CN112270619A - Intelligent lean overhaul management system for power transformation equipment based on big data - Google Patents

Intelligent lean overhaul management system for power transformation equipment based on big data Download PDF

Info

Publication number
CN112270619A
CN112270619A CN202011186848.XA CN202011186848A CN112270619A CN 112270619 A CN112270619 A CN 112270619A CN 202011186848 A CN202011186848 A CN 202011186848A CN 112270619 A CN112270619 A CN 112270619A
Authority
CN
China
Prior art keywords
data
equipment
power transformation
power
management
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202011186848.XA
Other languages
Chinese (zh)
Inventor
薄宏斌
张彦斌
王瀚霆
范继锋
仲文博
何世雄
赵俊杰
马兆嵘
慕佩良
王欣
李中为
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Inner Mongolia Electric Power Group Co ltd Wuhai Super High Voltage Power Supply Bureau
Original Assignee
Inner Mongolia Electric Power Group Co ltd Wuhai Super High Voltage Power Supply Bureau
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Inner Mongolia Electric Power Group Co ltd Wuhai Super High Voltage Power Supply Bureau filed Critical Inner Mongolia Electric Power Group Co ltd Wuhai Super High Voltage Power Supply Bureau
Priority to CN202011186848.XA priority Critical patent/CN112270619A/en
Publication of CN112270619A publication Critical patent/CN112270619A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2465—Query processing support for facilitating data mining operations in structured databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06313—Resource planning in a project environment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/24—Reminder alarms, e.g. anti-loss alarms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
    • G06F2216/03—Data mining
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention provides a big data-based intelligent lean overhaul management system for power transformation equipment, and relates to the technical field of power transformation equipment management. The system comprises a physical equipment layer for supporting the normal operation of the system, a data source layer for collecting and managing related data of the power transformation equipment, a business function supporting layer for carrying out big data analysis and a first-level application function layer for guiding the operation of a power grid according to real-time analysis data; meanwhile, based on the service function supporting layer, maintenance management, defect management, equipment visual management, high-voltage test management and big data analysis are realized; and the first-level application function layer accesses each subsystem abstracted based on the service function support layer to obtain a power transformation equipment related analysis result based on the big data, and the familial defects and the operation trend of the power transformation equipment are analyzed based on the analysis results. The system constructs a power supply station substation equipment maintenance data center, analyzes the operation state of the power equipment and provides reference for the daily operation work of the substation.

Description

Intelligent lean overhaul management system for power transformation equipment based on big data
Technical Field
The invention relates to the technical field of substation equipment management, in particular to a substation equipment intelligent lean overhaul management system based on big data.
Background
With the development of economy and the progress of society, the construction speed of national power grid companies is gradually increased, and the scale of the power grid is continuously enlarged and power transformation equipment is multiplied. With the increasing number of devices involved in the transformer substation, a large amount of operation data is accessed into a daily management system of the devices, and a foundation is provided for the application of big data related technology and artificial intelligence. The data mainly come from databases, networks, MIS systems and data acquisition and transmission equipment, the structures and the forms of the data are different to different degrees, and the traditional analysis-based mode is difficult to adapt to the multi-source heterogeneous data processing requirements.
The transformer substation is used as the core of the operation of the power system, and the power supply service pressure of a power grid enterprise and the pressure for improving the working efficiency are increased due to the fact that the scale of the power grid is multiplied. The original management mode of a power supply company is not suitable under new situations, the contradiction between personnel and workload of a power overhaul department of a power grid enterprise is increased, and the original production management mode cannot effectively manage power transformation equipment. The safety and stability of the operation of the power grid plays a decisive role in the development of power enterprises, the power transformation and distribution work is the key factor for ensuring the safety and stability of the operation of a transformer substation, and the maintenance management system plays an important role in the maintenance management system. Through a large amount of practices, the national power grid finds that the lean management mode is beneficial to effectively realizing standardization, standardization and scientification of enterprise management. The lean management system can continuously improve the operation performance and the customer satisfaction, and simultaneously can improve the maintenance efficiency of the power transformation equipment and the operation reliability of the power transformation equipment.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an intelligent lean maintenance management system for the power transformation equipment based on big data, which aims to overcome the defects of the prior art, enhance the daily operation and maintenance management working quality of the power transformation equipment, enhance the supervision control on acceptance and operation and maintenance, and finally realize the high-level operation of the power transmission and transformation equipment.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: the intelligent lean overhaul management system for the power transformation equipment based on the big data comprises a physical equipment layer for supporting the normal operation of the system, a data source layer for collecting and managing the relevant data of the power transformation equipment, a business function supporting layer for carrying out big data analysis by using the data of the data source layer and a primary application function layer for guiding the operation of a power grid according to real-time analysis data, wherein the data source layer is established on the physical equipment layer; meanwhile, the management system also comprises a maintenance management subsystem, a defect management subsystem, an equipment visualization management subsystem, a high-voltage test management subsystem and a big data analysis subsystem which are abstracted on the basis of the service function supporting layer;
the maintenance management subsystem automatically counts the operation years of the power transformation equipment according to the nameplate pictures recorded by the equipment ledger; automatically planning time period nodes of a maintenance scheduling plan of the power transformation equipment according to the running state and the historical state of the power transformation equipment, automatically planning a maintenance test plan of the power transformation equipment, making a next-year power failure plan, automatically issuing the power failure plan to managers and various professional teams and groups, and continuously and automatically correcting the maintenance test plan according to the temporary maintenance plan along with the accumulation of the loss elimination record, the maintenance record and the pre-test record data to generate a latest record;
the defect management subsystem carries out equipment defect management and index management on the power transformation equipment, constructs a defect elimination library, judges the operation trend of the power transformation equipment according to the evaluation state of the power transformation equipment recorded by the defects of the past year, gives maintenance suggestions and supervises the defects;
the equipment visualization management subsystem constructs a three-dimensional digital model of the transformer substation by using a visualization spatial information technology, visually presents the geographical position of the transformer substation in real time and displays the distribution of the transformer substation; meanwhile, a real scene is simulated three-dimensionally, three-dimensional digital models and information attributes of all power transformation equipment are organically combined, and the integrated management of functions of operation monitoring, operation and control, comprehensive information analysis, operation management and auxiliary application of the power transformation equipment is realized by adopting a network-based information processing technology;
the high-voltage test management subsystem manages related test items of all the power transformation primary equipment according to the requirements of a routine test operation instruction, and standardizes corresponding test methods and procedures, and standardizes test instruments and equipment; meanwhile, various systems and standards used by the testers are imported into the system;
the big data analysis subsystem analyzes the related data of the power transformation equipment based on the big data analysis and mining technology, realizes the analysis and information prompt of the related service of the defect, and provides reasonable suggestions for the defect treatment of the power transformation equipment.
Preferably, the data source layer collects and manages related data of the multi-source heterogeneous power equipment from different data sources; the data source layer collects and manages the related data of the multi-source heterogeneous power equipment and directly and indirectly reflects the state information of the power equipment; according to the update frequency of the state information of the power equipment, the state information of different sources is divided into 3 types: static data, dynamic data and quasi-dynamic data; the static data includes: equipment account, technical parameters, test data before commissioning and geographical position; the dynamic data are updated according to periods and comprise power transformation equipment operation data, routing inspection data, live detection data, online detection data and environmental meteorological data of the area where the power transformation equipment is located; the quasi-dynamic data comprises equipment overhaul test data, defect/fault/hidden danger records, overhaul records and defect elimination records.
Preferably, the service function support layer comprises a method center and a data center; the method center provides various big data-based relevant models and algorithms, wherein the models comprise a data integration model, a data topology analysis model, a data simulation model and a big data application algorithm model, and the algorithms comprise a deletion strategy recommendation algorithm, a maintenance strategy recommendation algorithm and a test period reminding algorithm; the data center processes the data related to the power equipment of the data source layer, including data import and entry, data analysis and mining processing, data cleaning and reconstruction, and performs partition integration on the power equipment data according to the characteristics of the data.
Preferably, the data center extracts, cleans, converts and loads the relevant data of the power equipment through an ETL tool, and then imports the relevant data into a relevant theme of a data warehouse, and guarantees the quality of the data through relevant rules.
Preferably, the first-level application function layer accesses each subsystem abstracted based on the service function support layer by calling a related service interface to obtain a substation equipment related analysis result based on big data, analyzes familial defects and operation trends of the substation equipment based on the analysis result, provides decision support for procurement, defect early warning and maintenance plans of the substation equipment, and provides guidance for daily work of a maintenance class, a relay protection class, an electrical measuring instrument, an automation class and a management department.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in: according to the intelligent lean overhaul management system for the power transformation equipment based on the big data, provided by the invention, the MIS system, the equipment management system, the workflow data, the historical data and the existing system data of power production are integrated in multiple ways through big data correlation technology, so that an overhaul data center of the power transformation equipment of the power supply bureau is constructed. Meanwhile, a big data analysis system is constructed, the operation state of the power equipment can be analyzed, and data reference is provided for daily operation work of the transformer substation. An overhaul management subsystem, a defect management subsystem, an equipment visual management subsystem and a high-voltage test management subsystem are built by depending on a large data platform, and the daily operation work and the effective management of the transformer substation are carried out. The platform is combined with a main service scene and an analysis model of the state evaluation of the power equipment, and the platform is used for analyzing the incidence relation and the internal rule of a large amount of equipment state real-time data and historical data, so that the functions of abnormality detection, dynamic evaluation, state prediction, fault diagnosis and the like of the power equipment are realized. And finally, displaying the comprehensive evaluation diagnosis result and the analysis process by utilizing a multi-dimensional and multi-angle visualization technology, and providing an optimization decision support for services such as equipment operation and maintenance, power grid dispatching operation, substation equipment management and the like.
According to the invention, through a big data analysis technology, the coordination capability and the working efficiency among all departments are improved, and the human resource cost is reduced. Through lean management of the power equipment, equipment defect analysis, familial defect analysis, equipment operation trend analysis, equipment defect early warning and equipment purchasing decision recommendation are performed on the power equipment, important reference is provided for daily work of related personnel of a transformer substation, and reliability and working efficiency of the daily operation and maintenance work are improved. According to the cross-platform big data analysis, the defects of the power transformation equipment can be early warned, related personnel are reminded to handle, and problems can be timely handled.
Drawings
Fig. 1 is a system structural block diagram of a transformer equipment intelligent lean overhaul management system based on big data according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In this embodiment, an ultra-high voltage power supply office in the ukai city is taken as an example, and the transformer equipment intelligent lean overhaul management system based on big data of the present invention is adopted to manage overhaul of the transformer equipment governed by the power supply office.
In this embodiment, the intelligent lean overhaul management system for the power transformation equipment based on the big data, as shown in fig. 1, includes a physical equipment layer for supporting the normal operation of the system, a data source layer for collecting and managing data related to the power transformation equipment, which is established on the physical equipment layer, a service function support layer for performing big data analysis by using the data of the data source layer, and a primary application function layer for guiding the operation of the power grid according to the real-time analysis data; meanwhile, the management system also comprises a maintenance management subsystem, a defect management subsystem, an equipment visualization management subsystem, a high-voltage test management subsystem and a big data analysis subsystem which are abstracted on the basis of the service function supporting layer;
in this embodiment, the physical device layer mainly includes hardware devices such as a router, a switch, and a server; the data source layer collects and manages related data of the multi-source heterogeneous power equipment from different data sources such as a database, a network, an MIS system, data collection and transmission equipment and the like; the data source layer collects and manages related data of the multi-source heterogeneous power equipment and covers information capable of directly and indirectly reflecting the state of the power equipment; according to the update frequency of the state information of the power equipment, the state information of different sources is divided into 3 types: static data, dynamic data and quasi-dynamic data; the static data includes: equipment account, technical parameters, test data before commissioning and geographical position; the dynamic data is updated according to the period of minutes, hours or days, is key data for reflecting state changes, and comprises power transformation equipment operation data, routing inspection data, live detection data, online detection data and environmental meteorological data of the area where the power equipment is located; the quasi-dynamic data is updated regularly or irregularly according to the month or year, and comprises equipment maintenance test data, defect/fault/hidden danger records, maintenance records, defect elimination records and the like.
The service function supporting layer comprises a method center and a data center; in the embodiment, the method center mainly relies on golden eye MLAL national letter cloud service machine learning algorithm library software to provide various big data-based related models and algorithms, wherein the models comprise a data integration model, a data topology analysis model, a data simulation model and a big data application algorithm model, and the algorithms comprise a deletion strategy recommendation algorithm, a maintenance strategy recommendation algorithm and a test period reminding algorithm; the data center processes the relevant data of the power equipment of the data source layer by relying on golden eye BDIS national letter cloud service relevant big data software, including data importing and inputting, data analyzing and mining processing, data cleaning and reconstructing, and conducts partition integration on the data of the power equipment according to the characteristics of the data. In this embodiment, the data center integrates the power equipment data partitions into overhaul data, defect elimination data, test data, a defect elimination policy library, an overhaul policy library, a spare part library, and a tool library.
In this embodiment, the processing method of the data center includes the following steps of firstly performing extraction, cleaning, conversion, and loading by using an ETL tool to realize centralized collection of data of different data sources, and then performing outflow in a fixed format. Therefore, incomplete and inaccurate useless data are eliminated, and the accuracy and analyzable value of the data are improved. And then, the processed data is stored and solidified in a file layer, and is read and written and supported by a file read-write engine HDFS which is matched with the analysis and processing of the big data, so that the parallel and multi-layer data processing during the big data processing is supported, and the data processing of the system is supported with high precision. The method has strong storage read-write capability and gives data kinetic energy to enterprise data. And finally, managing and controlling the data quality, mainly checking according to configured rules and submitting a data quality report. Aiming at the submitted data quality report, system maintenance personnel and service personnel can correct system bugs according to the data and adjust the service flow, which is beneficial feedback on the front of the system.
The first-level application function layer accesses each subsystem abstracted based on the service function support layer by calling related service interfaces to obtain substation equipment related analysis results based on big data, analyzes familial defects and operation trends of the substation equipment based on the analysis results, provides decision support for purchasing of the substation equipment, defect early warning and maintenance plans, and provides guidance for daily work of a maintenance class, a relay protection class, an electric measuring instrument, an automation class and a management department so as to timely perform corresponding processing.
In the embodiment, the overhaul management subsystem is closely attached to the overhaul work design of the Ughai ultrahigh-voltage power supply bureau, and the operation life of the power transformation equipment is automatically counted according to the nameplate picture recorded by the equipment ledger; according to the operation state and the historical state of the power transformation equipment, automatically planning time period nodes of a maintenance scheduling plan of the power transformation equipment, automatically planning a maintenance test plan of the power transformation equipment, making a next-year power failure plan, automatically issuing the maintenance test plan to managers and various professional teams and groups in the forms of computer clients, WeChat and the like, and continuously and automatically correcting the maintenance test plan according to the temporary maintenance plan along with the accumulation of the loss elimination record, the maintenance record and the pre-test record data to generate a latest record; the maintenance reminding meeting is timely pushed to relevant workers, maintenance work is comprehensively arranged, maintenance treatment comprises maintenance strategy selection, maintenance equipment, tools and spare parts are confirmed, and the system recommends the optimal strategy for the user to select according to historical data and keyword analysis.
The defect management subsystem carries out equipment defect management and index management on the power transformation equipment, constructs a defect elimination library, judges the operation trend of the power transformation equipment according to the evaluation state of the defect record of the power transformation equipment in the past year, gives reasonable maintenance suggestions and supervises the defects; and obtaining the defect elimination primary and secondary arrangement according to analysis, supervising each professional team to eliminate defects and forming simple and effective closed-loop management.
The equipment visualization management subsystem constructs a three-dimensional digital model of the transformer substation by using a visualization spatial information technology, visually presents the geographical position of the transformer substation in real time and displays the distribution of the transformer substation; meanwhile, a real scene is simulated three-dimensionally, three-dimensional digital models and information attributes of all power transformation equipment are organically combined, and the integrated management of functions of operation monitoring, operation and control, comprehensive information analysis, operation management and auxiliary application (maintenance, operation inspection and the like) of the power transformation equipment is realized by adopting a network-based information processing technology; the method provides a detailed functional sub-picture (three-dimensional visualization) for each power transformation device and each loop, and through the picture, before a maintenance task or defect elimination, maintenance testing personnel can clearly, visually and detailedly check related power transformation device nameplate data, and conveniently perform query operation of the device, including checking device information and running state, alarming, fault signals and the like. The overhaul test personnel can visually and intuitively observe various transformer equipment information and equipment ledger data by calling and looking up the picture, including checking the current conditions of the transformer equipment and the conditions of historical maintenance, defects and the like.
The high-voltage test management subsystem manages related test items of all the power transformation primary equipment according to the requirements of a routine test operation instruction, and standardizes corresponding test methods and procedures, and standardizes test instruments and equipment; meanwhile, various systems and standards used by testers are imported into the system, so that query and download are facilitated; the experimenter can preview the experiment operation and learn the attention matters of the experiment. The high-voltage test management subsystem can also automatically prompt test arrangement and test preparation before test, so that technicians can be familiar with the test process conveniently, and misoperation is reduced. After the test is finished, the tester can upload a test report and fill in special conditions of the test to accumulate data information for subsequent tests and overhaul.
The big data analysis module analyzes the related data of the power transformation equipment based on the big data analysis and mining technology, realizes the analysis and information prompt of the business related to the defect, and provides reasonable suggestions for the defect treatment of the power transformation equipment.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.

Claims (5)

1. The utility model provides a transformer equipment intelligence lean overhaul management system based on big data which characterized in that: the system comprises a physical equipment layer for supporting normal operation of a system, a data source layer which is established on the physical equipment layer and is used for collecting and managing related data of the power transformation equipment, a service function supporting layer which is used for carrying out big data analysis by utilizing the data of the data source layer and a primary application function layer which is used for guiding the operation of a power grid according to real-time analysis data; meanwhile, the management system also comprises a maintenance management subsystem, a defect management subsystem, an equipment visualization management subsystem, a high-voltage test management subsystem and a big data analysis subsystem which are abstracted on the basis of the service function supporting layer;
the maintenance management subsystem automatically counts the operation years of the power transformation equipment according to the nameplate pictures recorded by the equipment ledger; automatically planning time period nodes of a maintenance scheduling plan of the power transformation equipment according to the running state and the historical state of the power transformation equipment, automatically planning a maintenance test plan of the power transformation equipment, making a next-year power failure plan, automatically issuing the power failure plan to managers and various professional teams and groups, and continuously and automatically correcting the maintenance test plan according to the temporary maintenance plan along with the accumulation of the loss elimination record, the maintenance record and the pre-test record data to generate a latest record;
the defect management subsystem carries out equipment defect management and index management on the power transformation equipment, constructs a defect elimination library, judges the operation trend of the power transformation equipment according to the evaluation state of the power transformation equipment recorded by the defects of the past year, gives maintenance suggestions and supervises the defects;
the equipment visualization management subsystem constructs a three-dimensional digital model of the transformer substation by using a visualization spatial information technology, visually presents the geographical position of the transformer substation in real time and displays the distribution of the transformer substation; meanwhile, a real scene is simulated three-dimensionally, three-dimensional digital models and information attributes of all power transformation equipment are organically combined, and the integrated management of functions of operation monitoring, operation and control, comprehensive information analysis, operation management and auxiliary application of the power transformation equipment is realized by adopting a network-based information processing technology;
the high-voltage test management subsystem manages related test items of all the power transformation primary equipment according to the requirements of a routine test operation instruction, and standardizes corresponding test methods and procedures, and standardizes test instruments and equipment; meanwhile, various systems and standards used by the testers are imported into the system;
the big data analysis subsystem analyzes the related data of the power transformation equipment based on the big data analysis and mining technology, realizes the analysis and information prompt of the related service of the defect, and provides reasonable suggestions for the defect treatment of the power transformation equipment.
2. The big data based power transformation device intelligent lean overhaul management system according to claim 1, wherein: the data source layer collects and manages related data of multi-source heterogeneous power equipment from different data sources; the data source layer collects and manages the related data of the multi-source heterogeneous power equipment and directly and indirectly reflects the state information of the power equipment; according to the update frequency of the state information of the power equipment, the state information of different sources is divided into 3 types: static data, dynamic data and quasi-dynamic data; the static data includes: equipment account, technical parameters, test data before commissioning and geographical position; the dynamic data are updated according to periods and comprise power transformation equipment operation data, routing inspection data, live detection data, online detection data and environmental meteorological data of the area where the power transformation equipment is located; the quasi-dynamic data comprises equipment overhaul test data, defect/fault/hidden danger records, overhaul records and defect elimination records.
3. The big data based power transformation device intelligent lean overhaul management system according to claim 1, wherein: the service function supporting layer comprises a method center and a data center; the method center provides various big data-based relevant models and algorithms, wherein the models comprise a data integration model, a data topology analysis model, a data simulation model and a big data application algorithm model, and the algorithms comprise a deletion strategy recommendation algorithm, a maintenance strategy recommendation algorithm and a test period reminding algorithm; the data center processes the data related to the power equipment of the data source layer, including data import and entry, data analysis and mining processing, data cleaning and reconstruction, and performs partition integration on the power equipment data according to the characteristics of the data.
4. The big data based power transformation device intelligent lean overhaul management system according to claim 1, wherein: the data center extracts, cleans, converts and loads the relevant data of the power equipment through an ETL tool, and then leads the data into the relevant subjects of the data warehouse, and guarantees the quality of the data through relevant rules.
5. The big data based power transformation device intelligent lean overhaul management system according to claim 1, wherein: the first-level application function layer accesses each subsystem abstracted based on the service function support layer by calling related service interfaces to obtain substation equipment related analysis results based on big data, analyzes familial defects and operation trends of the substation equipment based on the analysis results, provides decision support for purchasing of the substation equipment, defect early warning and maintenance plans, and provides guidance for daily work of a maintenance class, a relay protection class, an electrical measuring instrument, an automation class and a management department.
CN202011186848.XA 2020-10-30 2020-10-30 Intelligent lean overhaul management system for power transformation equipment based on big data Pending CN112270619A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011186848.XA CN112270619A (en) 2020-10-30 2020-10-30 Intelligent lean overhaul management system for power transformation equipment based on big data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011186848.XA CN112270619A (en) 2020-10-30 2020-10-30 Intelligent lean overhaul management system for power transformation equipment based on big data

Publications (1)

Publication Number Publication Date
CN112270619A true CN112270619A (en) 2021-01-26

Family

ID=74344322

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011186848.XA Pending CN112270619A (en) 2020-10-30 2020-10-30 Intelligent lean overhaul management system for power transformation equipment based on big data

Country Status (1)

Country Link
CN (1) CN112270619A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113780596A (en) * 2021-09-14 2021-12-10 广州汇通国信科技有限公司 Power station intelligent operation and maintenance method and system based on big data

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH04344967A (en) * 1991-05-22 1992-12-01 Hitachi Ltd Supporting device for equipment maintenance management optimization
CN107609987A (en) * 2017-09-19 2018-01-19 广西电网有限责任公司电力科学研究院 A kind of intelligent power transformation operational system of equipment oriented owner
CN107977714A (en) * 2017-11-08 2018-05-01 天津市普迅电力信息技术有限公司 A kind of intelligent control platform of power transformation fortune inspection
CN110932405A (en) * 2019-12-17 2020-03-27 沈阳博来德滋电子科技有限公司 Intelligent monitoring and analyzing system for power transformation equipment based on big data

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH04344967A (en) * 1991-05-22 1992-12-01 Hitachi Ltd Supporting device for equipment maintenance management optimization
CN107609987A (en) * 2017-09-19 2018-01-19 广西电网有限责任公司电力科学研究院 A kind of intelligent power transformation operational system of equipment oriented owner
CN107977714A (en) * 2017-11-08 2018-05-01 天津市普迅电力信息技术有限公司 A kind of intelligent control platform of power transformation fortune inspection
CN110932405A (en) * 2019-12-17 2020-03-27 沈阳博来德滋电子科技有限公司 Intelligent monitoring and analyzing system for power transformation equipment based on big data

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113780596A (en) * 2021-09-14 2021-12-10 广州汇通国信科技有限公司 Power station intelligent operation and maintenance method and system based on big data

Similar Documents

Publication Publication Date Title
CN109978052B (en) Intelligent maintenance method for user-side energy equipment
CN104638764A (en) Intelligent state diagnosis and overhauling system for power distribution network equipment
CN114493213A (en) Carbon emission data acquisition and processing method based on Internet of things
CN105652232B (en) A kind of online abnormality diagnostic method of electric power meter based on stream process and system
CN108282026A (en) A kind of high-tension switch gear novel maintenance system
CN109857080B (en) Intelligent ship lock operation and maintenance system based on BIM
CN105574593B (en) Track state static detection and control system and method based on cloud computing and big data
CN107066500B (en) Power grid mass data quality verification method based on PMS model
CN108418849A (en) A kind of oil-gas pipeline SCADA system
CN112633531A (en) Wind power plant operation maintenance system
CN113315222A (en) Intelligent substation automation equipment operation and maintenance management and control system suitable for electric power system
CN113902241A (en) Power grid equipment maintenance strategy system and method based on comprehensive state evaluation
CN113722311A (en) Power distribution network power failure range positioning method, system, equipment and medium
CN115689177A (en) Machine learning-based intelligent scheduling strategy method for transformer maintenance plan
CN113537523A (en) Substation equipment state maintenance and decision-making assisting method
CN107301498A (en) Generalized information management system for the military service monitoring of high-speed railway wheel rail relation
CN102624096B (en) Intelligent supervisory system for power distribution field operation
CN112613066A (en) Internet information management system based on large-scale wind power plant
CN115908046A (en) Visual power distribution system based on airport terminal building BIM
CN115718472A (en) Fault scanning and diagnosing method for hydroelectric generating set
CN112270619A (en) Intelligent lean overhaul management system for power transformation equipment based on big data
CN111652500B (en) Automatic on-duty auxiliary system based on scheduling
CN113435721A (en) Method for constructing secondary data center of intelligent substation
CN113420162A (en) Equipment operation chain state monitoring method based on knowledge graph
CN117390944A (en) Substation operation condition simulation system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination