Data management system and management method for power grid equipment

Abstract

The invention relates to the technical field of power grid equipment data management, and discloses a power grid equipment data management system and method, and the system comprises a data collection processing module, a resource integration management module, a service mechanism construction module and a brand display execution module. When the whole-process data integration of the power grid equipment is carried out, a standardized data acquisition and verification mechanism is established, and differentiated integration rules are set for static and dynamic data in different stages, so that the standardization and the definition of the access of the static and dynamic data generated by the power grid equipment in planning, construction and operation and maintenance stages are ensured; and meanwhile, the data integration quality is monitored in real time by utilizing a dynamic gradient correction function, so that the problem of data deviation caused by transmission delay and field dislocation can be identified and eliminated, the construction accuracy of the digital distribution network management mode is ensured, and the resource integration error is reduced.

Description

Technical Field

[0001] This invention relates to the field of power grid equipment data management technology, specifically to a power grid equipment data management system and management method. Background Technology

[0002] As typical asset-intensive enterprises, power grid companies have long considered improving equipment operation levels and extending asset lifecycles as crucial means to reduce costs and enhance core competitiveness. Establishing an effective management system for physical equipment has been a persistent challenge for power grid companies.

[0003] Currently, due to the numerous static and dynamic data sources generated by power grid equipment during the planning, construction, and operation and maintenance phases, and their heterogeneous formats, traditional management systems cannot verify the timing alignment and quality consistency of data access links in real time when integrating resources throughout the entire process. When transmission delays and field misalignments occur at the data acquisition end, it will lead to deviations in the resource integration results, making it impossible to guarantee the accuracy of the digital distribution network management model.

[0004] Therefore, a data management system and management method for power grid equipment are proposed to solve the above problems. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a data management system and method for power grid equipment, which solves the problem mentioned in the background that deviations occur in resource integration results and the inability to guarantee the accuracy of digital distribution network management model construction.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a data management system and management method for power grid equipment, the method comprising the following steps:

[0007] S1. Collect static and dynamic data of power grid equipment during the planning, construction and operation and maintenance phases, and generate a basic dataset of power grid equipment;

[0008] S2. Based on the aforementioned power grid equipment basic dataset, perform resource integration processing for the entire process of construction and operation of the distribution network demonstration zone, and construct data for the digital distribution network full-process management model;

[0009] S3. Based on the data of the digital distribution network full-process management model, construct and process the grid-based customer service mechanism to generate government-enterprise linkage grid-based service model data;

[0010] S4. Based on the data of the government-enterprise linkage grid service model, perform display processing of the power grid service culture brand to generate power grid brand culture display data;

[0011] S5. Call the power grid brand culture display data, combine it with the digital distribution network full-process management mode data and the government-enterprise linkage grid service mode data to perform power grid equipment management output processing, and generate a power grid equipment management report.

[0012] Preferably, generating the basic dataset for power grid equipment in step S1 includes the following steps:

[0013] S11. Parameter measurement and processing of power grid equipment during the planning stage is performed through distribution network detection equipment, and static data of power grid equipment is generated. The static data of power grid equipment represents the combination parameters of equipment location parameters and physical form and position parameters established with the power grid topology as the coordinate axis in the non-operation state. The distribution network detection equipment includes laser rangefinders and sensors. The equipment parameters include voltage level parameters, load parameters and insulation parameters.

[0014] S12. Real-time parameter acquisition and processing of power grid equipment during operation is performed through distribution network dynamic monitoring equipment, and dynamic data of power grid equipment is generated. The dynamic data of power grid equipment represents the combination parameters of equipment location parameters and real-time performance parameters established with the power grid topology as the coordinate axis under the operating state. The distribution network dynamic monitoring equipment includes gyroscopes, accelerometers and temperature sensors.

[0015] Preferably, the resource integration process in S2 includes the following steps:

[0016] S21. Import the generated static data and dynamic data of the power grid equipment into the power grid monitoring platform. Use an intelligent search algorithm to search for distribution network planning resources, construction resources and operation and maintenance resources in the power grid monitoring platform according to resource type keywords, and generate distribution network resource integration data.

[0017] S22. Based on the integrated distribution network resource data, further processing for digital applications is performed to construct a digital distribution network full-process management model data. This full-process management model data represents the integrated management parameters of resources in the planning, construction, and operation and maintenance stages. The digital distribution network full-process management model data is constructed by linearly optimizing dynamic gradient parameters.

[0018] ;

[0019] in This represents data representing the entire process management mode of digital power distribution networks. This indicates data on the integration of distribution network resources. This represents the resource integration weighting coefficient. Represents the dynamic data optimization coefficient. This represents the gradient parameters of dynamic data.

[0020] Preferably, the resource integration process in S2 further includes the following steps:

[0021] S23. Based on the integrated data of the distribution network resources, perform intelligent three-dimensional visualization system construction processing to generate distribution network real-scene data;

[0022] S24. Based on the real-world data of the distribution network, design and process the operation to make the network transparent, assets transparent, and work transparent, and optimize the data of the digital distribution network full-process management mode.

[0023] Preferably, the construction of the grid-based customer service mechanism in S3 includes the following steps:

[0024] S31. Obtain the data of the digital distribution network full-process management mode;

[0025] S32. Based on the data of the digital distribution network full-process management mode, activate the government-enterprise linkage mechanism to generate government-enterprise collaborative data;

[0026] S33. Based on the aforementioned government-enterprise collaborative data, the results of power grid digitalization are integrated with community grid-based services to construct government-enterprise collaborative grid-based service model data. This data includes the "five zeros" service characteristics: zero-distance service, zero on-site visits, zero proof required for electricity application, zero waiting time for electricity use, and zero investment for installation. The government-enterprise collaborative grid-based service model data is calculated using the following formula:

[0027] ;

[0028] in This indicates data from a government-enterprise collaborative grid-based service model. This represents the service integration weighting coefficient. This represents the quantified value of the "five zeros" service characteristics. The degree of digital integration is indicated by the number of data interfaces and response speed.

[0029] Preferably, the construction of the grid-based customer service mechanism in S3 further includes the following steps:

[0030] S34. Based on the data of the government-enterprise linkage grid service model, optimize the internal management mechanism, formulate operation and maintenance organization management rules, and generate internal collaborative data.

[0031] S35. Based on the internal collaborative data, process user service requests, generate hot issue solution data, and update the government-enterprise linkage grid service model data through the response efficiency coefficient.

[0032] Preferably, the process of displaying the power grid service culture brand in S4 includes the following steps:

[0033] S41. Based on the data of the government-enterprise linkage grid service model, perform functional design processing of the power grid brand exhibition hall and generate exhibition hall functional data.

[0034] S42. Based on the exhibition hall function data and combined with the power grid service culture characteristics, the brand display content is integrated and processed to generate power grid brand culture display data. The power grid brand culture display data represents the combined parameters of business hall business processing and cultural display.

[0035] Preferably, in step S43, based on the power grid brand culture display data, cultural tourism integration processing is performed to generate data on enhancing cultural influence;

[0036] S44. Based on the cultural influence enhancement data, perform service brand promotion processing and update the power grid brand culture display data.

[0037] Preferably, the power grid equipment management output processing in step S5 includes the following steps:

[0038] S51. Extract the cultural display features and business processing features from the power grid brand culture display data;

[0039] S52, Display the cultural features The resource integration parameters in the data of the digital distribution network full-process management mode are the same as the business processing characteristics. By aligning and combining data using the Euclidean distance function, the basic data for management output is generated:

[0040] ;

[0041] in This indicates the basic data output by management. Indicates cultural display characteristics, Indicates resource integration parameters, This represents the alignment operation function. Indicates the output scaling factor;

[0042] S53. Based on the management output basic data, generate and process the power grid equipment status report, and output the power grid equipment management report.

[0043] Preferably, the system includes a data acquisition and processing module, a resource integration and management module, a service mechanism construction module, and a brand display execution module;

[0044] The data acquisition and processing module includes a static data acquisition unit and a dynamic data acquisition unit;

[0045] The static data acquisition unit collects static data of power grid equipment through distribution network detection equipment, and the dynamic data acquisition unit collects dynamic data of power grid equipment through distribution network dynamic monitoring equipment.

[0046] The resource integration and management module includes a resource integration unit and a full-process management unit;

[0047] The resource integration unit performs distribution network resource integration processing based on static and dynamic data of power grid equipment to generate distribution network resource integration data. The full-process management unit performs digital distribution network full-process management mode construction processing based on distribution network resource integration data to generate digital distribution network full-process management mode data.

[0048] The service mechanism construction module includes a government-enterprise linkage unit and a grid-based service unit;

[0049] The government-enterprise linkage unit activates the government-enterprise collaboration mechanism based on the data of the digital distribution network full-process management mode, generating government-enterprise collaboration data. The grid service unit constructs grid customer service based on the government-enterprise collaboration data, generating government-enterprise linkage grid service mode data.

[0050] The brand display execution module includes a brand design unit and a culture display unit;

[0051] The brand design unit processes the data of the government-enterprise collaborative grid service model to design the functions of the power grid brand exhibition hall and generate exhibition hall function data. The culture display unit processes the brand culture integration based on the exhibition hall function data and generates power grid brand culture display data.

[0052] Beneficial effects

[0053] Compared with the prior art, the present invention provides a data management system and method for power grid equipment, which has the following beneficial effects:

[0054] 1. In this invention, when integrating data from the entire power grid equipment process, a standardized data acquisition and verification mechanism is established, and differentiated integration rules are set for static and dynamic data at different stages. This ensures the standardization and clarity of static and dynamic data access generated by power grid equipment during the planning, construction, and operation and maintenance stages. At the same time, the dynamic gradient correction function is used to monitor the data integration quality in real time, which can identify and eliminate data deviation problems caused by transmission delays and field misalignments, ensuring the accuracy of the digital distribution network management model construction and reducing resource integration errors.

[0055] 2. In this invention, when constructing a government-enterprise collaborative grid-based service mechanism, the achievement status and efficiency indicators of the five zero service characteristics are analyzed in real time to dynamically perceive the matching degree between community service needs and the digital transformation results of the power grid. This enables the system to avoid misalignment between service response strategies and actual user demands. Furthermore, when service deviations occur, the system can quickly reconstruct the responsibility structure and collaborative processes through internal collaboration mechanisms, correct service strategies in real time, and ensure the accuracy and response efficiency of government-enterprise collaborative services.

[0056] 3. In this invention, when displaying and outputting the power grid brand culture, the system adaptively integrates business processing functions and cultural dissemination attributes to perform weighted evaluation and logical alignment of multi-dimensional service indicators. It coordinates the relationship between brand output data and the five zero service characteristics in real time, enabling the system to achieve multi-dimensional adaptive integration of business and culture, avoiding evaluation errors caused by feature conflicts, and improving the credibility of government-enterprise collaborative service effects and user experience. Attached Figure Description

[0057] Figure 1 This is a flowchart of a data management method for power grid equipment according to the present invention;

[0058] Figure 2 This is an architectural diagram of a data management system for power grid equipment according to the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and 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.

[0060] For specific implementation examples, please refer to: Figure 1-2 A data management system and management method for power grid equipment, the method comprising the following steps:

[0061] S1. Collect static and dynamic data of power grid equipment during the planning, construction and operation and maintenance phases, and generate a basic dataset of power grid equipment;

[0062] S2. Based on the basic dataset of power grid equipment, conduct resource integration and processing for the entire process of construction and operation of distribution network demonstration zones, and construct data for the full-process management model of digital distribution network;

[0063] S3. Based on the data of the digital distribution network full-process management model, construct and process the grid-based customer service mechanism to generate government-enterprise linkage grid-based service model data;

[0064] S4. Based on the data from the government-enterprise collaborative grid service model, process the data to display the power grid service culture brand and generate power grid brand culture display data.

[0065] S5. Call upon the power grid brand culture display data, combine the data of the digital distribution network full-process management model with the data of the government-enterprise linkage grid service model to process the power grid equipment management output and generate a power grid equipment management report.

[0066] The steps involved in generating the basic dataset for power grid equipment in S1 are as follows:

[0067] S11. Parameter measurement and processing of power grid equipment during the planning phase are performed using distribution network detection equipment. After weighted calibration of physical form and position parameters, static data of the power grid equipment is generated. Static data represents the combined parameters of equipment location and physical form and position parameters established with the power grid topology as the coordinate axis in the non-operating state. Distribution network detection equipment includes laser rangefinders and sensors. Equipment parameters include voltage level parameters, load parameters, and insulation parameters. The calculation formula for static data of power grid equipment is:

[0068] ;

[0069] in Represents static data of power grid equipment. Indicates the first Physical shape and position parameters, Indicates the parameter weighting coefficient. This represents the topology calibration factor, which corrects for grid topology coordinate deviations.

[0070] S12. Real-time parameter acquisition and processing of power grid equipment during operation is performed through distribution network dynamic monitoring equipment, and dynamic data of power grid equipment is generated. The dynamic data of power grid equipment represents the combination parameters of equipment location parameters and real-time performance parameters established with the power grid topology as the coordinate axis under the operating state. Distribution network dynamic monitoring equipment includes gyroscopes, accelerometers and temperature sensors.

[0071] Resource integration processing in S2 includes the following steps:

[0072] S21. Import the generated static and dynamic data of power grid equipment into the power grid monitoring platform. Use an intelligent search algorithm to search for distribution network planning resources, construction resources, and operation and maintenance resources in the power grid monitoring platform according to resource type keywords, and generate distribution network resource integration data. The distribution network resource integration data represents the combined parameters of distribution network planning resource information, construction resource information, and operation and maintenance resource information. The intelligent search algorithm is implemented through the following process:

[0073] S211. Perform semantic parsing on resource type keywords to generate a keyword vector set;

[0074] S212. Based on the keyword vector set, calculate the semantic similarity between the resource information in the distribution network planning resource library, construction resource library and operation and maintenance resource library;

[0075] S213. Based on the semantic similarity ranking results, filter and output information on distribution network planning resources, construction resources and operation and maintenance resources;

[0076] S22. Based on the integrated data of distribution network resources, conduct in-depth processing for digital applications to construct a full-process management model data for digital distribution networks. This full-process management model data represents the integrated management parameters of resources in the planning, construction, and operation and maintenance stages. The full-process management model data for digital distribution networks is constructed through linear optimization of dynamic gradient parameters.

[0077] ;

[0078] in This represents data representing the entire process management mode of digital power distribution networks. This indicates data on the integration of distribution network resources. This represents the resource integration weighting coefficient. Represents the dynamic data optimization coefficient. This represents the gradient parameters of dynamic data.

[0079] The resource integration process in S2 also includes the following steps:

[0080] S23. Based on the integrated data of the distribution network resources, a smart 3D visualization system is constructed and processed to generate distribution network real-scene data. The construction and processing of the smart 3D visualization system is achieved through the following process:

[0081] S231. Based on the static and dynamic operating parameters of the equipment in the distribution network resource integration data, construct a three-dimensional model set of distribution network equipment;

[0082] S232. Map the real-time collected dynamic operation data to the corresponding three-dimensional model to generate equipment operation status data with physical mapping relationship;

[0083] S233: Integrate 3D model sets and equipment operation status data to render and generate real-world data of the power distribution network;

[0084] S24. Based on the real-world data of the distribution network, design and process the data to make operation, assets, and work transparent, and optimize the data of the whole process management mode of the digital distribution network.

[0085] Building a grid-based customer service mechanism in S3 includes the following steps:

[0086] S31. Obtain data on the entire process management mode of digital distribution network;

[0087] S32. Based on the data from the digital distribution network full-process management model, activate the government-enterprise linkage mechanism to generate government-enterprise collaborative data;

[0088] S33. Based on government-enterprise collaborative data, the results of power grid digitalization are integrated with community grid-based services to construct government-enterprise collaborative grid-based service model data. This data includes the "five zeros" service characteristics: zero-distance service, zero on-site visits, zero proof required for electricity application, zero waiting time for electricity use, and zero investment for installation. The government-enterprise collaborative grid-based service model data is calculated using the following formula:

[0089] ;

[0090] in This indicates data from a government-enterprise collaborative grid-based service model. This represents the service integration weighting coefficient. This represents the quantified value of the "five zeros" service characteristics. The degree of digital integration is assessed based on the number of data interfaces and response speed.

[0091] 50 Service Characteristics Calculate using the following steps:

[0092] S331, Separately calculate the service zero-distance compliance rate Zero on-site service completion rate Zero-proof completion rate for electricity application Zero waiting rate for electricity consumption and the achievement rate of zero investment in installation ;

[0093] S332. Calculate the weighted average based on the achievement rate of each service indicator:

[0094] ;

[0095] in For the 50 service characteristic value, For service metrics index variables, For the first The achievement rate of each service indicator Let be the weighting coefficients for each service indicator, and satisfy . .

[0096] Digital integration Obtain it through the following steps:

[0097] S333, Obtain the number of data interfaces from the API interface of the power grid digitalization platform. Monitor and obtain the average response speed of the API interface. Set the maximum tolerable latency threshold It takes 2.0 seconds to calculate the degree of digital integration:

[0098] ;

[0099] Building a grid-based customer service mechanism in S3 also includes the following steps:

[0100] S34. Based on the data from the government-enterprise collaborative grid service model, optimize the internal management mechanism, formulate integrated operation and maintenance organization management rules, and generate internal collaborative data. The optimization of the internal management mechanism is achieved through the following process:

[0101] S341. Analyze the five zero service characteristic data in the government-enterprise linkage grid service model data to obtain the achievement status and efficiency indicators of each service characteristic.

[0102] S342. Based on the achieved status and efficiency indicators, restructure the authority and responsibility allocation architecture and collaborative processes of the integrated operation and maintenance organization.

[0103] S343. Based on the restructured authority and responsibility architecture and collaborative processes, formulate organizational management rules that include response time limits, task assignment and closed-loop assessment standards.

[0104] S344. Generate internal collaboration data to standardize internal collaboration processes in accordance with organizational management rules;

[0105] S35. Based on internal collaborative data, process user service requests, generate data on solutions to hot issues, and update the government-enterprise collaborative grid service model data through response efficiency coefficients.

[0106] ;

[0107] in This indicates the data update volume of the government-enterprise collaborative grid-based service model. This represents the efficiency coefficient of response to demands. This represents the data value for solutions to hot issues. This represents internal collaborative data values.

[0108] The process of showcasing the power grid service culture brand in S4 includes the following steps:

[0109] S41. Based on the data from the government-enterprise collaborative grid service model, perform functional design processing for the power grid brand exhibition hall and generate exhibition hall functional data.

[0110] S42. Based on the exhibition hall's functional data and combined with the characteristics of the power grid's service culture, a logarithmic attenuation compensation algorithm is used to integrate and process the brand display content, generating power grid brand culture display data. This data represents a combination of parameters integrating business hall operations and cultural displays. The formula for the logarithmic attenuation compensation algorithm is:

[0111] ;

[0112] in This data represents the display of the power grid's brand culture. The data represents the functional values ​​of the exhibition hall, and θ represents the cultural decay factor. This represents the brand gain coefficient.

[0113] The process of showcasing the power grid service culture brand in S4 also includes the following steps:

[0114] S43. Based on the data on the display of power grid brand culture, conduct cultural and tourism integration processing to generate data on the enhancement of cultural influence;

[0115] S44. Based on the data on the improvement of cultural influence, process the service brand promotion and update the data on the display of power grid brand culture.

[0116] The output processing for power grid equipment management in S5 includes the following steps:

[0117] S51. Extract cultural display features and business processing features from the power grid brand culture display data;

[0118] S52, Showcasing Cultural Characteristics Resource integration parameters in the data of the digital distribution network full-process management model, which are similar to the characteristics of business processing. By aligning and combining data using the Euclidean distance function, the basic data for management output is generated:

[0119] ;

[0120] in This indicates the basic data output by management. Indicates cultural display characteristics, Indicates resource integration parameters, This represents the alignment operation function. Indicates the output scaling factor;

[0121] Alignment operation function This can be achieved through the following steps:

[0122] Cultural display characteristics Quantified as 3D feature vector: ;

[0123] Integrate resource parameters Quantified as Dimensional parameter vector: ;

[0124] Calculate the Euclidean distance between the feature vector and the parameter vector:

[0125] ;

[0126] in A collection of cultural characteristics. A set of resource integration parameters. Let the dimension be the vector. The index variable for the vector elements represents the cultural feature vector. In the The eigenvalues ​​on the dimension are the resource integration parameter vectors. In the Parameter values ​​in the dimension;

[0127] S53. Based on the basic data output by management, generate and process the status report of power grid equipment, and output the power grid equipment management report.

[0128] The system includes a data acquisition and processing module, a resource integration and management module, a service mechanism construction module, and a brand display and execution module;

[0129] The data acquisition and processing module includes a static data acquisition unit and a dynamic data acquisition unit;

[0130] The static data acquisition unit collects static data of power grid equipment through distribution network detection equipment, while the dynamic data acquisition unit collects dynamic data of power grid equipment through distribution network dynamic monitoring equipment.

[0131] The resource integration management module includes a resource integration unit and a full-process management unit;

[0132] The resource integration unit performs distribution network resource integration processing based on static and dynamic data of power grid equipment to generate distribution network resource integration data. The full-process management unit performs digital distribution network full-process management model construction processing based on distribution network resource integration data to generate digital distribution network full-process management model data.

[0133] The service mechanism construction module includes government-enterprise linkage units and grid-based service units;

[0134] The government-enterprise collaboration unit activates the government-enterprise collaboration mechanism based on data from the digital power distribution network full-process management model, generating government-enterprise collaboration data. Grid-based service units, based on government-enterprise collaborative data The process involves building a grid-based customer service system, generating data for a government-enterprise collaborative grid-based service model, and outputting service values ​​through a load protection mechanism.

[0135] ;

[0136] in This represents the output value of the gridded service. This indicates data input for government-enterprise collaboration. Indicates the basic capacity of the gridded service unit. Indicates the load balancing factor;

[0137] The brand presentation execution module includes a brand design unit and a cultural presentation unit;

[0138] The brand design unit processes the data of the grid-based service model for government-enterprise collaboration to design the functions of the power grid brand exhibition hall and generate exhibition hall function data. The culture display unit integrates and processes the brand culture based on the exhibition hall function data and generates power grid brand culture display data.

[0139] The operation steps of the data management system and management method for power grid equipment are as follows:

[0140] Step 1: Data Acquisition Phase

[0141] The system collects static parameters of power grid equipment during the planning phase through distribution network monitoring equipment, including equipment location information, voltage level, load capacity, and insulation performance. Simultaneously, it collects dynamic parameters such as equipment location changes, temperature fluctuations, and vibration displacement in real time during operation through dynamic monitoring equipment. All collected data undergoes standardized processing to form a basic dataset of power grid equipment, providing a unified and standardized data foundation for subsequent processing.

[0142] Step Two: Resource Integration and Processing Stage

[0143] Based on a foundational dataset, the system employs intelligent search technology to match resource information within the monitoring platform according to resource type, generating integrated resource data. Subsequently, a dynamic gradient optimization algorithm is used to fuse the resource data with real-time performance change parameters, constructing a comprehensive digital distribution network management model. Simultaneously, a 3D visualization system is built to achieve transparent management of the power grid's operational status, asset distribution, and operational processes.

[0144] Step 3: Grid Service Construction Phase

[0145] The system activates the government-enterprise collaboration mechanism based on data from the digital distribution network management model, generating collaborative government-enterprise data. By quantitatively evaluating the "five zeros" service indicators and the performance of the digital platform interface, and integrating community needs with power grid resources, it generates grid-based service data for government-enterprise collaboration. It monitors service deviations in real time, optimizes the responsibility structure and response process through internal collaboration mechanisms, and dynamically updates service strategies.

[0146] Step Four: Cultural Brand Showcase Stage

[0147] Based on government-enterprise collaborative service data, the system designs a functional module for the power grid brand exhibition hall. Combining cultural characteristics and business processing needs, it integrates the displayed content using an attenuation compensation algorithm to generate power grid brand cultural data. It incorporates cultural and tourism elements to enhance cultural influence and continuously updates brand output content through promotional activities.

[0148] Step 5: Management Decision Output Stage

[0149] The system extracts cultural display features and business processing features, and matches them with resource integration parameters using spatial vector alignment technology to generate basic management data. Finally, based on this data, a comprehensive management report covering equipment status, service efficiency, and cultural influence is generated, achieving closed-loop output for the full lifecycle management of power grid equipment.

[0150] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0151] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A data management method for power grid equipment, characterized in that: The method includes the following steps: S1. Collect static and dynamic data of power grid equipment during the planning, construction and operation and maintenance phases, and generate a basic dataset of power grid equipment, including static data and dynamic data of power grid equipment. S2. Based on the aforementioned power grid equipment basic dataset, perform resource integration processing for the entire process of construction and operation of the distribution network demonstration zone, and construct data for the digital distribution network full-process management model; S3. Based on the data of the digital distribution network full-process management model, construct and process the grid-based customer service mechanism to generate government-enterprise linkage grid-based service model data; S4. Based on the data of the government-enterprise linkage grid service model, perform display processing of the power grid service culture brand to generate power grid brand culture display data; S5. Call the power grid brand culture display data, combine it with the digital distribution network full-process management mode data and the government-enterprise linkage grid service mode data to perform power grid equipment management output processing, and generate a power grid equipment management report.

2. The data management method for power grid equipment according to claim 1, characterized in that: The process of generating the basic dataset for power grid equipment in S1 includes the following steps: S11. Parameter measurement and processing of power grid equipment during the planning stage is performed through distribution network detection equipment, and static data of power grid equipment is generated. The static data of power grid equipment represents the combination parameters of equipment location parameters and physical form and position parameters established with the power grid topology as the coordinate axis in the non-operation state. The distribution network detection equipment includes laser rangefinders and sensors. The equipment parameters include voltage level parameters, load parameters and insulation parameters. S12. Real-time parameter acquisition and processing of power grid equipment during operation is performed through distribution network dynamic monitoring equipment, and dynamic data of power grid equipment is generated. The dynamic data of power grid equipment represents the combination parameters of equipment location parameters and real-time performance parameters established with the power grid topology as the coordinate axis under the operating state. The distribution network dynamic monitoring equipment includes gyroscopes, accelerometers and temperature sensors.

3. The data management method for power grid equipment according to claim 1, characterized in that: The resource integration process in S2 includes the following steps: S21. Import the generated static data and dynamic data of the power grid equipment into the power grid monitoring platform. Use an intelligent search algorithm to search for distribution network planning resources, construction resources and operation and maintenance resources in the power grid monitoring platform according to resource type keywords, and generate distribution network resource integration data. S22. Based on the integrated distribution network resource data, further processing for digital applications is performed to construct a digital distribution network full-process management model data. This full-process management model data represents the integrated management parameters of resources in the planning, construction, and operation and maintenance stages. The digital distribution network full-process management model data is constructed by linearly optimizing dynamic gradient parameters. ； in This represents data from the entire digital distribution network management model. This indicates data on the integration of distribution network resources. This represents the resource integration weighting coefficient. Represents the dynamic data optimization coefficient. This represents the gradient parameters of dynamic data.

4. The data management method for power grid equipment according to claim 3, characterized in that: The resource integration process in S2 also includes the following steps: S23. Based on the integrated data of the distribution network resources, perform intelligent three-dimensional visualization system construction processing to generate distribution network real-scene data; S24. Based on the real-world data of the distribution network, design and process the operation to make the network transparent, assets transparent, and work transparent, and optimize the data of the digital distribution network full-process management mode.

5. The data management method for power grid equipment according to claim 1, characterized in that: The steps involved in building the grid-based customer service mechanism in S3 are as follows: S31. Obtain the data of the digital distribution network full-process management mode; S32. Based on the data of the digital distribution network full-process management mode, activate the government-enterprise linkage mechanism to generate government-enterprise collaborative data; S33. Based on the aforementioned government-enterprise collaborative data, the results of power grid digitalization are integrated with community grid-based services to construct government-enterprise collaborative grid-based service model data. This data includes the "five zeros" service characteristics: zero-distance service, zero on-site visits, zero proof required for electricity application, zero waiting time for electricity use, and zero investment for installation. The government-enterprise collaborative grid-based service model data is calculated using the following formula: ； in This indicates data from a government-enterprise collaborative grid-based service model. This represents the service integration weighting coefficient. This represents the quantified value of the "five zeros" service characteristics. The degree of digital integration is indicated by the number of data interfaces and response speed.

6. The data management method for power grid equipment according to claim 1, characterized in that: The construction of the grid-based customer service mechanism in S3 also includes the following steps: S34. Based on the data of the government-enterprise linkage grid service model, optimize the internal management mechanism, formulate operation and maintenance organization management rules, and generate internal collaborative data. S35. Based on the internal collaborative data, process user service requests, generate hot issue solution data, and update the government-enterprise linkage grid service model data through the response efficiency coefficient.

7. The data management method for power grid equipment according to claim 1, characterized in that: The process of displaying the power grid service culture brand in S4 includes the following steps: S41. Based on the data of the government-enterprise linkage grid service model, perform functional design processing of the power grid brand exhibition hall and generate exhibition hall functional data. S42. Based on the exhibition hall function data and combined with the power grid service culture characteristics, the brand display content is integrated and processed to generate power grid brand culture display data. The power grid brand culture display data represents the combined parameters of business hall business processing and cultural display.

8. The data management method for power grid equipment according to claim 1, characterized in that: The process of displaying the power grid service culture brand in S4 also includes the following steps: S43. Based on the power grid brand culture display data, perform cultural tourism integration processing to generate data on enhancing cultural influence; S44. Based on the cultural influence enhancement data, perform service brand promotion processing and update the power grid brand culture display data.

9. A data management method for power grid equipment according to claim 1, characterized in that: The power grid equipment management output processing in S5 includes the following steps: S51. Extract the cultural display features and business processing features from the power grid brand culture display data; S52, Display the cultural features The resource integration parameters in the data of the digital distribution network full-process management mode are the same as the business processing characteristics. By aligning and combining data using the Euclidean distance function, the basic data for management output is generated: ； in This indicates the basic data output by management. Indicates cultural display characteristics, Indicates resource integration parameters, This represents the alignment operation function. Indicates the output scaling factor; S53. Based on the management output basic data, generate and process the power grid equipment status report, and output the power grid equipment management report.

10. A data management system for power grid equipment, used to implement the data management method for power grid equipment according to any one of claims 1-9, characterized in that: The system includes a data acquisition and processing module, a resource integration and management module, a service mechanism construction module, and a brand display and execution module; The data acquisition and processing module includes a static data acquisition unit and a dynamic data acquisition unit; The static data acquisition unit collects static data of power grid equipment through distribution network detection equipment, and the dynamic data acquisition unit collects dynamic data of power grid equipment through distribution network dynamic monitoring equipment. The resource integration and management module includes a resource integration unit and a full-process management unit; The resource integration unit performs distribution network resource integration processing based on static and dynamic data of power grid equipment to generate distribution network resource integration data. The full-process management unit performs digital distribution network full-process management mode construction processing based on distribution network resource integration data to generate digital distribution network full-process management mode data. The service mechanism construction module includes a government-enterprise linkage unit and a grid-based service unit; The government-enterprise linkage unit activates the government-enterprise collaboration mechanism based on the data of the digital distribution network full-process management mode, generating government-enterprise collaboration data. The grid service unit constructs grid customer service based on the government-enterprise collaboration data, generating government-enterprise linkage grid service mode data. The brand display execution module includes a brand design unit and a culture display unit; The brand design unit processes the data of the government-enterprise collaborative grid service model to design the functions of the power grid brand exhibition hall and generate exhibition hall function data. The culture display unit processes the brand culture integration based on the exhibition hall function data and generates power grid brand culture display data.

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