Method for constructing whole-process connection logic model of power grid equipment

Abstract

The invention discloses a method for constructing a whole-process connection logic model of power grid equipment, and belongs to the technical field of power system engineering. The method is implemented through the four steps of primary equipment information integration, model construction and improvement, model programming test and model conversion tool development. By constructing the basic data base and the standard data model, data standardization and service normalization are achieved, the deep problem of cross-professional business collaboration is solved, and the requirement of a company for data sharing is met. The standardized data management can greatly improve the efficiency and accuracy of data exchange, and effectively support the cooperative work of different business departments. A data center is taken as a core, an integrated data service is constructed, a data supply link is optimized, the communication of the whole process of equipment and the intelligent improvement of customer service are supported, and the transformation of enterprises to digitization is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of power system engineering, and in particular to a method for constructing a full-process through-logic model of power grid equipment. Background Art

[0002] In modern power systems, the management and maintenance of power grid equipment is crucial. With the continuous growth of power demand and the increasing complexity of power grid structure, traditional equipment management methods are obviously unable to meet current needs. Especially in the various stages of equipment planning, construction, operation, maintenance and decommissioning, how to achieve efficient data flow and accurate equipment management has become a major challenge facing power companies.

[0003] At present, power grid equipment management usually relies on multiple independent systems. The data between these systems are often incompatible or lack standardization, resulting in serious information islands. This situation not only affects the efficiency of equipment management, but also increases the complexity of data processing and the possibility of errors. In addition, with the advancement of smart grids and digital transformation, the requirements for full-process equipment management are also increasing, and there is an urgent need for a system solution that can run through the entire life cycle of equipment.

[0004] There are also some attempts to manage power grid equipment data in the existing technology, such as monitoring and analysis systems for single equipment data, or management platforms for specific stages. However, these methods often lack systematicity and globality, and cannot achieve full process management from equipment planning and design to decommissioning and disposal. At the same time, they cannot meet the needs of enterprises for data sharing, business collaboration, and intelligent decision-making.

[0005] Therefore, an integrated logic model for the entire process of power grid equipment can not only achieve comprehensive management of the equipment life cycle and improve the efficiency and life of equipment, but also solve the problem of cross-professional business collaboration and promote the digital transformation of enterprises by building standardized data models and integrated data service platforms. This will greatly improve the operational efficiency of power companies, reduce operating costs, and enhance market competitiveness. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention aims to provide a

[0007] The above object of the present invention is achieved through the following technical solutions:

[0008] A method for constructing a full-process through-logic model of power grid equipment includes the following steps:

[0009] 1) Primary equipment information integration: collect and organize the basic attribute information of primary equipment of 110kV and above, and incorporate the tower information on which the equipment relies into the logical model;

[0010] 2) Model construction and improvement: define the logical relationship and data flow path between models to ensure the coherence and consistency of the entire energy flow model, update or add necessary metering devices and data acquisition equipment according to model requirements, and ensure the comprehensiveness and accuracy of data sources;

[0011] 3) Model programming test: Carry out specific programming implementation of the logical model in stages and modules, and conduct integration testing of internal system components to ensure the coordination and consistency between the logical models of each part;

[0012] 4) Model conversion tool development: Based on the standardized methods in the pre-research phase, develop a configurable and extensible physical model automatic conversion tool that can automatically read the logical model and generate the corresponding physical model according to standard conversion rules.

[0013] Furthermore, the tower information in step 1) includes tower location coordinates, structural form, load conditions, and geographical environment.

[0014] Furthermore, in step 2), the designed logic model is integrated into the existing power information system, and a system-level cascade test is performed to verify the effectiveness and stability of the model.

[0015] Furthermore, in step 2), pilot applications are carried out in some areas or typical scenarios to collect measured data and user feedback, and the model algorithm and interface interaction are continuously adjusted and optimized.

[0016] Furthermore, in step 3), each subsystem is seamlessly integrated into a unified platform to perform full-link functional testing to ensure that all business logics can run stably in the actual operating environment.

[0017] Furthermore, in step 4), a unified data access platform is constructed to achieve efficient access and management of various data sources, with data cleaning, conversion, and storage functions, integrated data access strategies, and support flexible configuration of data update frequency, data filtering rules, and anomaly detection and processing mechanisms.

[0018] In summary, the present invention includes at least one of the following beneficial technical effects:

[0019] 1) Through the integrated logical model design, covering the entire life cycle from equipment planning and design to decommissioning disposal, ensuring the effective flow and seamless connection of data at each stage, and realizing the full life cycle management of power grid equipment. This helps to improve the efficiency and life of equipment while reducing operating costs.

[0020] 2) By building a basic data base and standard data model, data standardization and service standardization are achieved, solving the deep-seated problem of cross-professional business collaboration and meeting the company's demand for data sharing. This standardized data management can greatly improve the efficiency and accuracy of data exchange and effectively support the collaborative work of different business departments.

[0021] 3) With the data center as the core, we will build integrated data services, optimize the data supply chain, support the connection of the entire equipment process and the intelligent improvement of customer service, and promote the digital transformation of enterprises. This transformation can enhance the competitiveness and market responsiveness of enterprises and promote the intelligence and automation of business processes. DETAILED DESCRIPTION

[0022] Example 1

[0023] A method for constructing a full-process through-logic model of power grid equipment includes the following steps:

[0024] 1) Primary equipment information integration: Collect and organize the basic attribute information of primary equipment of 110kV and above, and incorporate the tower information on which the equipment relies into the logical model; the tower information includes the tower location coordinates, structural form, load conditions, and geographical environment.

[0025] Design a complete equipment life cycle logic model according to the six stages of equipment planning and design, manufacturing and procurement, installation and commissioning, operation and maintenance, overhaul and replacement, and decommissioning to ensure the effective flow and seamless connection of data at each stage. Create an asset measurement logic model to realize equipment status monitoring, life prediction, and maintenance strategy recommendation functions. Build a power consumption measurement logic model, covering user power consumption data mining, load prediction, and energy consumption management modules. Design an environmental measurement logic model to integrate climate and geographic information, influencing factor analysis, and decision-making support functions.

[0026] Collect environmental data related to equipment operation, such as temperature, humidity, wind speed, precipitation, geological information, etc. These data can come from weather stations, environmental sensors, and geographic information systems.

[0027] Analyze the impact of environmental factors on the operation of power grid equipment and determine which factors will lead to reduced equipment performance, increased failures, and shortened life. Develop decision-making support functions based on environmental data and influencing factor analysis. Provide predictive analysis of the impact of the environment on equipment operation to help optimize maintenance strategies and emergency responses. Modularize the environmental monitoring function to facilitate integration with other measurement models.

[0028] 2) Model construction and improvement: define the logical relationship and data flow path between each model to ensure the coherence and consistency of the entire energy flow model, update or add necessary metering devices and data acquisition equipment according to model requirements, and ensure the comprehensiveness and accuracy of data sources; integrate the designed logical model into the existing power information system, conduct system cascade adjustment and testing, and verify the effectiveness and stability of the model. Carry out pilot applications in some areas or typical scenarios, collect measured data and user feedback, and continuously adjust and optimize model algorithms and interface interactions.

[0029] Draw a model relationship diagram to clarify the logical relationship between each model (asset measurement, electricity consumption measurement, environmental measurement), and show how data flows between models. Define standardized data interfaces to enable smooth data exchange between different models. This includes data format, transmission protocol, and frequency. Clarify the flow path of data from source collection to final application to ensure that data can flow seamlessly in each stage of equipment planning and design, manufacturing procurement, installation and commissioning. Perform consistency verification during the model integration stage to ensure that data is not lost or redundant when flowing between models.

[0030] 3) Model programming test: Carry out specific programming implementation of the logical model in stages and modules, including the supplier risk assessment model, subsidy gap calculation module, private enterprise debt settlement process engine, and electricity collection algorithm, and conduct integration testing of internal system components to ensure the coordination and consistency between the logical models of each part; seamlessly integrate each subsystem into a unified platform, conduct full-link functional testing, and ensure that all business logic can run stably in the actual operating environment.

[0031] 4) Model conversion tool development: Based on the standardized methods in the pre-research phase, develop a configurable and extensible physical model automatic conversion tool that can automatically read the logical model and generate the corresponding physical model according to the standard conversion rules. Build a unified data access platform to achieve efficient access and management of various data sources, with data cleaning, conversion, and storage functions, integrated data access strategies, and support flexible configuration of data update frequency, data filtering rules, and anomaly detection and processing mechanisms.

[0032] Tightly integrate the physical model automatic conversion module with the data access platform to form a complete solution. Conduct system integration testing and performance testing to ensure that the automatic conversion from logical models to physical models is efficient and accurate in actual scenarios, and that data access is stable and timely. Based on test results and user feedback, continuously optimize the physical model automatic conversion tool and data access strategy to improve the overall performance of the system.

[0033] The main innovative features of the present invention are as follows:

[0034] 1) Construct a basic data base standard data model construction link: Based on the data base project, improve and expand the unified data logic model, convert and generate the interaction model, effectively solve the deep-seated problems of cross-professional business collaboration, and meet the company's data sharing needs; based on the interaction model and message model design, define the standard data interaction format, unify the data access strategy, and realize data standardization and service standardization.

[0035] 2) Create an enterprise-level data platform with integrated data services: Optimize the data access and integration links of the data platform from the aspects of data perception, data aggregation, data connection, data services, etc., improve the efficiency of data supply, and take the business process as the driving force. Focusing on data supply links such as business data item traceability, data access, data business connection integration, and data business full-link monitoring, build a "packaged" data service based on the enterprise-level data platform, and continuously promote the transformation of the data platform from a technology platform to a business platform, supporting the implementation of digital transformation projects such as full-process equipment connection and intelligent improvement of customer service.

[0036] The embodiments of this specific implementation method are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for constructing a full-process through-logic model of power grid equipment, characterized in that The steps include: 1) Primary equipment information integration: collect and organize the basic attribute information of primary equipment of 110kV and above, and incorporate the tower information on which the equipment relies into the logical model; 2) Model construction and improvement: define the logical relationship and data flow path between models to ensure the coherence and consistency of the entire energy flow model, update or add necessary metering devices and data acquisition equipment according to model requirements, and ensure the comprehensiveness and accuracy of data sources; 3) Model programming test: Carry out specific programming implementation of the logical model in stages and modules, and conduct integration testing of internal system components to ensure the coordination and consistency between the logical models of each part; 4) Model conversion tool development: Based on the standardized methods in the pre-research phase, develop a configurable and extensible physical model automatic conversion tool that can automatically read the logical model and generate the corresponding physical model according to standard conversion rules.

2. A method for constructing a full-process through-logic model of power grid equipment according to claim 1, characterized in that The tower information in step 1) includes the tower location coordinates, structural form, load conditions, and geographical environment.

3. A method for constructing a full-process through-logic model of power grid equipment according to claim 1, characterized in that In the step 2), the designed logic model is integrated into the existing power information system, and a system cascade test is performed to verify the effectiveness and stability of the model.

4. A method for constructing a full-process through-logic model of power grid equipment according to claim 1, characterized in that In the step 2), pilot applications are carried out in some areas or typical scenarios to collect measured data and user feedback, and the model algorithm and interface interaction are continuously adjusted and optimized.

5. A method for constructing a full-process through-logic model of power grid equipment according to claim 1, characterized in that In step 3), each subsystem is seamlessly integrated into a unified platform, and full-link functional testing is performed to ensure that all business logic can run stably in the actual operating environment.

6. A method for constructing a full-process through-logic model of power grid equipment according to claim 1, characterized in that In the step 4), a unified data access platform is constructed to achieve efficient access and management of various data sources, with data cleaning, conversion, and storage functions, integrated data access strategies, and support flexible configuration of data update frequency, data filtering rules, and anomaly detection and processing mechanisms.