CN106325252A - Multi-level large-span large data oriented power equipment state monitoring and evaluating system - Google Patents
Multi-level large-span large data oriented power equipment state monitoring and evaluating system Download PDFInfo
- Publication number
- CN106325252A CN106325252A CN201610862853.5A CN201610862853A CN106325252A CN 106325252 A CN106325252 A CN 106325252A CN 201610862853 A CN201610862853 A CN 201610862853A CN 106325252 A CN106325252 A CN 106325252A
- Authority
- CN
- China
- Prior art keywords
- data
- ied
- monitoring
- state monitoring
- assessment
- 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
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 129
- 230000005540 biological transmission Effects 0.000 claims abstract description 17
- 238000007405 data analysis Methods 0.000 claims abstract description 7
- 238000005516 engineering process Methods 0.000 claims abstract description 5
- 238000000034 method Methods 0.000 claims description 20
- 230000008569 process Effects 0.000 claims description 14
- 238000007726 management method Methods 0.000 claims description 11
- 238000012546 transfer Methods 0.000 claims description 10
- 238000013523 data management Methods 0.000 claims description 8
- 238000006243 chemical reaction Methods 0.000 claims description 7
- 238000007418 data mining Methods 0.000 claims description 7
- 238000012423 maintenance Methods 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 claims description 6
- 238000004891 communication Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 5
- 230000004888 barrier function Effects 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 4
- 239000000203 mixture Substances 0.000 claims description 4
- 238000012502 risk assessment Methods 0.000 claims description 4
- 238000012098 association analyses Methods 0.000 claims description 3
- 238000010224 classification analysis Methods 0.000 claims description 3
- 238000007621 cluster analysis Methods 0.000 claims description 3
- 230000009191 jumping Effects 0.000 claims description 3
- 239000013307 optical fiber Substances 0.000 claims description 3
- 238000012731 temporal analysis Methods 0.000 claims description 3
- 238000000700 time series analysis Methods 0.000 claims description 3
- 230000002457 bidirectional effect Effects 0.000 claims description 2
- 238000005265 energy consumption Methods 0.000 claims description 2
- 238000007639 printing Methods 0.000 claims description 2
- 238000000611 regression analysis Methods 0.000 claims description 2
- 238000004140 cleaning Methods 0.000 claims 1
- 238000001514 detection method Methods 0.000 claims 1
- 230000007257 malfunction Effects 0.000 claims 1
- 238000011156 evaluation Methods 0.000 abstract description 3
- 230000036541 health Effects 0.000 abstract description 3
- 230000006855 networking Effects 0.000 abstract 1
- 230000033001 locomotion Effects 0.000 description 5
- 238000010276 construction Methods 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 238000007689 inspection Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- RTZKZFJDLAIYFH-UHFFFAOYSA-N Diethyl ether Chemical compound CCOCC RTZKZFJDLAIYFH-UHFFFAOYSA-N 0.000 description 2
- 230000001413 cellular effect Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 230000003862 health status Effects 0.000 description 2
- 238000009413 insulation Methods 0.000 description 2
- 230000009545 invasion Effects 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 238000012800 visualization Methods 0.000 description 2
- 208000032368 Device malfunction Diseases 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000013517 stratification Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
-
- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses a multi-level large-span large data oriented power equipment state monitoring and evaluating system. The system is divided into four levels: an acquisition and convergence level, a station control layer, a provincial network level and a headquarter level. The acquisition and convergence level is further divided into a convergence sub-system and an acquisition sub-system. The station control level comprises a state monitoring server, a working station, a mobile terminal accessing device and a mobile terminal. The state monitoring server saves data of gateway transmission and is connected with the working station and the mobile terminal accessing device through an Ethernet. According to the invention, the advanced wireless sensor networking technology is organically combined with a power equipment state monitoring system, which realizes the full digitalization and integrated informationization from a primary power equipment terminal to a provincial headquarter level. Based on a computing platform of large data analysis and the risk evaluations on multi-time-and-space system, it is possible to provide powerful data support for decision makers so that full service life health prediction and periodical management can be completed to equipment assets.
Description
Technical field
The invention belongs to status of electric power research field, particularly to a kind of multilayer large-span towards the electric power of big data
Equipment condition monitoring and assessment system.
Background technology
Intelligent grid is the point of economic increase of current international forefront, has become as many countries and falls over each other the focus of research.
As an important application system of intelligent grid, power equipment state monitoring and assessment system complete to join status of electric power
Number gathers, analyzes, it is achieved status visualization, and according to the state of power equipment, this equipment is estimated early warning, and takes
Corresponding measure.By improving power equipment reliability of operation and controllability, and then improve overall power supply reliability, state
The intelligent functions of monitoring system can be that the whole decision of intelligent grid provides solid foundation.
The method of conventional electric power equipment condition monitoring uses the methods such as periodic preventative maintenance, test and manual patrol.
In order to avoid accident occur, in equipment running process, operator on duty needs often to make an inspection tour, by outward appearance phenomenon, reading instument,
Artificial experience etc. carry out judging to note abnormalities in time.In addition, also can the most out of service come customary to power equipment
Check, do mechanical action test or preventative Insulation Test, make the process etc. in terms of fault of construction in time.This regular inspection
Repair and often the method maked an inspection tour serves vital effect to the safety of power equipment is properly functioning.
In recent years, domestic and international power equipment state monitoring achieves bigger progress in terms of theoretical research, and have developed
For the condition monitoring and fault diagnosis device of the equipment such as transmission line of electricity, transformator and chopper, but supervise at status of electric power
Survey and still face a lot of outstanding problem at a lot of aspects.Power equipment state monitoring system is also in the dispersion monitoring stage, with calculating
Machine monitoring system is separate, between power control center and each transformer station, and condition monitoring system and other system it
Between, data message model and communication interface high isomerism, it is difficult to make full use of different information and carry out the state estimation of equipment, event
Barrier diagnosis and repair based on condition of component.In intelligent grid, power equipment state monitoring data have a characteristic that
(1) Condition Monitoring Data amount is that geometry character increases, and data scale constantly expands；Data type complexity is various, kind
Various；Monitoring Data wide area is distributed；Calculating task is various, computationally intensive；Data reliability is high with requirement of real-time.
(2) each platform data interactivity is poor.
In the face of these magnanimity, distributed, isomery, complexity, intensive status data, conventional data storage
It is difficult in adapt to intelligent grid to Condition Monitoring Data reliability and the requirements at the higher level of real-time with management method system.
Therefore, in the urgent need to set up a set of towards big data, unified, open, meet intelligent grid equipment development
The power equipment state monitoring system needed, it is achieved quick evaluating status of electric power, condition diagnosing and the prediction of large span,
Thus realizing health status and the time between overhauls(TBO) of intelligent evaluation equipment, the life-cycle health forecast completing asset of equipments was managed with the cycle
Reason.
Summary of the invention
It is an object of the invention to provide a kind of multilayer large-span towards the power equipment state monitoring of big data and assessment system
System, it is characterised in that described equipment condition monitoring and assessment system are divided into four layers: gather convergence-level, station level, province's stratum reticulare and total
Portion's layer；Described collection convergence-level is divided into again convergence subsystem and acquisition subsystem；Described station level include status monitoring services device,
Work station, mobile terminal access device and mobile terminal；The data of described status monitoring services device storage gateway transmission, and pass through
Ethernet is connected with work station and mobile terminal access device；
Described province stratum reticulare is built based on cloud platform, including big data management platform and shape based on data mining algorithm
State assessment system.In view of the safety of cloud platform, utilize fire wall cloud platform to be isolated with external network, and be mounted with invasion
Detecting system, prevents malicious attack；
Described general headquarters layer includes decision-making management work station, big ping server and Decision Support Servers；General headquarters layers obtain and
Collecting assessment data, decision-making management work station obtains warning data according to assessment data, submits abort situation and advanced warning grade to,
Big ping server output result, it is achieved assessment result visualizes；SMT Station Management person provides final decision, carries out assessment result
Decision support further.
Described acquisition subsystem is as the whole system bottom, including multiple primary equipment status monitoring IED group, state
Monitoring IED is attached directly on primary equipment；In status monitoring IED, various kinds of sensors gathers primary equipment relevant information respectively,
Data processing module collects and carries out simple computation, and ZigBee module uses the form sending broadcast to send information to converge
IED, is set to 1 jumping broadcast radius here and just disclosure satisfy that system needs；ZigBee be one closely, low complex degree, low
Power consumption, low rate, the bidirectional wireless communication technology of low cost.It is mainly used in apart from the highest each of short, low in energy consumption and transfer rate
Plant and carry out data transmission between electronic equipment；IED is the abbreviation of intelligent electronic device.
Described convergence subsystem includes converging IED group and coordinating concentrator；All kinds of primary equipments converge IED composition and converge
IED group；Described coordination concentrator includes coordinator and gateway；Converge IED group and expand ZigBee transmission range, converge IED and connect
Receive the broadcast that the status monitoring IED of acquisition subsystem sends, first carry out identification, only process corresponding state monitoring
The message that IED sends；ZigBee module is sent to coordinator by converging the information after IED processes by clean culture；Coordinator is responsible for
The establishment of whole network, maintenance, and collect the information that each convergence IED sends, utilize optical fiber to pass through RS 485 serial ports by data
Being transferred to gateway, gateway carries out protocol conversion, and transfers data to server by Ethernet.
Described work station mainly includes monitor workstation, engineer work station and data operation element station；Described monitoring work
Make station provide primary equipment Condition Monitoring Data graphically to browse, alert, monitor, the service such as control；Described engineer work station
There is provided for engineer and safeguard and improve the service of condition monitoring system, described data manipulation work station provide browsing data, derivation,
Inquiry, printing etc. service.Mobile terminal accesses status monitoring services device, mobile terminal master by mobile terminal safety access device
Malfunction notification to be realized, personnel's informing function.Status monitoring services device is also responsible for transferring data to province's stratum reticulare.Whole station level
System uses C/S structure.
Described province stratum reticulare receives the data of described station level transmission, at big data management platform by converting, clear up, collecting
The technical finesse that one-tenth, classification, non-structural data characteristics are extracted, the higher data of the rate that is obtained by, utilize ETL instrument that data are entered
It is loaded into data warehouse after row extraction, conversion；The data of data warehouse are carried out preliminary search and accident analysis, if it find that therefore
Barrier, alerts to described station level, and station level receives alarm, and fault is carried out on-call maintenance.
In described status assessing system based on data mining algorithm, data are further analyzed and carry out state
Assessment；Utilize time series analysis, cluster analysis, classification analysis, the analysis of non-structural data characteristics, association analysis and/or recurrence
The method analyzed carries out data analysis, and utilizes log generator to generate journal file；Utilization state assessment algorithm assessment data
Analysis result, tracing trouble, and complete risk assessment, save stratum reticulare and transfer data to general headquarters' layer by Ethernet.
Described carrying out identification, only processing the message that corresponding state monitoring IED sends is that GIS converges IED and only processes GIS
The message that status monitoring IED group sends.
During the information after IED processes that converges is sent to coordinator by clean culture by described ZigBee module, it should
Guarantee the proper communication of whole ZigBee-network, i.e. status monitoring IED is set to terminal node, converge IED and be set to route
Device node, coordinator is set to coordinator node；Wherein, terminal node is mainly responsible for the collection of data, can only send data, no
The message of other nodes can be forwarded；Router node is responsible for the Route Selection of packet, coordinator be responsible for whole network establishment,
Safeguard, and can be connected with gateway by serial ports.
The invention has the beneficial effects as follows, solve the problem that current power equipment state monitoring system exists, by advanced nothing
Line sensor network technology organically combines with power equipment state monitoring system, proposes novel multilamellar power equipment state monitoring
System architecture, network span is big, from a power equipment terminal until saving net HQ-level to realize data transmission total digitalization,
Information integral；Introduce cloud computing platform based on big data analysis, improve the sharing degree of data to a greater extent and process magnanimity
Monitoring Data；This system is stratification state assessment, equipment fault prediction, and system risk based on multi-space state estimation is assessed
Deng, it is provided with force data guarantee for intelligence decision support system, thus realizes health status and the time between overhauls(TBO) of intelligent evaluation equipment, complete
The life-cycle health forecast of forming apparatus assets and cycle management.
Accompanying drawing explanation
Fig. 1 is the overall construction drawing of the multilayer large-span power equipment state monitoring towards big data and assessment system.
Fig. 2 be towards big data power equipment state monitoring with assessment system general headquarters' layer and province stratum reticulare software configuration
Figure.
Fig. 3 is the power equipment state monitoring towards big data and the assessment collection convergence-level of system and station level structure
Figure.
Fig. 4 is the primary equipment cellular construction figure of the power equipment state monitoring towards big data and assessment system.
Detailed description of the invention
The present invention provides a kind of multilayer large-span power equipment state monitoring towards big data and assessment system, knot below
Close accompanying drawing, preferred embodiment is elaborated.It should be emphasized that it is that the description below is merely exemplary rather than in order to limit
The scope of the present invention processed and application thereof.
A kind of multilayer large-span shown in Fig. 1 is tied towards the power equipment state monitoring of big data with the overall of assessment system
Composition.In Fig. 1, multilayer large-span is divided into four layers towards power equipment state monitoring and the assessment system of big data, i.e. gathers
Convergence-level, station level, province's stratum reticulare and general headquarters' layer；Described collection convergence-level is divided into again convergence subsystem and acquisition subsystem；Described
Station level includes status monitoring services device, work station, mobile terminal access device and mobile terminal；Described status monitoring services device
The data of storage gateway transmission, and be connected with work station and mobile terminal access device by Ethernet；Described province stratum reticulare is base
Build in cloud platform, including big data management platform and status assessing system based on data mining algorithm.Described general headquarters layer
Including decision-making management work station, big ping server and Decision Support Servers；General headquarters' layer obtains and collects assessment data, decision-making pipe
Reason work station obtains warning data according to assessment data, submits abort situation and advanced warning grade to, exports result at big ping server,
Realize assessment result visualization；SMT Station Management person provides final decision, and assessment result is carried out further decision support.
Described collection convergence-level includes all kinds of status monitoring IED group and converges subsystem.Each status monitoring IED gathers phase
Pass information, sends information to converge subsystem, converges after information is collected by subsystem and is transferred to station level.
Described station level status monitoring services device store described collection convergence-level transmission data, and with work station and movement
Terminal is connected.User passes through work station and mobile terminal accessing server.Server transfers data to province's stratum reticulare.
Described province stratum reticulare receives the data of described station level transmission, at big data management platform by converting, clear up, collecting
The technical finesses such as one-tenth, classification, non-structural data characteristics extraction, the higher data of the rate that is obtained by.Again data are carried out further
Analyze and utilization state assessment algorithm assessment data, analysis result, tracing trouble, complete risk assessment.Save stratum reticulare and pass through ether
Net transfers data to general headquarters' layer.
A kind of power equipment state monitoring towards big data shown in Fig. 2 is soft with general headquarters' layer of assessment system and province's stratum reticulare
Part structure chart.
Described province stratum reticulare is built based on cloud platform, including big data management platform and shape based on data mining algorithm
State assessment system.In view of the safety of cloud platform, utilize fire wall cloud platform to be isolated with external network, and be mounted with invasion
Detecting system, prevents malicious attack.
Described province stratum reticulare receives the data of described station level transmission, at big data management platform by converting, clear up, collecting
The technical finesses such as one-tenth, classification, non-structural data characteristics extraction, the higher data of the rate that is obtained by.ETL is utilized (to extract conversion to add
Carry) data extract by instrument, change after be loaded into data warehouse.The data of data warehouse are carried out preliminary search and fault
Analyzing, if it find that fault, alert to described station level, station level receives alarm, and fault is carried out on-call maintenance.
In described status assessing system based on data mining algorithm, data are further analyzed and carry out state
Assessment.Utilize time series analysis, cluster analysis, classification analysis, the analysis of non-structural data characteristics, association analysis, regression analysis
Etc. method, carry out data analysis, and utilize log generator to generate journal file.Utilization state assessment algorithm assessment data analysis
As a result, tracing trouble, and complete risk assessment.Save stratum reticulare and transfer data to general headquarters' layer by Ethernet.
Described general headquarters layer is that assessment result is carried out further decision support.General headquarters' layer obtains and collects assessment data, root
Obtain warning data according to assessment data, submit abort situation and advanced warning grade, and cartography export result to, it is achieved assessment result is visual
Change.SMT Station Management person provides final decision.
Fig. 3 is a kind of power equipment state monitoring towards big data of providing of the present invention and the collection of assessment system is converged
Layer and station level structure chart.In Fig. 3, described collection convergence-level is divided into again convergence subsystem and acquisition subsystem.
Described acquisition subsystem is as the whole system bottom, including multiple primary equipment status monitoring IED group, such as:
GIS (gas-insulated switchgear) status monitoring IED group, primary cut-out state monitoring IED group, spark gap status monitoring
IED group etc..Each primary equipment needs multiple status monitoring IED to constitute status monitoring IED group.Status monitoring IED is straight
Connect on primary equipments such as being attached to GIS, primary cut-out, spark gap.In status monitoring IED, various kinds of sensors gathers once respectively
Device-dependent message, data processing module collects and carries out simple computation, and ZigBee module sends broadcast and sends information to converge
Poly-IED, is set to 1 jumping broadcast radius here and can meet system needs.
Described convergence subsystem includes converging IED group, coordinating concentrator.All kinds of primary equipments converge IED composition and converge IED
Group.Described coordination concentrator includes coordinator and gateway.Converge IED group and expand ZigBee transmission range.Converge IED and receive institute
State the broadcast that acquisition subsystem status monitoring IED sends, first carry out identification, only process corresponding state monitoring IED
The message sent.Such as GIS converges IED and only processes the message that GIS status monitoring IED group sends.ZigBee module will converge
Information after IED processes is sent to coordinator by clean culture.Coordinator is responsible for the establishment of whole network, maintenance, and collects each
Converge the information that IED sends, utilize optical fiber to transfer data to gateway by RS 485 serial ports.Gateway carries out protocol conversion, and
Server is transferred data to by Ethernet.
In order to ensure the proper communication of whole ZigBee-network, status monitoring IED is set to terminal node, converges IED
Being set to router node, coordinator is set to coordinator node.Terminal node is mainly responsible for the collection of data, can only send number
According to, it is impossible to forward the message of other nodes.Router node is responsible for the Route Selection of packet.Coordinator is responsible for whole network
Set up, safeguard, and can be connected with gateway by serial ports.
Described station level includes status monitoring services device, work station, mobile terminal access device and mobile terminal.Described shape
The data of state monitoring server storage gateway transmission, and be connected with work station and mobile terminal access device by Ethernet.Institute
State work station and mainly include monitor workstation, engineer work station and data operation element station.Described monitor workstation provides one
The services such as secondary device Condition Monitoring Data graphically browses, alerts, monitors, control.Described engineer work station carries for engineer
For safeguarding and improve the service of condition monitoring system.Described data manipulation work station provides browsing data, derives, inquires about, prints
Deng service.Mobile terminal accesses status monitoring services device by mobile terminal safety access device, and mobile terminal mainly realizes event
Barrier circular, personnel's informing function.Whole station level system uses C/S structure.
Fig. 4 is a kind of multilayer large-span of providing of the present invention towards the power equipment state monitoring of big data and assessment system
Primary equipment cellular construction figure.Described multilayer large-span needs towards the power equipment state monitoring of big data with assessment system
The primary equipment of monitoring has: GIS, primary cut-out, transformator, capacitance type equipment, electromotor and spark gap totally six kinds.
Described primary equipment unit includes primary equipment body and primary equipment Intelligent component cabinet, and primary equipment body comprises
Several status monitorings IED being attached directly on primary equipment, primary equipment Intelligent component cabinet comprises primary equipment and converges
IED。
The structure of the primary equipment body such as primary cut-out, transformator and Intelligent component cabinet as shown in Figure 4, in GIS body
IED, lightning arrester characteristic is judged including high pressure position characteristic IED being attached directly on GIS, circuit breaker characteristic IED, switch motion
IED, earth point IED, in status monitoring IED, various kinds of sensors gathers relevant information respectively, and status monitoring IED collects and carries out phase
Close the convergence IED sending information to GIS Intelligent component cabinet after calculating.Converge IED and receive described acquisition subsystem corresponding state
The information of monitoring IED, carries out collecting and correlation computations, and sends information to coordinator concentrator.
Primary equipment GIS status monitoring IED specifically includes: high pressure position characteristic IED, circuit breaker characteristic IED, switch motion
Judge IED, lightning arrester characteristic IED, earth point IED.High pressure position characteristic IED needs the project of monitoring to have: insulation characterisitic；Conduction
Characteristic；SF6Gas characteristic.Corresponding monitoring parameter is respectively: acceleration；Temperature；Pressure.Lightning arrester characteristic IED needs monitoring
Project be circuit breaker characteristic, corresponding monitoring parameter is movement time.Switch motion judge IED need monitoring project be every
Leave pass, earthed switch action judges, corresponding monitoring parameter is action.Lightning arrester characteristic IED needs the project of monitoring to be to keep away
Thunder device characteristic, corresponding monitoring parameter is electric current.Earth point IED needs the project of monitoring to be earth point fault, corresponding monitoring
Parameter is earth fault.The primary equipment status monitoring IED functional structure such as primary cut-out, transformator is as shown in table 1.Table 1 one
Secondary device status monitoring IED functional structure.
Described multilayer large-span sets towards the power equipment state monitoring of big data with assessment system acquisition subsystem monitoring
For having six kinds: GIS, primary cut-out, transformator, capacitance type equipment, electromotor and spark gap.Each equipment has some
The corresponding one or more monitoring projects of individual status monitoring IED, status monitoring IED, monitoring project again corresponding one or
Multiple monitoring parameters.Monitoring parameter can be monitored by direct related sensor, and the index of monitoring project is by Sensor monitoring
Parameter is obtained a result after corresponding IED carries out correlation computations as shown in table 2；
Table 2, towards power equipment state monitoring and the status monitoring IED menu of assessment system of big data
Claims (8)
1. a multilayer large-span is towards the power equipment state monitoring of big data and assessment system, it is characterised in that described in set
Standby status monitoring is divided into four layers with assessment system: gather convergence-level, station level, province's stratum reticulare and general headquarters' layer；Described collection convergence-level
It is divided into again convergence subsystem and acquisition subsystem；Described station level includes that status monitoring services device, work station, mobile terminal access
Device and mobile terminal；The data of described status monitoring services device storage gateway transmission, and by Ethernet and work station and shifting
Dynamic terminal access device is connected；
Described province stratum reticulare is built based on cloud platform, comments including big data management platform and state based on data mining algorithm
Estimate system, it is contemplated that the safety of cloud platform, utilize fire wall cloud platform to be isolated with external network, and be mounted with intrusion detection
System, prevents malicious attack；
Described general headquarters layer includes decision-making management work station, big ping server and Decision Support Servers；General headquarters' layer obtains and collects
Assessment data, decision-making management work station obtains warning data according to assessment data, submits abort situation and advanced warning grade to, at large-size screen monitors
Server output result, it is achieved assessment result visualizes；SMT Station Management person provides final decision, and assessment result is entered one
Step decision support.
The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special
Levying and be, described acquisition subsystem is as the whole system bottom, including multiple primary equipment status monitoring IED group, state
Monitoring IED is attached directly on primary equipment；In status monitoring IED, various kinds of sensors gathers primary equipment relevant information respectively,
Data processing module collects and carries out simple computation, and ZigBee module uses the form sending broadcast to send information to converge
IED, is set to 1 jumping broadcast radius here and just disclosure satisfy that system needs；Wherein, IED is the abbreviation of intelligent electronic device；
ZigBee be a kind of closely, low complex degree, low-power consumption, low rate, the bidirectional wireless communication technology of low cost, be mainly used in away from
Carry out data transmission between short, low in energy consumption and that transfer rate is the highest various electronic equipments.
The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special
Levying and be, described convergence subsystem includes converging IED group and coordinating concentrator；All kinds of primary equipments converge IED composition and converge IED
Group；Described coordination concentrator includes coordinator and gateway；Converge IED group and expand ZigBee transmission range, converge IED reception and adopt
The broadcast that the status monitoring IED of subsystem sends, first carries out identification, only processes corresponding state monitoring IED and sends out
The message sent；ZigBee module is sent to coordinator by converging the information after IED processes by clean culture；Coordinator is responsible for whole net
The establishment of network, maintenance, and collect the information that each convergence IED sends, utilize optical fiber to be transferred data to by RS-485 serial ports
Gateway, gateway carries out protocol conversion, and transfers data to server by Ethernet.
The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special
Levying and be, described work station mainly includes monitor workstation, engineer work station and data operation element station；Described monitoring work
The services such as offer primary equipment Condition Monitoring Data of standing graphically browses, alerts, monitors, control；Described engineer work station is
Engineer provides and safeguards and improve the service of condition monitoring system, and described data manipulation work station provides browsing data, derives, looks into
Inquiry, printing etc. service, and mobile terminal accesses status monitoring services device by mobile terminal safety access device, and mobile terminal is main
Realizing malfunction notification, personnel's informing function, status monitoring services device is also responsible for transferring data to province's stratum reticulare, whole station level system
System uses C/S structure.
The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special
Levying and be, described province stratum reticulare receives the data of described station level transmission, big data management platform by conversion, cleaning, integrated,
The technical finesse that classification, non-structural data characteristics are extracted, the higher data of the rate that is obtained by, utilize ETL instrument that data are carried out
It is loaded into data warehouse after extraction, conversion；The data of data warehouse are carried out preliminary search and accident analysis, if it find that therefore
Barrier, alerts to described station level, and station level receives alarm, and fault is carried out on-call maintenance.
The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special
Levying and be, data, in described status assessing system based on data mining algorithm, are further analyzed by described general headquarters layer
And carry out state estimation；Utilize time series analysis, cluster analysis, classification analysis, the analysis of non-structural data characteristics, association analysis
And/or the method for regression analysis carries out data analysis, and log generator is utilized to generate journal file；Utilization state assessment algorithm
Assessment data results, tracing trouble, and complete risk assessment, save stratum reticulare and transfer data to general headquarters' layer by Ethernet.
The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special
Levy and be, described in carry out identification, only processing the message that corresponding state monitoring IED sends is that GIS converges IED and only processes GIS
The message that status monitoring IED group sends.
The most according to claim 2, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special
Levy and be, during the information after IED processes that converges is sent to coordinator by clean culture by described ZigBee module, it should really
Protect the proper communication of whole ZigBee-network, i.e. status monitoring IED is set to terminal node, converge IED and be set to router
Node, coordinator is set to coordinator node；Wherein, terminal node is mainly responsible for the collection of data, can only send data, it is impossible to
Forward the message of other nodes；Router node is responsible for the Route Selection of packet, and coordinator is responsible for the establishment of whole network, dimension
Protect, and can be connected with gateway by serial ports.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610862853.5A CN106325252A (en) | 2016-09-28 | 2016-09-28 | Multi-level large-span large data oriented power equipment state monitoring and evaluating system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610862853.5A CN106325252A (en) | 2016-09-28 | 2016-09-28 | Multi-level large-span large data oriented power equipment state monitoring and evaluating system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106325252A true CN106325252A (en) | 2017-01-11 |
Family
ID=57821032
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610862853.5A Pending CN106325252A (en) | 2016-09-28 | 2016-09-28 | Multi-level large-span large data oriented power equipment state monitoring and evaluating system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106325252A (en) |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107085170A (en) * | 2017-06-23 | 2017-08-22 | 盛秀群 | Extra high voltage direct current transmission line based on big data is maked an inspection tour and reponse system |
| CN107222578A (en) * | 2017-07-20 | 2017-09-29 | 河北为信电子科技股份有限公司 | By the method and system of Distribution Management System data transfer to intelligent terminal APP |
| CN107730040A (en) * | 2017-09-30 | 2018-02-23 | 国网山东省电力公司电力科学研究院 | Power information system log information comprehensive characteristics extracting method and device based on RBM |
| CN107993424A (en) * | 2017-12-29 | 2018-05-04 | 川铁电气（天津）股份有限公司 | One kind switch folding condition monitoring device and monitoring method |
| CN108425405A (en) * | 2018-04-02 | 2018-08-21 | 淮阴工学院 | A kind of monitoring of networking water source and water supply by stage device and its monitoring system |
| CN109376168A (en) * | 2018-10-23 | 2019-02-22 | 广东电网有限责任公司 | A kind of big data analysis system of master network equipment |
| CN109491339A (en) * | 2018-11-16 | 2019-03-19 | 国网江苏省电力有限公司盐城供电分公司 | A kind of operating condition of transformer station equipment early warning system based on big data |
| CN109974780A (en) * | 2019-04-01 | 2019-07-05 | 西京学院 | A kind of electrical equipment status monitoring system based on Internet of Things |
| CN110289683A (en) * | 2019-06-12 | 2019-09-27 | 上海大学 | Micro-capacitance sensor network transmission performance monitoring system and implementation method based on NB-IOT |
| CN110673561A (en) * | 2019-10-18 | 2020-01-10 | 孚亨工业科技(昆山)有限公司 | Service quality control system of heat source system |
| CN111934321A (en) * | 2020-08-31 | 2020-11-13 | 国网甘肃省电力公司电力科学研究院 | Evaluation system of transmission network transmission capacity based on big data platform |
| CN112241546A (en) * | 2020-10-30 | 2021-01-19 | 国网山东省电力公司电力科学研究院 | Information interaction system and method for power plant network security |
| CN112763963A (en) * | 2020-11-26 | 2021-05-07 | 中国电力科学研究院有限公司 | System and method for carrying out online monitoring on mutual inductor based on deep network |
| CN113641726A (en) * | 2021-08-06 | 2021-11-12 | 国网北京市电力公司 | Unsupervised sheath current data mining system based on generation countermeasure network |
| CN114325215A (en) * | 2021-11-22 | 2022-04-12 | 国网湖南省电力有限公司 | Intensive detection system for power equipment state and application method thereof |
| CN115835155A (en) * | 2022-11-24 | 2023-03-21 | 广西电网有限责任公司电力科学研究院 | Self-energy-taking sensor self-organizing network networking method |
| CN116780782A (en) * | 2023-08-24 | 2023-09-19 | 成都易电云商工程服务有限公司 | Comprehensive maintenance system for electrical equipment of power distribution network |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1916949A (en) * | 2006-09-06 | 2007-02-21 | 曾德华 | Support system for evaluating status of electric power equipments, and maintaining strategy |
| CN102710024A (en) * | 2012-06-13 | 2012-10-03 | 广西电网公司电力科学研究院 | IPv6-based electric transmission and transformation equipment on-line monitoring system |
| EP2677718A1 (en) * | 2012-06-22 | 2013-12-25 | Idecsi | Secondary asynchronous background authorization (SABA) |
| CN104281130A (en) * | 2014-09-22 | 2015-01-14 | 国家电网公司 | Hydroelectric equipment monitoring and fault diagnosis system based on big data technology |
| CN104578412A (en) * | 2014-12-19 | 2015-04-29 | 上海电机学院 | Big data technology-based state detection system and method |
| CN104715596A (en) * | 2014-12-30 | 2015-06-17 | 国家电网公司 | Method for transmitting data in transformer station |
| US20150180748A1 (en) * | 2013-12-20 | 2015-06-25 | Futurewei Technologies Inc. | METHOD AND APPARATUS OF WebRTC MEDIA CONTROL |
| WO2015167057A1 (en) * | 2014-04-28 | 2015-11-05 | 가온미디어 주식회사 | Home thin-client in-home information collection processing system using dual-cloud based assist gateway, and operation method of same |
| CN105187010A (en) * | 2015-09-07 | 2015-12-23 | 无锡联盛合众新能源有限公司 | Intelligent monitoring and operation maintenance system for photovoltaic power station |
-
2016
- 2016-09-28 CN CN201610862853.5A patent/CN106325252A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1916949A (en) * | 2006-09-06 | 2007-02-21 | 曾德华 | Support system for evaluating status of electric power equipments, and maintaining strategy |
| CN102710024A (en) * | 2012-06-13 | 2012-10-03 | 广西电网公司电力科学研究院 | IPv6-based electric transmission and transformation equipment on-line monitoring system |
| EP2677718A1 (en) * | 2012-06-22 | 2013-12-25 | Idecsi | Secondary asynchronous background authorization (SABA) |
| US20150180748A1 (en) * | 2013-12-20 | 2015-06-25 | Futurewei Technologies Inc. | METHOD AND APPARATUS OF WebRTC MEDIA CONTROL |
| WO2015167057A1 (en) * | 2014-04-28 | 2015-11-05 | 가온미디어 주식회사 | Home thin-client in-home information collection processing system using dual-cloud based assist gateway, and operation method of same |
| CN104281130A (en) * | 2014-09-22 | 2015-01-14 | 国家电网公司 | Hydroelectric equipment monitoring and fault diagnosis system based on big data technology |
| CN104578412A (en) * | 2014-12-19 | 2015-04-29 | 上海电机学院 | Big data technology-based state detection system and method |
| CN104715596A (en) * | 2014-12-30 | 2015-06-17 | 国家电网公司 | Method for transmitting data in transformer station |
| CN105187010A (en) * | 2015-09-07 | 2015-12-23 | 无锡联盛合众新能源有限公司 | Intelligent monitoring and operation maintenance system for photovoltaic power station |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107085170A (en) * | 2017-06-23 | 2017-08-22 | 盛秀群 | Extra high voltage direct current transmission line based on big data is maked an inspection tour and reponse system |
| CN107222578A (en) * | 2017-07-20 | 2017-09-29 | 河北为信电子科技股份有限公司 | By the method and system of Distribution Management System data transfer to intelligent terminal APP |
| CN107730040A (en) * | 2017-09-30 | 2018-02-23 | 国网山东省电力公司电力科学研究院 | Power information system log information comprehensive characteristics extracting method and device based on RBM |
| CN107993424A (en) * | 2017-12-29 | 2018-05-04 | 川铁电气（天津）股份有限公司 | One kind switch folding condition monitoring device and monitoring method |
| CN108425405A (en) * | 2018-04-02 | 2018-08-21 | 淮阴工学院 | A kind of monitoring of networking water source and water supply by stage device and its monitoring system |
| CN108425405B (en) * | 2018-04-02 | 2024-02-13 | 淮阴工学院 | Networked water source monitoring and graded water supply device and monitoring system thereof |
| CN109376168A (en) * | 2018-10-23 | 2019-02-22 | 广东电网有限责任公司 | A kind of big data analysis system of master network equipment |
| CN109491339B (en) * | 2018-11-16 | 2022-06-24 | 国网江苏省电力有限公司盐城供电分公司 | Big data-based substation equipment running state early warning system |
| CN109491339A (en) * | 2018-11-16 | 2019-03-19 | 国网江苏省电力有限公司盐城供电分公司 | A kind of operating condition of transformer station equipment early warning system based on big data |
| CN109974780A (en) * | 2019-04-01 | 2019-07-05 | 西京学院 | A kind of electrical equipment status monitoring system based on Internet of Things |
| CN110289683A (en) * | 2019-06-12 | 2019-09-27 | 上海大学 | Micro-capacitance sensor network transmission performance monitoring system and implementation method based on NB-IOT |
| CN110673561A (en) * | 2019-10-18 | 2020-01-10 | 孚亨工业科技(昆山)有限公司 | Service quality control system of heat source system |
| CN111934321A (en) * | 2020-08-31 | 2020-11-13 | 国网甘肃省电力公司电力科学研究院 | Evaluation system of transmission network transmission capacity based on big data platform |
| CN112241546A (en) * | 2020-10-30 | 2021-01-19 | 国网山东省电力公司电力科学研究院 | Information interaction system and method for power plant network security |
| CN112763963A (en) * | 2020-11-26 | 2021-05-07 | 中国电力科学研究院有限公司 | System and method for carrying out online monitoring on mutual inductor based on deep network |
| CN112763963B (en) * | 2020-11-26 | 2024-05-14 | 中国电力科学研究院有限公司 | System and method for on-line monitoring of transformer based on depth network |
| CN113641726B (en) * | 2021-08-06 | 2024-01-30 | 国网北京市电力公司 | Unsupervised sheath current data mining system based on generation of countermeasure network |
| CN113641726A (en) * | 2021-08-06 | 2021-11-12 | 国网北京市电力公司 | Unsupervised sheath current data mining system based on generation countermeasure network |
| CN114325215A (en) * | 2021-11-22 | 2022-04-12 | 国网湖南省电力有限公司 | Intensive detection system for power equipment state and application method thereof |
| CN115835155A (en) * | 2022-11-24 | 2023-03-21 | 广西电网有限责任公司电力科学研究院 | Self-energy-taking sensor self-organizing network networking method |
| CN116780782B (en) * | 2023-08-24 | 2023-10-31 | 成都易电云商工程服务有限公司 | Comprehensive maintenance system for electrical equipment of power distribution network |
| CN116780782A (en) * | 2023-08-24 | 2023-09-19 | 成都易电云商工程服务有限公司 | Comprehensive maintenance system for electrical equipment of power distribution network |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106325252A (en) | Multi-level large-span large data oriented power equipment state monitoring and evaluating system | |
| CN105515184B (en) | Multisensor many reference amounts distribution synergic monitoring system based on wireless sensor network | |
| CN110401262A (en) | GIS device state intelligent monitoring system and method based on edge calculations technology | |
| CN107895176A (en) | A kind of mist computing system and method towards water power group of planes wide area monitoring, diagnosing | |
| CN210166487U (en) | Power supply station area power failure fault warning device based on edge calculation | |
| CN110910626A (en) | Energy consumption information acquisition system based on ubiquitous power Internet of things | |
| CN104966330A (en) | Remote machine room intelligent inspection system based on cloud computer | |
| CN105372534A (en) | Multi-sensor multi-parameter information intelligent integration system | |
| CN104502753A (en) | Networked on-line real-time analysis system for electric power fault recording device and application of system | |
| CN106845562B (en) | The fault monitoring system and data processing method of photovoltaic module | |
| Song et al. | Research on applications of the internet of things in the smart grid | |
| CN208209630U (en) | A kind of the micromation intelligent on-line monitoring device and monitoring system of low-voltage distribution apparatus | |
| CN104392591B (en) | Transmission pole malfunction monitoring expert system | |
| CN113220751A (en) | Metering system and evaluation method for multi-source data state quantity | |
| CN105632108A (en) | GPRS and ZigBee network-based debris flow monitoring and early warning system | |
| Cao et al. | Analysis and prospect of the application of wireless sensor networks in ubiquitous power internet of things | |
| Ju et al. | The use of edge computing-based internet of things big data in the design of power intelligent management and control platform | |
| CN203932958U (en) | Power grid integrated intelligence is adjusted and online nucleus correcting system | |
| CN102338835A (en) | Power quality dynamic monitoring system | |
| CN203968150U (en) | The long-range intensive management system of distributed energy | |
| CN206906519U (en) | A kind of extra high voltage direct current transmission line based on big data is maked an inspection tour and reponse system | |
| CN107017835B (en) | The fault monitoring system and method for photovoltaic module | |
| CN206132904U (en) | Novel wisdom fault indication system of 10kv circuit | |
| Yang et al. | Technology research on panoramic situation awareness of operation state of smart distribution network | |
| CN111917187B (en) | Intelligent substation cloud monitored control system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170111 |
|
| RJ01 | Rejection of invention patent application after publication |