Intelligent identification method and system for electric power secondary equipment based on digital model

Abstract

The invention provides an electric power secondary equipment intelligent identification method and system based on a digital model, and the method comprises the steps: building a digital model of a transformer substation, and enabling the digital model to define secondary equipment, primary equipment and a topological connection relation between the secondary equipment and the primary equipment; screening out target secondary equipment from the digital model based on a preset equipment type set; traversing an associated topology path of the target secondary equipment in the digital model to determine functional attributes of the target secondary equipment and / or associated primary equipment; classifying the target secondary equipment into a predefined equipment sub-type based on the functional attribute; and calling a naming rule template corresponding to the device sub-type, and generating a standardized name of the target secondary device. The intelligent level and efficiency of operation and maintenance management of the power system can be remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of secondary equipment identification technology, and in particular to an intelligent identification method and system for power secondary equipment based on a digital model. Background Technology

[0002] In the field of power system operation and maintenance management, accurate identification and standardized naming of substation secondary equipment are fundamental to ensuring the safe and efficient operation of the system. Currently, this process relies heavily on manual labor. Engineers need to consult numerous design drawings and circuit manuals, analyze the connections between equipment based on personal experience to determine their functions, and then manually name them. This method is not only inefficient and prone to errors, but also difficult to adapt to the increasingly complex architecture of smart substations, resulting in chaotic equipment records and high operation and maintenance costs, which has become a bottleneck restricting the digital transformation and upgrading of power systems.

[0003] Current technologies lack a systematic method for automatically resolving equipment topology relationships and intelligently identifying their functions. While some digital models exist to describe substation equipment, they primarily focus on data storage and display, failing to deeply mine the topological connection information contained within the models to achieve automatic reasoning and standardized naming of equipment functions. Therefore, there is an urgent need for an intelligent solution capable of automatically traversing topological paths, identifying functions based on rules, and generating standardized names to overcome the limitations of manual processing and improve the level of intelligence in power grid management. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for intelligent identification of secondary power equipment based on a digital model, aiming to solve at least one of the problems in the background art.

[0005] In a first aspect, the present invention provides a method for intelligent identification of secondary power equipment based on a digital model, the method comprising:

[0006] A digital model of the substation is constructed, which defines the secondary equipment, primary equipment, and the topological connections between them;

[0007] Based on a preset set of equipment types, target secondary equipment is selected from the digital model;

[0008] Traverse the associated topology path of the target secondary device in the digital model to determine its functional attributes and / or associated primary devices;

[0009] Based on the aforementioned functional attributes, the target secondary device is categorized into a predefined device subtype;

[0010] The naming rule template corresponding to the device subtype is invoked to generate a standardized name for the target secondary device.

[0011] In some embodiments, the step of traversing the associated topology path of the target secondary device in the digital model includes:

[0012] Starting from the target secondary device, a breadth-first or depth-first path search is performed along its electrical connections to discover all directly or indirectly related smart devices and primary devices.

[0013] In some embodiments, the step of determining its functional attributes and / or the associated primary device includes:

[0014] The device types and loop signal properties found in the associated topology path are matched with a predefined functional feature library, which defines the standard functions corresponding to different combinations of devices and loops.

[0015] In some embodiments, the step of classifying the target secondary device into a predefined device subtype includes:

[0016] A rule-based classifier is applied, the input of which includes the functional attribute and the associated primary device type, and the output is the corresponding device subtype.

[0017] In some embodiments, the rule-based classifier performs the following steps:

[0018] If the target secondary device is a pressure plate and its functional attribute is an enable / disable protection function, then it is classified as a protection function pressure plate subtype.

[0019] If its functional attribute is to switch operation modes, then it is classified as a control mode pressure plate type.

[0020] In some embodiments, the step of calling the naming rule template corresponding to the device subtype to generate the normalized name of the target secondary device includes:

[0021] Based on the device subtype, the corresponding name format string is retrieved from a configuration mapping table. The string contains placeholders for voltage level, function description, and location.

[0022] The functional attributes, the associated primary device identifier, and the cabinet information where the target secondary device is located are filled into the corresponding placeholders of the naming rule template to synthesize the final name.

[0023] Secondly, the present invention provides an intelligent identification system for secondary power equipment based on a digital model, the system comprising:

[0024] The model building module is used to build a digital model of the substation, which defines the secondary equipment, primary equipment and their topological connections.

[0025] The equipment screening module is used to screen out target secondary equipment from the digital model based on a preset set of equipment types;

[0026] The traversal module is used to traverse the associated topology path of the target secondary device in the digital model to determine its functional attributes and / or associated primary devices.

[0027] The type classification module is used to classify the target secondary device into a predefined device subtype based on the functional attributes.

[0028] The name generation module is used to call the naming rule template corresponding to the device subtype to generate a standardized name for the target secondary device.

[0029] Thirdly, the present invention provides a storage medium that stores one or more programs, which, when executed by a processor, implement the above-described intelligent identification method for power secondary equipment based on a digital model.

[0030] Fourthly, the present invention provides an electronic device, the electronic device comprising a memory and a processor, wherein:

[0031] The memory is used to store computer programs;

[0032] When the processor executes the computer program stored in the memory, it implements the above-mentioned intelligent identification method for power secondary equipment based on a digital model.

[0033] Compared with the prior art, the present invention has the following advantages:

[0034] This invention addresses the industry pain points of current substation secondary equipment function identification and naming, which relies on manual experience, is inefficient, and lacks standardized practices. It proposes an intelligent solution based on a digital model. This solution systematically constructs a digital model containing primary and secondary equipment and their topological connections. It automatically traverses and analyzes the associated paths of target equipment to determine its functional attributes. Based on predefined classification rules and naming templates, it ultimately achieves accurate subtyping of equipment and automatic generation of standardized names, thereby significantly improving the intelligence level and efficiency of power system operation and maintenance management. Attached Figure Description

[0035] Figure 1 This is a flowchart of a method for intelligent identification of secondary power equipment based on a digital model, proposed in an embodiment of the present invention.

[0036] Figure 2 This is a schematic diagram of the structure of an intelligent identification system for secondary power equipment based on a digital model, as proposed in an embodiment of the present invention.

[0037] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Unless otherwise defined, the technical or scientific terms used herein should have the ordinary meaning understood by those skilled in the art. The terms "comprising" and similar expressions used herein mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, but does not exclude other elements or objects.

[0039] like Figure 1 As shown, an embodiment of the present invention proposes an intelligent identification method for secondary power equipment based on a digital model. The method includes steps S101 to S105, wherein:

[0040] Step S101: Construct a digital model of the substation, wherein the digital model defines the secondary equipment, primary equipment and the topological connection relationships between them;

[0041] In this step, static parameters (such as model and rated parameters) and dynamic operating data (such as real-time status signals and communication protocol data) of primary equipment (such as transformers, circuit breakers, and busbars) and secondary equipment (such as relay protection devices, monitoring and control devices, and sensors) of the substation are collected. A digital model of the substation is then constructed using 3D modeling tools or graph database technology. This model defines equipment nodes (primary and secondary equipment) and edges (topological connections) in a graph structure. Edge attributes include electrical connection type (such as cable or fiber optic cable), communication protocol type (such as IEC 61850 or Modbus), and signal flow direction.

[0042] Step S102: Based on the preset set of equipment types, select the target secondary equipment from the digital model;

[0043] It should be noted that the equipment type field is extracted from the digital model and matched with a preset set of equipment types (such as "line protection device", "busbar monitoring and control device", "fault recorder", etc.) to filter out target secondary equipment that meets the conditions. The matching rules may include exact matching (such as the equipment model being exactly the same) or fuzzy matching (such as semantic matching based on keywords, such as matching all protection devices with the keyword "protection").

[0044] Step S103: Traverse the associated topology path of the target secondary device in the digital model to determine its functional attributes and / or associated primary devices;

[0045] It should be noted that in this step, starting from the target secondary device, a breadth-first or depth-first path search is performed along its electrical connections to discover all directly or indirectly related intelligent devices and primary devices. Then, the device types and loop signal properties discovered in the associated topology path are matched with a predefined functional feature library, which defines the standard functions corresponding to different combinations of devices and loops.

[0046] By employing breadth-first or depth-first path search algorithms, a systematic traversal of device relationships was achieved, ensuring that no critical connection information was overlooked, thus laying a complete data foundation for subsequent functional analysis. By establishing a predefined functional feature library and performing feature matching, complex loop analysis was transformed into a standardized pattern recognition problem, significantly improving the accuracy and consistency of functional attribute determination.

[0047] Step S104: Based at least on the functional attributes, classify the target secondary device into a predefined device subtype;

[0048] In this step, a rule-based classifier is applied. The input of the classifier includes the functional attribute and the associated primary device type, and the output is the corresponding device subtype. The rule-based classifier performs the following steps: if the target secondary device is a pressure plate and its functional attribute is an activation / deactivation protection function, then it is classified as a protection function pressure plate subtype; if its functional attribute is a switching operation mode, then it is classified as a control mode pressure plate subtype.

[0049] By introducing a rule-based classifier, multi-dimensional feature information is transformed into accurate equipment subtype determinations, thus automating and intelligentizing the classification process. Furthermore, specific rule examples demonstrate how the classifier achieves refined classification, effectively distinguishing different types of pressure plates and improving the granularity and professionalism of equipment management.

[0050] Step S105: Call the naming rule template corresponding to the device subtype to generate the standardized name of the target secondary device.

[0051] In this step, firstly, based on the device subtype, the corresponding name format string is retrieved from a configuration mapping table. The string contains placeholders for voltage level, function description, and location. Then, the function attribute, the associated primary device identifier, and the cabinet information where the target secondary device is located are filled into the corresponding placeholders of the naming rule template to synthesize the final name.

[0052] By configuring the mapping table and the placeholder filling mechanism, the naming process can be flexibly configured and automatically synthesized, which not only ensures the uniformity of naming conventions, but also meets the personalized needs of different scenarios.

[0053] In summary, the above-mentioned intelligent identification method for power secondary equipment based on a digital model systematically constructs a digital model containing primary equipment, secondary equipment, and their topological connections. It automatically traverses and analyzes the associated paths of target equipment to determine its functional attributes. Based on predefined classification rules and naming templates, it ultimately achieves accurate classification of equipment subtypes and automatic generation of standardized names, thereby significantly improving the intelligence level and efficiency of power system operation and maintenance management.

[0054] like Figure 2 As shown, one embodiment of the present invention proposes an intelligent identification system for secondary power equipment based on a digital model, the system comprising:

[0055] The model building module 10 is used to build a digital model of the substation, which defines the secondary equipment, primary equipment and their topological connections.

[0056] Equipment screening module 20 is used to screen target secondary equipment from the digital model based on a preset set of equipment types;

[0057] Traversal module 30 is used to traverse the associated topology path of the target secondary device in the digital model to determine its functional attributes and / or associated primary devices;

[0058] The type classification module 40 is used to classify the target secondary device into a predefined device subtype based at least on the functional attributes;

[0059] The name generation module 50 is used to call the naming rule template corresponding to the device subtype to generate a standardized name for the target secondary device.

[0060] In another aspect, the present invention also proposes a storage medium on which one or more programs are stored, which, when executed by a processor, implement the above-described intelligent identification method for power secondary equipment based on a digital model.

[0061] In another aspect, the present invention also proposes an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so as to realize the above-mentioned intelligent identification method for power secondary equipment based on a digital model.

[0062] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain stored, communicated, propagated, or transmitted programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0063] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0064] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0065] While embodiments of the present invention have been described in detail above, it will be apparent to those skilled in the art that various modifications and variations can be made to these embodiments. However, it should be understood that such modifications and variations fall within the scope and spirit of the invention as set forth in the claims. Furthermore, the invention described herein may have other embodiments and can be implemented or carried out in various ways.

Claims

1. A digital model-based intelligent identification method for power secondary equipment, characterized in that, The method comprises: constructing a digital model of the substation, the digital model defining secondary devices, primary devices and topological connection relationships therebetween; based on a preset device type set, screening a target secondary device from the digital model; traversing an associated topological path of the target secondary device in the digital model to determine a functional attribute and / or an associated primary device thereof; based on the functional attribute, classifying the target secondary device into a predefined device sub-type; calling a naming rule template corresponding to the device sub-type to generate a standardized name of the target secondary device. 2.The digital model-based power secondary device intelligent identification method according to claim 1, characterized in that, The step of traversing the associated topological path of the target secondary device in the digital model comprises: taking the target secondary device as a starting point, performing a breadth-first or depth-first path search along an electrical connection relationship thereof to discover all directly or indirectly associated intelligent devices and primary devices. 3.The digital model based power secondary device intelligent identification method of claim 2, wherein, The step of determining the functional attribute and / or the associated primary device comprises: matching a device type, a loop signal property discovered in the associated topological path with a predefined functional feature library, the functional feature library defining standard functions corresponding to different device and loop combinations.

4. The digital model-based power secondary device intelligent identification method according to claim 3, characterized in that, The step of classifying the target secondary device into a predefined device sub-type comprises: applying a rule-based classifier, an input of the classifier including the functional attribute and the associated primary device type, and an output being a corresponding device sub-type.

5. The digital model-based power secondary device intelligent identification method according to claim 4, characterized in that, The rule-based classifier performs the following steps: if the target secondary device is a pressure plate and the functional attribute thereof is a protection function switching function, then classifying the target secondary device into a protection function pressure plate sub-type; if the functional attribute thereof is a mode switching function, then classifying the target secondary device into a control mode pressure plate sub-type.

6. The digital model-based power secondary device intelligent identification method according to claim 5, characterized in that, The step of calling a naming rule template corresponding to the device sub-type to generate a standardized name of the target secondary device comprises: according to the device sub-type, retrieving a corresponding name format string from a configuration mapping table, the string including placeholders of voltage level, functional description and location; filling the functional attribute, the associated primary device identifier and cabinet information where the target secondary device is located into corresponding placeholders of the naming rule template to synthesize a final name.

7. A digital model-based intelligent identification system for power secondary equipment, characterized in that, The system comprises: a model construction module configured to construct a digital model of the substation, the digital model defining secondary devices, primary devices and topological connection relationships therebetween; a device screening module configured to screen a target secondary device from the digital model based on a preset device type set; a traversal module configured to traverse an associated topological path of the target secondary device in the digital model to determine a functional attribute and / or an associated primary device thereof; a type classification module configured to classify the target secondary device into a predefined device sub-type based on the functional attribute; a name generation module configured to call a naming rule template corresponding to the device sub-type to generate a standardized name of the target secondary device.

8. A storage medium, characterized by The storage medium stores one or more programs, which are executed by the processor to implement the digital model-based intelligent identification method of power secondary equipment according to any one of claims 1-6. 9.An electronic device, comprising a memory and a processor, wherein: the memory is configured to store a computer program; the processor is configured to execute the computer program stored in the memory to implement the digital model-based intelligent identification method of power secondary equipment according to any one of claims 1-6.

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