Intelligent substation configuration file comparison method and system

Abstract

The invention relates to the technical field of intelligent substations, in particular to an intelligent substation configuration file comparison method and system. The method comprises the following steps: analyzing a configuration file of an intelligent substation to generate a logic connection diagram of a virtual secondary circuit between IED equipment; verifying the correctness of the network connection and the logic relationship between the IED devices in the logic connection diagram by using a fuzzy matching algorithm; in response to verification correctness, determining the similarity between the two configuration files to be compared; and determining the similarity degree of the configuration files according to the relationship between the similarity and a set threshold value. According to the invention, the efficiency and accuracy of intelligent substation configuration file comparison can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart substations, and more specifically, to a method and system for comparing configuration files of smart substations. Background Art

[0002] The operation safety of smart substations is closely related to the safety of operation and maintenance personnel and the operation safety of power grids. At present, through the research on the models and configuration files of smart substations, the development and application of a series of management software such as version control, text comparison, and downloading of configuration files of SCD files (Substation Configuration Description, the whole station system configuration file) have been realized. Among them, the SCD configuration file is instantiated by the whole station ICD file (IEDCapability Description, intelligent device function description file), which contains the communication parameters and data information flow between devices, and is used to describe the relevant information association between the secondary devices of the smart substation. Furthermore, the SCD file is split to form the CID file (Configured IED Description, configured intelligent electronic device description file) used by each IED device (Intelligent Electronic Devices).

[0003] During the construction, expansion, operation and maintenance of smart substations, if any file is changed, it may affect the normal operation of the IED device and thus the operation of the smart substation. Such changes are often invisible and difficult to identify. In addition, these files have many formats and complex content nodes. Manual verification of files using text comparison tools is difficult, has a high error rate and is inefficient, especially when verifying all station configuration files at the same time.

[0004] Therefore, how to improve the efficiency and accuracy of configuration file comparison in smart substations is an urgent problem that needs to be solved. Summary of the invention

[0005] In order to solve the technical problems of low efficiency and low accuracy in configuration file comparison of the above-mentioned smart substation, the present invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides a method for comparing configuration files of a smart substation, comprising:

[0007] Parse the configuration file of the smart substation to generate a logical connection diagram of the virtual secondary circuits between IED devices;

[0008] Verifying the correctness of the network connection and logical relationship between the IED devices in the logical connection diagram by using a fuzzy matching algorithm;

[0009] In response to the verification being correct, determining a similarity between the two configuration files to be compared;

[0010] The similarity of the configuration files is determined according to the relationship between the similarity and a set threshold.

[0011] Furthermore, parsing the configuration file of the smart substation includes: parsing the configuration file based on a graph search algorithm.

[0012] Furthermore, the graph search algorithm is a depth-first search algorithm or a breadth-first search algorithm.

[0013] Furthermore, the correctness of the network connection and the logical relationship between the IED devices in the logical connection diagram is verified by using a fuzzy matching algorithm, including:

[0014] Establish a standard model library of network connections and logical relationships between IED devices;

[0015] Based on the fuzzy matching algorithm, the logical connection diagram is matched and verified with the standard model library.

[0016] Furthermore, determining the similarity between two configuration files to be compared includes: determining the similarity based on a Jaccard coefficient.

[0017] Further, determining the similarity based on the Jaccard coefficient includes:

[0018] Preprocessing and feature extraction are performed on the two configuration files to be compared to obtain two corresponding sets;

[0019] The similarity between the two sets is calculated based on the Jaccard coefficient.

[0020] Furthermore, the preprocessing includes: removing comments, removing blank lines, and standardizing naming.

[0021] Furthermore, the calculation expression of the Jaccard coefficient is:

[0022]

[0023] Where J(A,B) represents the similarity between set A and set B, and W(i) is the weight of element i.

[0024] Further, determining the similarity of the configuration files according to the relationship between the similarity and a set threshold value includes:

[0025] In response to the similarity being greater than a first threshold, merging or synchronously updating the two configuration files;

[0026] In response to the similarity being less than a second threshold, outputting a comparison result.

[0027] In a second aspect, the present invention provides a smart substation configuration file comparison system, comprising a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a smart substation configuration file comparison method according to the first aspect is implemented.

[0028] The beneficial effect of the present invention is that the method of the present invention verifies the accuracy of the configuration files before comparing the two configuration files, thereby avoiding the interference of erroneous information on the comparison process, thereby improving the accuracy of the configuration file comparison of the smart substation. In addition, since the two files are automatically compared, the problems of high error rate and low efficiency caused by manual comparison are avoided, thereby improving the efficiency and accuracy of the configuration file comparison. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0030] Figure 1 is a flow chart schematically illustrating a method for comparing configuration files of a smart substation according to an embodiment of the present invention;

[0031] Figure 2 FIG. 4 is a block diagram schematically showing a structure of a smart substation configuration file comparison system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0033] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0034] Figure 1 FIG. 4 is a flow chart schematically illustrating a method for comparing configuration files of a smart substation according to an embodiment of the present invention.

[0035] In a first aspect, the present invention provides a method for comparing configuration files of a smart substation, such as Figure 1 As shown, the method of the present invention comprises:

[0036] S101. Parse the configuration file of the smart substation to generate a logical connection diagram of the virtual secondary circuits between IED devices.

[0037] It is understandable that the configuration files of smart substations include ICD files, SCD files, and CID files. Among them, the ICD file describes the functions of the intelligent electronic device IED. The ICD files of different types of IED devices are instantiated to form the SCD file that describes the behavior and logical connection of all the intelligent devices in the station. The SCD file is split to form the CID file used by each IED device.

[0038] In one embodiment, the configuration file of the smart substation can be intelligently parsed by an association search algorithm based on graph theory (i.e., a graph search algorithm), and a logical connection diagram of the virtual secondary circuits between IED devices is generated after parsing. It can be understood that in graph theory, a graph is composed of nodes (or vertices) and edges. Among them, nodes represent objects, and edges represent the relationship between objects. According to the directionality of the edges, graphs can be divided into directed graphs (i.e., edges have directions) and undirected graphs (i.e., edges have no directions).

[0039] In addition, in the power system, the secondary circuit is a circuit that monitors, controls, regulates and protects the working status of the primary equipment (equipment in the primary circuit), while the virtual secondary circuit is a logical path for transmitting data signals for protection, measurement, control and monitoring between IED devices through data communication networks and protocols.

[0040] In one embodiment, the graph-theory-based association search algorithm used can be a depth-first search algorithm (DFS) or a breadth-first search algorithm (BFS), and those skilled in the art can choose according to actual needs. Among them, the DFS algorithm mainly traverses along the depth direction of the tree or graph, searching branches as deeply as possible until reaching a leaf node or backtracking after meeting specific conditions. The BFS algorithm searches layer by layer in a hierarchical order, first visiting the node closest to the starting node, and then expanding outward in sequence. The BFS algorithm is more suitable for use in a configuration file with a hierarchical structure.

[0041] In this embodiment, the configuration file of the smart substation can be parsed according to the DFS algorithm based on graph theory. Specifically, based on the configuration file of the smart substation, each endpoint and connection part of the virtual secondary circuit is used as the node and edge in the graph. Starting from the starting node, the DFS algorithm deeply explores each possible connection path and records the connection order and relationship between the nodes, thereby gradually constructing a logical connection graph.

[0042] By using the graph-based depth-first search algorithm to intelligently parse the configuration files of the smart substation, the legitimacy of the virtual terminals (interfaces for data exchange through the communication network) can be quickly and accurately detected, and a logical connection diagram of the virtual secondary circuits between IED devices can be generated. For illegal virtual terminals detected, feedback can be given in a timely manner so that the operation and maintenance personnel can handle them, thereby ensuring the safety and stability of the operation of the smart substation.

[0043] S102: Verify the correctness of the network connection and logical relationship between the IED devices in the logical connection diagram using a fuzzy matching algorithm.

[0044] In one embodiment, a standard model library of network connection relationships and logical relationships between IED devices can be established based on the "six unified" standards. Specifically, the content in the "six unified" standards is mapped into a standard model library, which needs to be associated with the actual loop model, including GOOSE transmission and reception, SV transmission and reception, etc.

[0045] It is understandable that the "six unified" standards unify the types, voltage levels, wiring methods, data sets, virtual terminal connection relationships, and pressure plate settings of IED devices, so that IED devices from different manufacturers can follow the same standards in network connections and logical relationships, thereby achieving interoperability and seamless system integration. Therefore, the standard model library established based on the "six unified" standards has a wide range of applications and can be applied to different configuration files when matching.

[0046] Furthermore, according to the fuzzy matching algorithm, the generated logical connection diagram is matched and verified one by one with the standard model library. Especially for the virtual terminal connection problem, each virtual terminal between IED devices must be checked against the standard model library item by item to ensure the correctness and consistency of the virtual terminal connection. Furthermore, in the case of no successful matching or matching failure, timely feedback is given to the operation and maintenance personnel for modification, and then verification is performed again after modification to ensure the accuracy and reliability of the configuration file, thereby ensuring the safe and stable operation of the smart substation and the accuracy of the subsequent determination of the similarity between the two configuration files.

[0047] By verifying the accuracy and reliability of the configuration file, the interference caused by erroneous information in the configuration file during the configuration file comparison is avoided, thereby improving the accuracy of the subsequent determination of the similarity between the two configuration files. At the same time, the smart substation using the modified correct configuration file can operate safely and reliably, thereby improving the stability and safety of the operation of the smart substation.

[0048] In addition, by adopting the fuzzy matching algorithm, it is possible to avoid misjudging essentially the same connection relationship or logical relationship into different situations when matching the logical connection diagram with the standard model library, thereby causing the problem of low verification accuracy. It is understandable that this situation may be caused by the use of words with the same semantics but different expressions, such as GOOSE input virtual terminals and GOOSE receiving virtual terminals, which have the same meaning but are not the same in description. They are generally caused by different personnel making configuration files. In addition, such words with the same semantics but different expressions are more common in the field of smart substations. Therefore, by using the fuzzy matching algorithm, the probability of this situation occurring can be reduced, thereby improving the accuracy of the verification. In addition, since the above-mentioned process of verifying the diagram is automatic, the problems of high error rate and low accuracy in manual verification are avoided, and the efficiency of verification is improved.

[0049] S103: In response to the verification being correct, determine the similarity between the two configuration files to be compared.

[0050] In one embodiment, the similarity between the two configuration files can be determined by the Jaccard coefficient, thereby identifying the changed parts. Specifically, the two configuration files to be compared that are verified to be correct are preprocessed to ensure that the two configuration files to be compared can be in the same format and structure, so as to subsequently calculate the similarity between the two configuration files, while avoiding interference caused by different formats or structures in determining the similarity. In other optional embodiments, those skilled in the art can select a suitable algorithm to calculate the similarity between the two configuration files according to actual needs.

[0051] It should be noted that the two configuration files can be files of the same type, such as SCD files and SCD files, or files of different types, such as SCD files and CID files. Those skilled in the art can compare different configuration files according to different requirements, which is highly flexible. It can be understood that the comparison of files of the same type can be a comparison before and after a change, and files of different types can be files that have not changed. Among them, when comparing the SCD file with the CID file, a mapping relationship between the IED device corresponding to the CID file and the IED device in the SCD file can be established to achieve the comparison of the SCD file with the CID file.

[0052] In one embodiment, the preprocessing of the configuration file includes removing comments, removing blank lines or spaces, normalizing the naming, etc. By preprocessing the configuration file, the interference of redundant information on the calculation of the similarity between two configuration files can be reduced, thereby improving the accuracy of the obtained similarity. In one embodiment, redundant information such as blank lines and comment statements in the configuration file can be found and removed by a character recognition tool. In other optional embodiments, those skilled in the art can choose a way to remove redundant information in the configuration file according to actual needs.

[0053] Furthermore, key information (i.e., feature extraction) is extracted from the preprocessed configuration file, such as configuration item names, parameter values, etc., and then two corresponding sets are formed. These two sets will be used for subsequent Jaccard coefficient calculations.

[0054] Specifically, according to the definition and formula of the Jaccard coefficient, the similarity between the two sets is calculated. Specifically, the sizes of the intersection and the union of the two sets are calculated respectively, and then the ratio of the intersection to the union is calculated, and the ratio is the similarity of the corresponding two configuration files.

[0055] Among them, the calculation expression of Jaccard coefficient is:

[0056]

[0057] Where J(A,B) represents the similarity between set A and set B, J(A,B)∈[0,1], |A∩B| represents the number of common elements between set A and set B, and |A∪B| represents the total number of elements contained in set A and set B.

[0058] In one embodiment, when determining the union and intersection between two sets, a fuzzy matching algorithm can be applied to avoid essentially the same element being mistaken for a different element (i.e., words with the same semantics but different expressions, for example, element a1 in set A is an SMV virtual terminal, and element b1 in set B is an SV virtual terminal, both of which are essentially the same), thereby causing two configuration files that originally had a high degree of similarity to obtain a low degree of similarity after calculation. Therefore, through the fuzzy matching algorithm, the union and intersection of two sets can be determined quickly, efficiently, and accurately, thereby improving the accuracy and reliability of the subsequent calculation of the similarity between the two sets.

[0059] In other optional embodiments, a standard vocabulary library may also be established, which includes all words with the same semantics but different expressions in the field of smart substations. Words with the same semantics but different expressions can be mapped to the same preset word, and then the extracted key information is matched with the vocabulary library in turn. For successful matches, they are converted into the preset words, thereby improving the accuracy of the determined intersection and union.

[0060] It is understandable that, during the calculation process, corresponding processing schemes can be set for empty sets or special cases to ensure the accuracy of the calculation results. Specifically, when both sets are empty sets, the similarity between the two sets is set to 1; when one of the two sets is an empty set and the other is not an empty set, the similarity between the two sets is set to 0.

[0061] In one embodiment, different weights can also be matched to each IED device, virtual terminal connection, parameter, etc. according to the criticality or complexity of each IED device to the safe and reliable operation of the smart substation. For example, the weight of the main transformer is set to 0.3 (high criticality, high complexity), the weight of the circuit breaker is set to 0.2 (high criticality, medium complexity), the weight of the disconnector is set to 0.1 (medium criticality, low complexity), etc.; further, the weight of the connection between the main transformer and the circuit breaker is set to 0.2 (high criticality, medium complexity), the weight of the connection between the circuit breaker and the disconnector is set to 0.1 (medium criticality, low complexity), etc., and accordingly, the parameters can also be set with different weights.

[0062] In addition, you can also find parts that are more likely to change or cause problems based on historical configuration file changes, and assign higher weights to these parts that are more likely to change or cause problems.

[0063] Specifically, after assigning weights to each part, the calculation expression of the Jaccard coefficient can be:

[0064]

[0065] Where J(A,B) represents the similarity between set A and set B, J(A,B)∈[0,1], W(i) is the weight of element i, ∑ i∈A∩B W(i) represents the sum of the weights of the elements shared by set A and set B, ∑ i∈A∪B W(i) represents the sum of the weights of the total elements contained in set A and set B, ∑ i∈A W(i) represents the sum of the weights corresponding to the elements in set A, ∑ i∈B W(i) represents the sum of the weights corresponding to the elements in set B.

[0066] It can be understood that, during the calculation process, the processing in the previous embodiment can be maintained for an empty set or special cases to ensure the accuracy of the calculation results.

[0067] By assigning different weights to different devices and connection relationships, the obtained similarity is more targeted, more in line with actual application scenarios, and more focused on the key factors affecting the safe and reliable operation of smart substations. When the differences in these key factors are too large, corresponding processing (such as key analysis) can be taken in time to avoid problems in the subsequent operation of smart substations, thereby improving the safety and reliability of the operation of smart substations.

[0068] S104: Determine the similarity of the configuration files according to the relationship between the similarity and a set threshold.

[0069] Specifically, according to the obtained similarity, the similarity between the two configuration files can be evaluated, so as to take corresponding measures. Specifically, in response to the similarity between the two configuration files being greater than a first threshold, the two configuration files are merged or synchronously updated; in response to the similarity between the two configuration files being less than a second threshold, the comparison result is output.

[0070] In one embodiment, the first threshold value may be set to 0.9, and the second threshold value may be set to 0.5. It is understandable that when the similarity between two configuration files is closer to 1, the two configuration files are more similar. In this embodiment, when the similarity between two configuration files is greater than 0.9, the two files may be merged or updated synchronously; when the similarity between two configuration files is closer to 0, the difference between the two configuration files is greater. In this embodiment, when the similarity between two configuration files is less than 0.5, the difference between the two files may be marked and output in the form of a report, thereby helping operation and maintenance personnel to quickly locate and process the differences in configuration files, thereby improving the accuracy and efficiency of maintenance.

[0071] In other optional embodiments, the first threshold may also be set to 0.95, and the second threshold may also be set to 0.6. Those skilled in the art may set them according to actual needs.

[0072] Figure 2 FIG. 4 is a block diagram schematically showing a structure of a smart substation configuration file comparison system according to this embodiment.

[0073] In a second aspect, the present invention also provides a smart substation configuration file comparison system. Figure 2As shown, the smart substation configuration file comparison system includes a processor and a memory, the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a smart substation configuration file comparison method according to the first aspect of the present invention is implemented.

[0074] The smart substation configuration file comparison system also includes other components well known to those skilled in the art, such as a communication interface, and the configuration and functions of the components are known in the art, so they will not be described in detail here.

[0075] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus or device. For example, a computer-readable storage medium may be any suitable magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that may be used to store the required information and may be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device. Any application or module described in the present invention may be implemented using computer-readable / executable instructions that may be stored or otherwise maintained by such a computer-readable medium.

[0076] In the description of this specification, “plurality” means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0077] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A method for comparing configuration files of a smart substation, characterized in that: include: Parse the configuration file of the smart substation to generate a logical connection diagram of the virtual secondary circuits between IED devices; Verifying the correctness of the network connection and logical relationship between the IED devices in the logical connection diagram by using a fuzzy matching algorithm; In response to the verification being correct, determining a similarity between the two configuration files to be compared; The similarity of the configuration files is determined according to the relationship between the similarity and a set threshold.

2. The smart substation configuration file comparison method according to claim 1 is characterized in that: Parsing a configuration file of a smart substation includes: parsing the configuration file based on a graph search algorithm.

3. The intelligent substation configuration file comparison method according to claim 2 is characterized in that: The graph search algorithm is a depth-first search algorithm or a breadth-first search algorithm.

4. The smart substation configuration file comparison method according to claim 1 is characterized in that: The correctness of the network connection and the logical relationship between the IED devices in the logical connection diagram is verified by using a fuzzy matching algorithm, including: Establish a standard model library of network connections and logical relationships between IED devices; Based on the fuzzy matching algorithm, the logical connection diagram is matched and verified with the standard model library.

5. The smart substation configuration file comparison method according to claim 1, characterized in that: Determining the similarity between two configuration files to be compared includes: determining the similarity based on a Jaccard coefficient.

6. The method for comparing configuration files of smart substations according to claim 5, characterized in that: Determining the similarity based on the Jaccard coefficient includes: Preprocessing and feature extraction are performed on the two configuration files to be compared to obtain two corresponding sets; The similarity between the two sets is calculated based on the Jaccard coefficient.

7. The intelligent substation configuration file comparison method according to claim 6 is characterized in that: The preprocessing includes: removing comments, removing blank lines, and normalizing names.

8. The method for comparing configuration files of smart substations according to claim 6, characterized in that: The calculation expression of the Jaccard coefficient is: Where J(A,B) represents the similarity between set A and set B, and W(i) is the weight of element i.

9. The method for comparing configuration files of smart substations according to claim 1, characterized in that: Determining the similarity of the configuration files according to the relationship between the similarity and a set threshold value includes: In response to the similarity being greater than a first threshold, merging or synchronously updating the two configuration files; In response to the similarity being less than a second threshold, outputting a comparison result.

10. A smart substation configuration file comparison system, characterized in that: It comprises a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a smart substation configuration file comparison method according to claims 1-9 is implemented.

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