recorded and pushed to the maintenance personnel.

[0107] Furthermore, in order to conduct long-term and repeated checks on protection device setting anomalies, it is also necessary to establish and carry out periodic inspection tasks. When the periodic time node is reached, the above-mentioned method of processing the setting data into measurement points and comparing the measurement points with the benchmark is used to check for protection device setting anomalies, so as to realize the periodic detection of protection device setting anomalies.

[0108] To meet the need for dynamic inspection of protection device setting changes, it is also necessary to be able to temporarily create setting change inspection tasks to meet the needs of dynamically detecting protection device setting changes.

[0109] Furthermore, in the operation and maintenance of relay protection devices, a change in a certain electrical parameter will inevitably lead to a modification of the setting notification form. When the setting notification form is changed, it is necessary to trigger the protection device setting anomaly check. After triggering the anomaly check, the process of obtaining two sets of setting data from the dual setting data sources is restarted, and then a complete process of setting data processing, comparison, and output conclusion is performed again to verify the consistency between the changed setting notification form and the setting value set by the protection device.

[0110] Similarly, if the software or hardware of the protection device changes, the protection device settings need to be readjusted, which in turn causes the protection device settings data to change. In this case, the protection device settings change check also needs to be triggered to detect whether the device settings are consistent with the settings notification after the software or hardware changes.

[0111] Furthermore, to ensure the accuracy and reliability of the protection device setting anomaly detection results, setting data from two different sources is obtained from the device station control layer communication interface and the device printing interface.

[0112] The subsequent processing of fixed-value measurement points, measurement point matching, and comparison with the benchmark fixed value are the same, but two anomaly detection conclusions still need to be output. The output result is only valid if the two conclusions are consistent. If the anomaly detection conclusions from the two data sources are inconsistent, an alarm needs to be output, and the cause needs to be investigated and dealt with until the two detection conclusions are consistent.

[0113] Example 4 is an embodiment of the present invention. This embodiment provides a system for centralized detection of abnormal settings of relay protection devices, including: a data acquisition module, used to acquire setting data including first setting data and second setting data from multiple protection devices through a substation; The normalization processing module is used to normalize the first fixed value data and the second fixed value data respectively, and generate a first fixed value measurement point dataset and a second fixed value measurement point dataset. The setting value processing module is used to acquire setting value notification data and parse it into setting value reference data, and to bind the setting value reference data with the protection device; The matching and comparison module is used to match and compare the first fixed value measurement point dataset and the second fixed value measurement point dataset with the fixed value reference data, respectively. The result verification module is used to determine whether the comparison results based on two fixed-value measurement point datasets are consistent, and to generate anomaly alarm information and data source anomaly alarm.

[0114] This embodiment also provides an electronic device applicable to a method for centralized detection of abnormal settings in relay protection devices, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the method for centralized detection of abnormal settings in relay protection devices as proposed in the above embodiment.

[0115] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements a method for centralized detection of abnormal settings in relay protection devices as proposed in the above embodiments.

[0116] The storage medium proposed in this embodiment and the method for implementing centralized detection of abnormal settings of relay protection devices proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0117] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0118] 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 preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for centralized detection of abnormal settings in relay protection devices, characterized in that: include, The setpoint data is obtained from multiple protection devices through a substation. The setpoint data includes first setpoint data obtained through a communication interface call and second setpoint data obtained through a printing interface. The first fixed value data and the second fixed value data are respectively normalized to generate a first fixed value measurement point dataset and a second fixed value measurement point dataset; Obtain the set value notification data and parse it into set value reference data, then bind the set value reference data to the protection device; The first fixed value measurement point dataset and the second fixed value measurement point dataset are matched and compared with the fixed value reference data respectively. When the fixed value measurement point data is inconsistent with the fixed value reference data, an anomaly alarm message is generated. Determine whether the comparison results based on the first fixed-value measurement point dataset and the comparison results based on the second fixed-value measurement point dataset are consistent. If they are inconsistent, output a data source abnormality alarm.

2. The method for centralized detection of abnormal settings in relay protection devices as described in claim 1, characterized in that: The step of normalizing the first fixed-value data and the second fixed-value data to generate the first fixed-value measurement point dataset and the second fixed-value measurement point dataset includes: Obtain the substation identification information and protection device identification information corresponding to the set value data, perform source tracing and annotation processing on the set value data, and generate set value measurement point data containing data source information; The completeness of the setpoint measurement data is verified by referring to the setpoint benchmark data. If the setpoint measurement data is incomplete, the setpoint data of the protection device is re-acquired. The data of the fixed-value measurement points that have passed the verification are processed to standardize the data format and generate a fixed-value measurement point dataset.

3. The method for centralized detection of abnormal settings in relay protection devices as described in claim 2, characterized in that: The process of tracing and labeling the fixed-value data to generate fixed-value measurement point data containing data source information includes: Data source tags are generated based on substation identification information and protection device identification information, respectively; Write the generated data source labels into the data structure of the fixed value data to establish a mapping relationship between the fixed value data and the data source; Based on the established mapping relationship, the fixed value measurement point data is output. The data structure of the fixed value measurement point data includes a data source identifier field and a fixed value information field.

4. The method for centralized detection of abnormal settings in relay protection devices as described in claim 3, characterized in that: The standardization of the data format of the verified fixed-value measurement points includes: Extract the names of all setpoints from the setpoint data within the same protection device and create a setpoint name index table; Based on the defined value name index table, detect whether there are duplicate defined value names; When duplicate value names are detected, the data type of the corresponding value item is identified, and the duplicate value names are distinguished and marked according to the difference in data type.

5. The method for centralized detection of abnormal settings in relay protection devices as described in claim 4, characterized in that: The standardization of the data format of the verified fixed-value measurement point data also includes: Obtain the current unit of the fixed value item of the fixed value measurement point data, and determine the preset reference unit system; Calculate the unit conversion factor based on the dimensional relationship between the current unit and the corresponding reference unit in the reference unit system; The constant value of the constant value item is numerically converted according to the unit conversion factor to generate a constant value using the reference unit.

6. The method for centralized detection of abnormal settings in relay protection devices as described in claim 5, characterized in that: The step of binding the setpoint reference data with the protection device includes: Based on the protection device identification information contained in the setting reference data, the corresponding protection device is retrieved, and the setting measurement point dataset of the protection device is obtained. Establish a binding relationship between the fixed value items of the fixed value benchmark data and the fixed value measurement point data in the fixed value measurement point dataset; Verify whether the fixed value items of the fixed value benchmark data and the fixed value measurement point data have been bound item by item. If there are any data items that have not been bound, generate a binding error flag.

7. The method for centralized detection of abnormal settings in relay protection devices as described in claim 6, characterized in that: The step of matching and comparing the first fixed-value measurement point dataset and the second fixed-value measurement point dataset with the fixed-value benchmark data includes: Perform a string-complete match between the name of the fixed value item in the fixed value benchmark data and the name of the fixed value in the fixed value measurement point data. If the strings are completely identical, the match is considered successful. When a complete string match fails, extract the value item name and the feature characters in the value name, and perform fuzzy matching based on the degree of repetition of the feature characters; When fuzzy matching fails, semantic matching is performed on the fixed value name and the fixed value name based on preset semantic association rules.

8. A system for centralized detection of abnormal settings in relay protection devices, employing the method for centralized detection of abnormal settings in relay protection devices as described in any one of claims 1 to 7, characterized in that, include: The data acquisition module is used to acquire setpoint data, including first setpoint data and second setpoint data, from multiple protection devices through a substation; The normalization processing module is used to normalize the first fixed value data and the second fixed value data respectively, and generate a first fixed value measurement point dataset and a second fixed value measurement point dataset. The setting value processing module is used to acquire setting value notification data and parse it into setting value reference data, and to bind the setting value reference data with the protection device; The matching and comparison module is used to match and compare the first fixed value measurement point dataset and the second fixed value measurement point dataset with the fixed value reference data, respectively. The result verification module is used to determine whether the comparison results based on two fixed-value measurement point datasets are consistent, and to generate anomaly alarm information and data source anomaly alarm.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method for centralized detection of abnormal settings of a relay protection device as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for centralized detection of abnormal settings of a relay protection device as described in any one of claims 1 to 7.

Images