CN111934426A - Big data-based power grid equipment trend fault early warning system - Google Patents
Big data-based power grid equipment trend fault early warning system Download PDFInfo
- Publication number
- CN111934426A CN111934426A CN202010724173.3A CN202010724173A CN111934426A CN 111934426 A CN111934426 A CN 111934426A CN 202010724173 A CN202010724173 A CN 202010724173A CN 111934426 A CN111934426 A CN 111934426A
- Authority
- CN
- China
- Prior art keywords
- data
- module
- unit
- power grid
- early warning
- 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.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Human Computer Interaction (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a big data-based power grid equipment trend fault early warning system which comprises a monitoring module, a transmission module, an analysis module, an auditing module and a control module, wherein the output end of the monitoring module is connected with the input end of the transmission module, the output end of the transmission module is connected with the input end of the analysis module, the output end of the analysis module is connected with the input end of the auditing module, the output end of the auditing module is connected with the input end of the control module, the monitoring module comprises an acquisition unit, an identification unit and a conversion unit, the transmission module comprises a data filtering unit and a data storage unit, the analysis module comprises a data prestoring unit and a data comparison unit, and the control module comprises an automatic matching unit and a manual control unit. The invention has wide monitoring range, early warning and judgment of fault points, improved safety and stability of the use of the power grid equipment, reduced loss caused by the fault of the power grid equipment, reduced inspection work of operation and maintenance personnel and suitability for popularization.
Description
Technical Field
The invention relates to the technical field of power grid equipment maintenance, in particular to a trend fault early warning system for power grid equipment based on big data.
Background
The big data IT industry term refers to a data set which cannot be captured, managed and processed by a conventional software tool within a certain time range, and is a massive, high-growth rate and diversified information asset which can have stronger decision-making power, insight discovery power and flow optimization capability only by a new processing mode; the whole of the substation and the transmission and distribution line of various voltages in the power system is called a power grid. The system comprises three units of power transformation, power transmission and power distribution. The task of the power grid is to deliver and distribute electrical energy, changing the voltage; with the continuous development of society, the application of big data is wider, and the application of the big data on a power grid is gradually popularized and used; if equipment breaks down in the operation of power grid equipment, can cause the influence to the power consumption, seriously cause the short circuit of circuit, cause major accident, and at present the power grid is in operation usually patrolling and examining personnel regularly to the power grid equipment maintenance, and some trouble is to salvage it after having taken place, seriously influence the stability of power consumption, provide a power grid equipment trend nature trouble early warning system based on big data for this reason.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides a trend fault early warning system for power grid equipment based on big data.
The invention provides a big data-based power grid equipment trend fault early warning system which comprises a monitoring module, a transmission module, an analysis module, an auditing module and a control module, wherein the output end of the monitoring module is connected with the input end of the transmission module, the output end of the transmission module is connected with the input end of the analysis module, the output end of the analysis module is connected with the input end of the auditing module, the output end of the auditing module is connected with the input end of the control module, the monitoring module comprises an acquisition unit, an identification unit and a conversion unit, the transmission module comprises a data filtering unit and a data storage unit, the analysis module comprises a data prestoring unit and a data comparison unit, and the control module comprises an automatic matching unit and a manual control unit.
Preferably, the monitoring module is used for monitoring the power grid equipment, the acquisition unit is used for acquiring real-time operation data of the monitoring equipment, the acquisition content comprises equipment flow and equipment temperature, the identification unit is used for identifying the data acquired by the acquisition unit, classifying the data according to different data transmission forms, transmitting the classified data to the conversion unit, the conversion unit is used for converting the classified data received according to internal rules, converting the acquired various data into a uniform framework and ensuring barrier-free transmission of the data in the system, and the conversion unit is also used for converting the acquired information into specific data values.
Preferably, the data filtering unit is configured to divide the collected and converted information into normal data and abnormal data, filter the collected and converted information, filter the normal information, transmit the abnormal data to the data storage unit, and the data storage unit stores and backs up the abnormal information and transmits the abnormal information.
Preferably, the normal information is a data value equal to or less than a rated value, the abnormal information is greater than the rated value, and the rated value is a pre-storage rule.
Preferably, the analysis module judges the abnormal information through a data pre-storage unit and a data comparison unit, the data pre-storage unit is used for storing historical abnormal data, the data comparison unit is used for comparing the abnormal information with the historical abnormal data, and after the historical abnormal data is determined to be larger than or equal to the historical abnormal data, the abnormal information is transmitted to the auditing module.
Preferably, the auditing module is used for judging the abnormal information again, matching the abnormal information with the fault equipment, and displaying the abnormal information in a visual and prominent early warning manner.
Preferably, the monitoring module, the transmission module, the analysis module and the audit module are intelligently connected through a network, and the monitoring module, the transmission module, the analysis module and the audit module are located in the same terminal device to work.
Preferably, the control module is used for matching a solution with the early-warning fault equipment in the system, the automatic matching unit transmits the matched solution and the early-warning fault equipment to the manual control unit, and the manual control unit is used for dispatching personnel to repair and maintain the early-warning fixed point.
According to the power grid equipment trend fault early warning system based on big data, the monitoring module, the transmission module, the analysis module, the auditing module and the control module are arranged, the power grid equipment is monitored one by one in real time through the monitoring module, the monitored data are converted into a unified frame, the converted data are filtered through the data filtering unit, abnormal information is transmitted after being backed up through the data storage unit, the analysis module compares the abnormal information with pre-stored information, the abnormal information is judged again through the auditing module, the abnormal information is matched with fault equipment, visual prominent early warning display is carried out, a solution is matched between an early warning place and the fault equipment through the control module, and a worker is dispatched to carry out technical maintenance; the invention has wide monitoring range, judges the fault point in advance, improves the safety and stability of the use of the power grid equipment, reduces the production loss caused by the fault of the power grid equipment, reduces the routing inspection work of operation and maintenance personnel, and is suitable for popularization.
Drawings
Fig. 1 is a schematic block diagram of a trend fault early warning system for power grid equipment based on big data according to the present invention;
fig. 2 is a partial structural block diagram of a power grid equipment trend fault early warning system based on big data according to the present invention;
fig. 3 is a partial structural block diagram of a power grid equipment trend fault early warning system based on big data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
Referring to fig. 1-3, a trend fault early warning system for power grid equipment based on big data comprises a monitoring module, a transmission module, an analysis module, an audit module and a control module, wherein the output end of the monitoring module is connected with the input end of the transmission module, the output end of the transmission module is connected with the input end of the analysis module, the output end of the analysis module is connected with the input end of the audit module, the output end of the audit module is connected with the input end of the control module, the monitoring module comprises a collection unit, a recognition unit and a conversion unit, the transmission module comprises a data filtering unit and a data storage unit, the analysis module comprises a data pre-storage unit and a data comparison unit, the control module comprises an automatic matching unit and a manual control unit, the monitoring module is used for monitoring the power grid equipment, and the collection unit is used for collecting real-time, the acquisition content comprises equipment flow and equipment temperature, the identification unit is used for identifying the data acquired by the acquisition unit and classifying the data according to different data transmission forms, the classified data are transmitted to the conversion unit, the conversion unit is used for converting the classified data received by the acquisition unit according to internal rules and converting the acquired data into a uniform framework for ensuring barrier-free transmission of the data in the system, the conversion unit is also used for converting the acquired information into specific data values, the data filtering unit is used for dividing the acquired and converted information into normal data and abnormal data, the data filtering unit is used for filtering the acquired and converted information, filtering the normal information and transmitting the abnormal data to the data storage unit, the data storage unit stores and backs up the abnormal information and transmits the abnormal information, and the normal information is that the data value is less than or equal to a rated value, the abnormal information is larger than a rated value, the rated value is a pre-storage rule, the analysis module judges the abnormal information through a data pre-storage unit and a data comparison unit, the data pre-storage unit is used for storing historical abnormal data, the data comparison unit is used for comparing the abnormal information with the historical abnormal data, after the historical abnormal data is determined to be larger than or equal to the historical abnormal data, the abnormal information is transmitted to an auditing module, the auditing module is used for judging the abnormal information again, the abnormal information is matched with fault equipment and is displayed through visual prominent early warning, the monitoring module, the transmission module, the analysis module and the auditing module are intelligently connected through a network, the monitoring module, the transmission module, the analysis module and the auditing module are positioned in the same terminal equipment to work, the control module is used for matching the early-warned fault equipment in a system to solve a solution, the automatic matching unit transmits the matched solution and the early warning fault equipment location to the manual control unit, and the manual control unit is used for dispatching personnel to overhaul and maintain the early warning fixed point.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (8)
1. The utility model provides a power grid equipment trend fault early warning system based on big data, includes monitoring module, transmission module, analysis module, examines and repair the module and controls the module, its characterized in that, monitoring module's output is connected with transmission module's input, transmission module's output is connected with analysis module's input, analysis module's output is connected with the input of examining and repairing the module, examine and repair module's output and control module's input and be connected, monitoring module includes acquisition unit, recognition cell and conversion unit, transmission module includes data filter unit and data storage unit, analysis module includes that data prestore unit and data contrast unit, it includes automatic matching unit and artifical management and control unit to control the module.
2. The big-data-based power grid equipment trend fault early warning system as claimed in claim 1, wherein the monitoring module is configured to monitor power grid equipment, the acquisition unit is configured to acquire real-time operation data of the monitoring equipment, the acquisition content includes equipment flow and equipment temperature, the identification unit is configured to identify the data acquired by the acquisition unit, classify the data according to different transmission forms of the data, and transmit the classified data to the conversion unit, the conversion unit is configured to convert the classified data received by the conversion unit according to internal rules, and convert the acquired data into a unified framework, so as to ensure that the data is transmitted without obstacles in the system, and the conversion unit is further configured to convert the acquired information into specific data values.
3. The big data-based power grid equipment trend fault early warning system as claimed in claim 1, wherein the data filtering unit is configured to divide the collected and converted information into normal data and abnormal data, the data filtering unit filters the collected and converted information, filters the normal information, and transmits the abnormal data to the data storage unit, and the data storage unit stores and backs up the abnormal information and transmits the abnormal information.
4. The big data-based power grid equipment trend fault early warning system as claimed in claim 3, wherein the normal information is that the data value is less than or equal to a rated value, the abnormal information is greater than the rated value, and the rated value is a pre-storage rule.
5. The big-data-based power grid equipment trend fault early warning system according to claim 4, wherein the analysis module judges the abnormal information through a data pre-storage unit and a data comparison unit, the data pre-storage unit is used for storing historical abnormal data, the data comparison unit is used for comparing the abnormal information with the historical abnormal data, and after the historical abnormal data is determined to be greater than or equal to the historical abnormal data, the abnormal information is transmitted to the auditing module.
6. The big-data-based power grid equipment trend fault early warning system as claimed in claim 5, wherein the auditing module is configured to determine the abnormal information again, match the abnormal information with the faulty equipment, and highlight the early warning display visually.
7. The big-data-based power grid equipment trend fault early warning system as claimed in claim 1, wherein the monitoring module, the transmission module, the analysis module and the auditing module are intelligently connected through a network, and the monitoring module, the transmission module, the analysis module and the auditing module are located in the same terminal equipment to work.
8. The big data-based power grid equipment trend fault early warning system according to claim 1, wherein the control module is configured to match early-warning fault equipment with a solution in the system, the automatic matching unit is configured to transmit the matched solution and a location of the early-warning fault equipment to a manual management and control unit, and the manual management and control unit is configured to dispatch personnel to repair and maintain an early-warning fixed point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010724173.3A CN111934426B (en) | 2020-07-24 | 2020-07-24 | Power grid equipment trend fault early warning system based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010724173.3A CN111934426B (en) | 2020-07-24 | 2020-07-24 | Power grid equipment trend fault early warning system based on big data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111934426A true CN111934426A (en) | 2020-11-13 |
| CN111934426B CN111934426B (en) | 2023-08-01 |
Family
ID=73315501
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010724173.3A Active CN111934426B (en) | 2020-07-24 | 2020-07-24 | Power grid equipment trend fault early warning system based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111934426B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112529363A (en) * | 2020-11-17 | 2021-03-19 | 国网浙江省电力有限公司湖州供电公司 | Automatic analysis and automatic optimal reconstruction system and method for power grid faults |
| CN115331155A (en) * | 2022-10-14 | 2022-11-11 | 智慧齐鲁(山东)大数据科技有限公司 | Mass video monitoring point location graph state detection method and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090187344A1 (en) * | 2008-01-19 | 2009-07-23 | Brancaccio Daniel S | System, Method, and Computer Program Product for Analyzing Power Grid Data |
| CN104810926A (en) * | 2015-05-06 | 2015-07-29 | 杨启蓓 | Intelligent multidimensional big-data analyzing expert system for high-voltage circuit breakers of power grid |
| CN208939660U (en) * | 2018-08-31 | 2019-06-04 | 国家电网有限公司 | A kind of grid equipment maintenance prior-warning device |
| CN110264679A (en) * | 2019-06-18 | 2019-09-20 | 国网山东省电力公司沂南县供电公司 | Power distribution cabinet monitors system and method |
| CN111060149A (en) * | 2019-11-22 | 2020-04-24 | 广东电网有限责任公司云浮供电局 | Data monitoring method and device based on power equipment |
| CN111260504A (en) * | 2020-02-11 | 2020-06-09 | 吴龙圣 | Intelligent power grid monitoring method and system and intelligent power grid controller |
-
2020
- 2020-07-24 CN CN202010724173.3A patent/CN111934426B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090187344A1 (en) * | 2008-01-19 | 2009-07-23 | Brancaccio Daniel S | System, Method, and Computer Program Product for Analyzing Power Grid Data |
| CN104810926A (en) * | 2015-05-06 | 2015-07-29 | 杨启蓓 | Intelligent multidimensional big-data analyzing expert system for high-voltage circuit breakers of power grid |
| CN208939660U (en) * | 2018-08-31 | 2019-06-04 | 国家电网有限公司 | A kind of grid equipment maintenance prior-warning device |
| CN110264679A (en) * | 2019-06-18 | 2019-09-20 | 国网山东省电力公司沂南县供电公司 | Power distribution cabinet monitors system and method |
| CN111060149A (en) * | 2019-11-22 | 2020-04-24 | 广东电网有限责任公司云浮供电局 | Data monitoring method and device based on power equipment |
| CN111260504A (en) * | 2020-02-11 | 2020-06-09 | 吴龙圣 | Intelligent power grid monitoring method and system and intelligent power grid controller |
Non-Patent Citations (1)
| Title |
|---|
| 赵光平;曲娓;: "新型配电智能监控系统的设计与实现", 自动化博览, no. 08 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112529363A (en) * | 2020-11-17 | 2021-03-19 | 国网浙江省电力有限公司湖州供电公司 | Automatic analysis and automatic optimal reconstruction system and method for power grid faults |
| CN115331155A (en) * | 2022-10-14 | 2022-11-11 | 智慧齐鲁(山东)大数据科技有限公司 | Mass video monitoring point location graph state detection method and system |
| CN115331155B (en) * | 2022-10-14 | 2023-02-03 | 智慧齐鲁(山东)大数据科技有限公司 | Mass video monitoring point location graph state detection method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111934426B (en) | 2023-08-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106655522B (en) | A kind of main station system suitable for electric grid secondary equipment operation management | |
| CN107991525B (en) | Green industry park electricity supply and utilization efficiency monitoring and fault responsibility identification method and system | |
| CN104020754B (en) | Method for enabling state monitoring information of transformer station primary main equipment to access to regulation and control system | |
| CN114757590B (en) | Enterprise operation risk early warning and management and control system based on big data analysis | |
| CN107798395A (en) | A kind of power grid accident signal automatic diagnosis method and system | |
| CN111934426A (en) | Big data-based power grid equipment trend fault early warning system | |
| CN110912273B (en) | Distribution network ground fault analysis management system | |
| CN110751338A (en) | Construction and early warning method for heavy overload characteristic model of distribution transformer area | |
| CN113193549B (en) | System and method for regulating and controlling transaction perception and fault co-processing | |
| CN111600743A (en) | Intelligent operation and maintenance system based on big data | |
| CN114928166A (en) | Medical equipment power distribution monitoring management system | |
| CN115293370A (en) | Digital integrated operation and maintenance management system of distributed photovoltaic power station | |
| CN103885372B (en) | A kind of Switching Power Supply rectification module monitoring and early warning method and system | |
| CN112488361B (en) | Transformer area low voltage prediction method and device based on big data | |
| CN110310009A (en) | A kind of alarm of dispatching of power netwoks operation risk and panorama appraisal procedure | |
| CN113346622A (en) | Power grid operation risk intelligent warning system based on big data analysis | |
| CN111509839A (en) | Trip event model analysis method based on alarm signal | |
| CN117614137A (en) | Power distribution network optimization system based on multi-source data fusion | |
| CN116488351A (en) | Low-voltage distribution box remote monitoring method and system based on Internet of things | |
| CN113097981B (en) | Method for judging missing of monitoring alarm signal of transformer substation | |
| CN115313662A (en) | Distribution automation intelligence auxiliary tool that patrols and examines | |
| CN115441581A (en) | Large-scale power grid safety and intelligent scheduling system based on big data | |
| CN111416434A (en) | Distribution network load online monitoring system and method | |
| CN113013987B (en) | Intelligent automatic power grid monitoring system and working method thereof | |
| CN213717610U (en) | Distribution network protection fixed value setting system based on full information data flow |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |