Measurement point standard model treatment method and system of electrical monitoring system

Abstract

The invention relates to the technical field of measuring point models, in particular to a method and system for treating a measuring point standard model of an electrical monitoring system, and the method comprises the steps: creating a template and defining a standard measuring point: creating an equipment classification coding template according to the type and function level of electrical equipment; performing management loop statistics and difference judgment: judging the semantic difference between the actual measurement point name and the standard measurement point name through a fuzzy matching algorithm, and generating a consistency judgment result; dynamic governance rule generation and exception handling: generating an ungoverned measuring point set, and adding ungoverned measuring points to the standard template; database cleaning and rule integration: matching the relationship between the measuring points and the equipment, modifying data substitutions and cleaning redundant measuring points; carrying out dynamic template loading and governance execution: carrying out template rule loading on all associated equipment or specified substations, and generating a governance effect evaluation report; according to the invention, the standardization degree of the measuring point data of the electrical monitoring system is improved, and a reliable data basis is provided for intelligent operation and maintenance and accurate monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of measuring point models, and in particular to a method and system for managing a measuring point standard model of an electrical monitoring system. Background Art

[0002] In modern electrical monitoring systems, standardized management of measurement point data is crucial to ensuring accurate monitoring of equipment status and intelligent operation and maintenance. However, due to the large differences in measurement point naming, data types, unit standards, etc. among different equipment manufacturers and different models of electrical equipment, measurement point data lacks a unified standard, affecting data compatibility and availability. In addition, traditional measurement point management methods mainly rely on manual configuration and maintenance, which is not only inefficient but also prone to problems such as missed measurement points, inconsistent names, and confusing units, thus affecting system reliability and data analysis accuracy.

[0003] In the existing technology, although there are some methods for standardized management of measurement point data, such as the measurement point mapping method based on fixed templates, it is difficult to adapt to the complex and changeable types of electrical equipment and their functional levels, and the compatibility with newly connected equipment is poor; at the same time, traditional methods lack intelligent analysis means in the management process, and cannot efficiently identify the semantic differences between measurement points, nor can they dynamically adjust the management rules to adapt to new or abnormal measurement points; in addition, after the long-term accumulation of measurement point data in the database, duplicate records, redundant data and missing values may be generated, further reducing the accuracy of the data and management efficiency. Therefore, there is an urgent need for a measurement point management system based on a standard model that can realize the automatic matching of equipment measurement points, data cleaning, rule optimization and management effect evaluation, so as to improve the intelligence level of the electrical monitoring system. Summary of the Invention

[0004] The invention provides a method for managing a standard model of measuring points of an electrical monitoring system.

[0005] A method for managing a measurement point standard model of an electrical monitoring system comprises the following steps:

[0006] S1, template creation and standard measurement point definition: Create equipment classification coding templates based on the type and functional level of electrical equipment. The equipment classification coding templates include equipment classification codes, loop templates, and full equipment templates. Generate standard measurement point information for each equipment classification coding template. The standard measurement point information includes the Chinese and English name, type, unit, and attributes of the measurement point, and is stored in the standardized measurement point database.

[0007] S2, Governance Loop Statistics and Difference Determination: Based on the equipment classification coding template and standard measurement point information, the total number of associated equipment and the number of ungoverned loops are counted. The semantic differences between the actual measurement point names and the standard measurement point names are determined through a fuzzy matching algorithm to generate a consistency determination result.

[0008] S3, dynamic governance rule generation and exception handling: Based on the consistency judgment results, a set of unmanaged measurement points is generated, the unmanaged measurement points are added to the standard template, and prompt information is generated for devices without measurement points and data is exported;

[0009] S4, database cleaning and rule integration: Match the relationship between measurement points and equipment according to the equipment data model, modify data aliases and clean redundant measurement points, including correcting units and filling missing values;

[0010] S5, dynamic template loading and governance execution: According to the selected loading mode, the template rules are fully or partially loaded to all related equipment or designated substations, the standardized governance of the measuring points is completed, and a governance effect evaluation report is generated.

[0011] Optionally, the S1 includes:

[0012] S11, Creation of Equipment Classification Coding Template: Based on the type and functional level of electrical equipment, equipment classification coding is defined using structured coding rules;

[0013] S12, loop template and full equipment template: The loop template is a measurement point set template defined according to the equipment loop, describing the standard measurement point information related to the loop;

[0014] S13, generation of standard measuring point information: the standard measuring point information includes the Chinese and English names, types, units and attributes of the measuring points, and is generated through a fuzzy matching algorithm;

[0015] S14, storing the standardized measuring point database: storing the generated standard measuring point information, including the Chinese and English names, types, units and attributes of the measuring points, in the standardized measuring point database.

[0016] Optionally, the S2 includes:

[0017] S21, Equipment Quantity and Circuit Statistics: Based on the equipment classification code template, count the total number of electrical equipment and the number of unmanaged circuits associated with the equipment classification code template;

[0018] S22, fuzzy matching judgment of semantic differences: similarity calculation is performed using a fuzzy matching algorithm, and a consistency judgment result is generated based on the calculation result.

[0019] Optionally, the S3 includes:

[0020] S31, generating an unmanaged measurement point set, and identifying measurement points that do not match the standard template in actual measurement points;

[0021] S32, expand the physical attributes and equipment classification of unmanaged measurement points and add them to the standard template;

[0022] S33, generating prompt information for the equipment without measurement points, and exporting relevant data of the abnormal equipment.

[0023] Optionally, in S31, an unregulated measurement point set is generated according to the consistency determination result.

[0024] Optionally, the S32 processes each measuring point in the unmanaged measuring point set according to its physical properties and device classification through governance rules, adds it to the standard template, and dynamically expands the physically defined analog parameters to generate expanded measuring point information.

[0025] Optionally, the step S33 generates prompt information for devices without measuring points that still lack measuring points, including device identification, device location, and missing measuring point information, and exports abnormal device data.

[0026] Optionally, the S4 includes:

[0027] S41, matching the relationship between measurement points and equipment: matching the measurement point set and the equipment set according to the equipment data model;

[0028] S42, filling in missing data and storing in database: filling in missing measurement point data.

[0029] Optionally, the S5 includes:

[0030] S51, determining the loading mode and selecting the target equipment: based on the loading mode selected by the user, determining the loading range, which includes the full loading mode and the partial loading mode, and selecting the target loading equipment;

[0031] S52, template rule loading: according to the loading target, extract the template rules applicable to the target device from the standard template database and load them into the measurement point data set of the corresponding device;

[0032] S53, executing measurement point standardization management and generating a management effect evaluation report: performing measurement point standardization management on the loaded template rules, calculating the measurement point standardization rate, and generating a management effect evaluation report.

[0033] A measuring point standard model management system for an electrical monitoring system, used to implement the above-mentioned measuring point standard model management method for an electrical monitoring system, includes the following modules:

[0034] Template management module: creates equipment classification coding templates based on the type and functional level of electrical equipment. The equipment classification coding templates include equipment classification codes, specific circuit templates, and full equipment templates. It also generates standard measurement point information and stores it in the standardized measurement point database.

[0035] Data analysis module: Counts the total number of associated devices and the number of unmanaged loops, and uses a fuzzy matching algorithm to determine the semantic differences between actual measurement point names and standard measurement point names, generating consistency determination results;

[0036] Governance rule generation module: Dynamically adjusts the governance rule set based on consistency determination results, adds unregulated measurement points to the standard template, generates prompt information and exports data for devices without measurement points, and expands physically defined analog parameters.

[0037] Database management module: matches the relationship between measurement points and equipment according to the equipment data model, and standardizes the measurement point data, including cleaning redundant measurement points, correcting units, and filling missing values;

[0038] Template loading and governance execution module: According to the selected loading mode, the template rules are fully or partially loaded to all related equipment or designated substations, the standardized governance of the measuring points is completed, and a governance effect evaluation report is generated.

[0039] Beneficial effects of the present invention:

[0040] The present invention provides a method and system for managing a standard model of measuring points in an electrical monitoring system. By establishing an equipment classification coding template and combining it with standard measuring point information, unified management of measuring points of different types of electrical equipment is achieved, effectively solving problems such as inconsistent measuring point names, confusing units, and heterogeneous data structures. Through a fuzzy matching algorithm, the semantic differences between actual measuring points and standard measuring points can be automatically identified, and management rules can be dynamically adjusted based on consistency judgment results, thereby improving the accuracy of measuring point matching. In addition, the present invention can automatically expand ungoverned measuring points and synchronize the management results to a standardized measuring point database, ensuring the integrity and standardization of measuring point data, reducing manual intervention, and improving the degree of automation of the system.

[0041] The present invention also features database cleaning and dynamic template loading capabilities, automatically identifying and cleaning redundant information, duplicate records, and missing values from measurement point data to ensure high-quality data storage and use. Furthermore, the present invention supports both full and partial loading modes, enabling the application of standard templates to all equipment or specific substations based on user needs, making the measurement point management process more flexible and efficient. Through management effect evaluation reports, the implementation of measurement point standardization can be quantified, providing data support for subsequent optimization of the electrical monitoring system. Overall, the present invention improves the standardization and management efficiency of measurement point data in the electrical monitoring system, enhances the system's intelligent management capabilities, and provides a reliable data foundation for intelligent operation and maintenance and precise monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 is a flow chart of a method according to an embodiment of the present invention;

[0044] Figure 2 2 is a system module diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is also noted that, to provide a more detailed description, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative methods for implementing certain known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0046] It should be noted that references in the specification to "one embodiment," "an embodiment," "an exemplary embodiment," "some embodiments," etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not every embodiment necessarily includes such specific features, structures, or characteristics. In addition, when specific features, structures, or characteristics are described in conjunction with an embodiment, it is within the knowledge of persons skilled in the relevant art to implement such features, structures, or characteristics in conjunction with other embodiments (whether or not explicitly described).

[0047] In general, terms can be understood, at least in part, from their use in context. For example, depending at least in part on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0048] like Figure 1 As shown, a method for managing a standard model of measurement points of an electrical monitoring system includes the following steps:

[0049] S1, template creation and standard measurement point definition: Create equipment classification coding templates based on the type and functional level of electrical equipment. Equipment classification coding templates include equipment classification coding, loop templates, and full equipment templates. Generate standard measurement point information for each equipment classification coding template. The standard measurement point information includes the Chinese and English name, type, unit, and attributes of the measurement point, and is stored in the standardized measurement point database.

[0050] S2, Governance Loop Statistics and Difference Determination: Based on the equipment classification coding template and standard measurement point information, the total number of associated equipment and the number of ungoverned loops are counted. The semantic differences between the actual measurement point names and the standard measurement point names are determined through a fuzzy matching algorithm to generate a consistency determination result.

[0051] S3, dynamic governance rule generation and exception handling: Based on the consistency judgment results, a set of unmanaged measurement points is generated, the unmanaged measurement points are added to the standard template, and prompt information is generated for devices without measurement points and data is exported;

[0052] S4, database cleaning and rule integration: Match the relationship between measurement points and equipment according to the equipment data model, modify data aliases and clean redundant measurement points, including correcting units and filling missing values;

[0053] S5, dynamic template loading and governance execution: According to the selected loading mode, the template rules are fully or partially loaded to all related equipment or designated substations, the standardized governance of the measuring points is completed, and a governance effect evaluation report is generated.

[0054] S1 includes:

[0055] S11, Creation of equipment classification coding template: Based on the type and functional level of electrical equipment, the equipment classification coding is defined using structured coding rules, expressed as:

[0056] C eq =C type ×10 n +C level ;

[0057] Among them, C eq For equipment classification code, C type The code is for the equipment type. Different types of electrical equipment are assigned unique code values (1 for power generation equipment, 2 for substation equipment, and 3 for transmission equipment). n is the number of digits at the equipment level. C level Encode the functional level of the device;

[0058] S12, loop template and full equipment template: The loop template is a measurement point set template defined according to the equipment's loop (voltage loop, current loop), describing the standard measurement point information related to the loop. The loop template encoding formula is expressed as:

[0059] C loop =C eq ×10 m +C sub ;

[0060] Among them, C loop is the loop template code, C sub It is the secondary code of the circuit, which is set according to the specific characteristics of the electrical circuit. m is the total number of devices in the circuit template.

[0061] S13, generation of standard measuring point information: The standard measuring point information includes the Chinese and English names, types, units and attributes of the measuring points, which are generated through fuzzy matching algorithms and expressed as:

[0062]

[0063] Among them, M is the matching degree of the measurement point name, and its value range is [0,1], S i is the i-th character in the standard measuring point name, W i is the weight of the i-th character in the standard measurement point name, which is usually determined according to the position or importance of the character in the word. j is the weight of the jth character in the actual measuring point name, k and l are the number of characters in the standard measuring point name and the actual measuring point name, respectively;

[0064] S14, storing the standardized measuring point database: storing the generated standard measuring point information, including the Chinese and English names, types, units and attributes of the measuring points, in the standardized measuring point database.

[0065] S2 includes:

[0066] S21, Equipment quantity and circuit statistics: According to the equipment classification code template, count the total number of electrical equipment associated with the equipment classification code template N total and the number of unmanaged circuits N ungoverned , expressed as:

[0067]

[0068] Among them, N total The total number of devices associated with the device classification coding template, E a Indicates the number of devices associated with the a-th device in the device classification code template, nz is the total number of device types, N ungoverned is the total number of unmanaged loops, U b Indicates the number of unmanaged circuits in the bth device, and mz is the total number of devices in the device classification coding template;

[0069] S22, fuzzy matching judgment of semantic differences: In order to determine the semantic differences between the actual measurement point name and the standard measurement point name, a fuzzy matching algorithm is used to calculate the similarity, and a consistency judgment result is generated based on the calculation result, which is expressed as:

[0070]

[0071] Among them, Sim(A,B) represents the similarity score between the actual measurement point name A and the standard measurement point name B, A c and B c The cth character in the actual measuring point name A and the standard measuring point name B, respectively, c is the weight of the cth character, ranging from [0,1], w d is the weight of the dth character, ranging from [0,1], p and q are the total number of characters in the names A and B respectively, δ(A c ,B c ) is the indicator function, when A c =B c When δ(A c ,B c )=1, otherwise δ(A c ,B c )=0, Consistency is the consistency judgment result. If it is 1, the measurement point names are consistent. If it is 0, the measurement point names are inconsistent. θ is the similarity threshold, and the value range is [0,1].

[0072] S3 includes:

[0073] S31, generating an unmanaged measurement point set, and identifying measurement points that do not match the standard template in actual measurement points;

[0074] S32, expand the physical attributes and equipment classification of unmanaged measurement points and add them to the standard template;

[0075] S33, generating prompt information for the equipment without measurement points, and exporting relevant data of the abnormal equipment.

[0076] In S31, an unmanaged measurement point set W is generated according to the consistency determination result. The unmanaged measurement points in the unmanaged measurement point set are the measurement points in the actual measurement point set that are not matched to the standard template set, and are expressed as:

[0077]

[0078] Among them, W represents the set of ungoverned measurement points, M f is the actual measurement point set, M s is the set of measurement points in the standard template, w e Represents a single unregulated point with index e.

[0079] S32 For each measurement point w in the unmanaged measurement point set W e , according to its physical properties p e and equipment classification c e , after being processed by governance rules, it is added to the standard template and the analog parameters of the physical definition are dynamically expanded to generate the expanded measurement point information w e ′, expressed as:

[0080] w e ′=g(p e ,c e );

[0081] Among them, w e ′ represents the expanded measurement point, and w represents the unmanaged measurement point. e After being processed by governance rules and added to the standard template, the new measurement points, including measurement point name standardization, unit conversion, physical property extension, data consistency verification and abnormal measurement point processing, are e is the measuring point w e The physical properties of e is the measuring point w e Equipment classification, g(p e ,c e ) represents a function that expands physical parameters based on physical properties and device classification.

[0082] S33 generates a prompt message P for the device without measuring points that still lacks measuring points. y , including device identification ID y , device location L y And the missing measurement point information U y , and export abnormal device data D y , expressed as:

[0083] P y =(ID y ,L y ,U y );

[0084] Among them, P y For prompt information, ID y is the device identifier, L y is the device location, U y Missing measurement point information.

[0085] S4 includes:

[0086] S41, matching the relationship between measurement points and equipment: According to the equipment data model, and matching the measurement point set M x With equipment collection E x , to ensure that the measurement points are correctly assigned, the matching rules are expressed as:

[0087]

[0088] The equipment data model includes equipment information, equipment measurement point information, measurement point mapping information, data verification information and equipment operation status. matched Represents the set of successfully matched measurement points, M x is the set of measurement points in the database, E x is the device set in the database, m x For a single measuring point, e x For a single device, is the measuring point m x With device e x Matching rule function;

[0089] S42, filling missing data and storing in database: Filling missing measurement point data, the filling value is calculated based on the historical data of similar measurement points, expressed as:

[0090]

[0091] Among them, V fi is the filling value, H mv is the historical data set of similar measurement points, v h The measured value in the historical data is the cleaned measurement point data M final Store in the database to complete database cleaning and rule integration.

[0092] S5 includes:

[0093] S51, determine the loading mode and select the target device: based on the loading mode M selected by the user mode , determine the loading range, the loading mode includes full loading mode and partial loading mode, in the full loading mode, all related equipment set E all As the loading target, in the local loading mode, only the specified substation set S sub To load the template, select the target loading device. The target loading device set is represented as:

[0094]

[0095] Among them, T target is the final selected loading object, M mode The loading mode selected by the user, E all Indicates all associated devices, S sub Represents a collection of equipment in a specified substation;

[0096] S52, template rule loading: according to the loading target T target , from the standard template database DB template The template rules applicable to the target device are extracted and loaded into the measurement point data set of the corresponding device. The loading rules are expressed as:

[0097] T applied ={t z |t z ∈DB template ∧t z ∈T target};

[0098] Among them, T applied is the final loaded template rule set, t z is the rule of the zth template, DB template is the standard template database, T target is the loading target;

[0099] S53, perform standardization management of measurement points and generate management effect evaluation report: for the loaded template rule T applied Carry out standardization management of measurement points and calculate the standardization rate R of measurement points std , and generate a governance effect evaluation report G eval , expressed as:

[0100]

[0101] G eval =f(R std ,M updated ,M error );

[0102] Among them, R std is the normalized rate of the measurement point, M std is the set of successfully standardized measurement points, M total is the total number of measurement points participating in standardization governance, G eval For the governance effect evaluation report, f(R std ,M updated ,M error ) is the evaluation report generation function, M updated This is the set of measurement points updated after loading.error It is a set of abnormal measurement points that cannot be standardized.

[0103] like Figure 2 As shown, a measurement point standard model management system for an electrical monitoring system is used to implement the above-mentioned measurement point standard model management method for an electrical monitoring system, including the following modules:

[0104] Template management module: Create equipment classification coding templates based on the type and functional level of electrical equipment. Equipment classification coding templates include equipment classification codes, specific circuit templates, and full equipment templates. It also generates standard measurement point information and stores it in the standardized measurement point database.

[0105] Data analysis module: Counts the total number of associated devices and the number of unmanaged loops, and uses a fuzzy matching algorithm to determine the semantic differences between actual measurement point names and standard measurement point names, generating consistency determination results;

[0106] Governance rule generation module: Dynamically adjusts the governance rule set based on consistency determination results, adds unregulated measurement points to the standard template, generates prompt information and exports data for devices without measurement points, and expands physically defined analog parameters.

[0107] Database management module: matches the relationship between measurement points and equipment according to the equipment data model, and standardizes the measurement point data, including cleaning redundant measurement points, correcting units, and filling missing values;

[0108] Template loading and governance execution module: According to the selected loading mode, the template rules are fully or partially loaded to all related equipment or designated substations, the standardized governance of the measuring points is completed, and a governance effect evaluation report is generated.

[0109] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0110] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for managing a standard model of measurement points in an electrical monitoring system, characterized in that: The following steps are involved: S1, template creation and standard measurement point definition: Create equipment classification coding templates based on the type and functional level of electrical equipment. The equipment classification coding templates include equipment classification codes, loop templates, and full equipment templates. Generate standard measurement point information for each equipment classification coding template. The standard measurement point information includes the Chinese and English name, type, unit, and attributes of the measurement point, and is stored in the standardized measurement point database. S2, Governance Loop Statistics and Difference Determination: Based on the equipment classification coding template and standard measurement point information, the total number of associated equipment and the number of ungoverned loops are counted. The semantic differences between the actual measurement point names and the standard measurement point names are determined through a fuzzy matching algorithm to generate a consistency determination result. S3, dynamic governance rule generation and exception handling: Based on the consistency judgment results, a set of unmanaged measurement points is generated, the unmanaged measurement points are added to the standard template, and prompt information is generated for devices without measurement points and data is exported; S4, database cleaning and rule integration: Match the relationship between measurement points and equipment according to the equipment data model, modify data aliases and clean redundant measurement points, including correcting units and filling missing values; S5, dynamic template loading and governance execution: According to the selected loading mode, the template rules are fully or partially loaded to all related equipment or designated substations, the standardized governance of the measuring points is completed, and a governance effect evaluation report is generated.

2. The method for managing a measuring point standard model of an electrical monitoring system according to claim 1, characterized in that: Said S1 comprises: S11, Creation of Equipment Classification Coding Template: Based on the type and functional level of electrical equipment, equipment classification coding is defined using structured coding rules; S12, loop template and full equipment template: The loop template is a measurement point set template defined according to the equipment loop, describing the standard measurement point information related to the loop; S13, generation of standard measuring point information: the standard measuring point information includes the Chinese and English names, types, units and attributes of the measuring points, and is generated through a fuzzy matching algorithm; S14, storing the standardized measuring point database: storing the generated standard measuring point information, including the Chinese and English names, types, units and attributes of the measuring points, in the standardized measuring point database.

3. The method for managing a measuring point standard model of an electrical monitoring system according to claim 2, characterized in that: The S2 includes: S21, Equipment Quantity and Circuit Statistics: Based on the equipment classification code template, count the total number of electrical equipment and the number of unmanaged circuits associated with the equipment classification code template; S22, fuzzy matching judgment of semantic differences: similarity calculation is performed using a fuzzy matching algorithm, and a consistency judgment result is generated based on the calculation result.

4. The method for managing a measuring point standard model of an electrical monitoring system according to claim 3, characterized in that: The S3 includes: S31, generating an unmanaged measurement point set, and identifying measurement points that do not match the standard template in actual measurement points; S32, expand the physical attributes and equipment classification of unmanaged measurement points and add them to the standard template; S33, generating prompt information for the device without measurement points, and exporting relevant data of the abnormal device.

5. The method for managing a measuring point standard model of an electrical monitoring system according to claim 4, characterized in that: In S31, an unregulated measurement point set is generated according to the consistency determination result.

6. The method for managing a measuring point standard model of an electrical monitoring system according to claim 4, characterized in that: The S32 processes each measuring point in the unmanaged measuring point set according to its physical properties and device classification through governance rules, adds it to the standard template, and dynamically expands the physically defined analog parameters to generate expanded measuring point information.

7. The method for managing a measuring point standard model of an electrical monitoring system according to claim 4, characterized in that: The step S33 generates prompt information for the devices without measuring points that are still missing measuring points, including the device identification, the device location and the missing measuring point information, and exports the abnormal device data.

8. The method for managing a measuring point standard model of an electrical monitoring system according to claim 7, characterized in that: The S4 includes: S41, matching the relationship between measurement points and equipment: matching the measurement point set and the equipment set according to the equipment data model; S42, filling in missing data and storing in database: filling in missing measurement point data.

9. The method for managing a measuring point standard model of an electrical monitoring system according to claim 8, characterized in that: The S5 includes: S51, determining the loading mode and selecting the target equipment: based on the loading mode selected by the user, determining the loading range, which includes the full loading mode and the partial loading mode, and selecting the target loading equipment; S52, template rule loading: according to the loading target, extract the template rules applicable to the target device from the standard template database and load them into the measurement point data set of the corresponding device; S53, executing measurement point standardization management and generating a management effect evaluation report: performing measurement point standardization management on the loaded template rules, calculating the measurement point standardization rate, and generating a management effect evaluation report.

10. A measuring point standard model management system for an electrical monitoring system, used to implement a measuring point standard model management method for an electrical monitoring system according to any one of claims 1 to 9, characterized in that: Includes the following modules: Template management module: creates equipment classification coding templates based on the type and functional level of electrical equipment. The equipment classification coding templates include equipment classification codes, specific circuit templates, and full equipment templates. It also generates standard measurement point information and stores it in the standardized measurement point database. Data analysis module: Counts the total number of associated devices and the number of unmanaged loops, and uses a fuzzy matching algorithm to determine the semantic differences between actual measurement point names and standard measurement point names, generating consistency determination results; Governance rule generation module: Dynamically adjusts the governance rule set based on consistency determination results, adds unregulated measurement points to the standard template, generates prompt information and exports data for devices without measurement points, and expands physically defined analog parameters. Database management module: matches the relationship between measurement points and equipment according to the equipment data model, and standardizes the measurement point data, including cleaning redundant measurement points, correcting units, and filling missing values; Template loading and governance execution module: According to the selected loading mode, the template rules are fully or partially loaded to all related equipment or designated substations, the standardized governance of the measuring points is completed, and a governance effect evaluation report is generated.

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