CN107273524A - A kind of intelligent power distribution big data application system - Google Patents
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- CN107273524A CN107273524A CN201710484843.7A CN201710484843A CN107273524A CN 107273524 A CN107273524 A CN 107273524A CN 201710484843 A CN201710484843 A CN 201710484843A CN 107273524 A CN107273524 A CN 107273524A
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Abstract
The present invention relates to a kind of intelligent power distribution big data application system, the system includes：Data acquisition module provides standardized data interface, carries out the standardization access of multi-source, heterogeneous data source；The data that data integration cleaning module is accessed to data acquisition module are merged, associated, duplicate removal and ranks transposition；Public service module utilizes the data after the processing of data integration cleaning module；Data analysis application module construction parser storehouse, carries out user power utilization behavioural characteristic analysis, builds application model and algorithms library, according to analysis result, builds energy-saving application, power consumption prediction application, Optimal network frame application and flood peak staggered regulation application；Data display is carried out to the result of data analysis application module using display module.Compared with prior art, the present invention has the cleaning for completing data, distributed platform migration and standardized set into exploitation completes user behavior analysis, power consumption prediction application module, and lifts the advantages of intelligence matches somebody with somebody electricity consumption level.
Description
Technical field
The present invention relates to a kind of intelligent distribution system, more particularly, to a kind of intelligent power distribution big data application system.
Background technology
Big data (Big Data) technology has obtained national governments and Global Academy, the highest attention of industrial quarters in recent years
And attention, the application fast development in every profession and trade field.In March, 2012, U.S. government has issued " big data research and development innovation
Plan ", and invest 200,000,000 dollars of startup big data technical researches.The Chinese government, academia and industrial quarters also give big data
The concern of height.At present, in the information-based industry more compared with early, data accumulation, such as internet, telecommunications, finance field, big number
The significant impact to industry development has tentatively been shown according to technology.In recent years the data resource of power industry starts sharp increase simultaneously
Reach a certain scale, strong demand is also produced to big data technology.It is embodied in：Data volume is sent out from TB grades to PB grades
Exhibition, faces the storage of data high-performance and enhanced scalability challenge；Corporate business develops to intelligent, lean direction, to complexity
Data processing and real-time propose requirements at the higher level；Trans-sectoral business, cross-platform data processing and analysis ability need further lifting.
However, the above mentioned problem for solving power system, particularly distribution system currently with big data technology rarely has research.
The content of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide a kind of big number of intelligent power distribution
According to application system.
The purpose of the present invention can be achieved through the following technical solutions：
A kind of intelligent power distribution big data application system, the system includes：
Data acquisition module：Standardized data interface is provided, the standardization access of multi-source, heterogeneous data source is carried out；
Data integration cleaning module：The data that data acquisition module is accessed are merged, associated, duplicate removal and ranks turn
Put；
Public service module：Data after being handled using data integration cleaning module, in data analysis, data management sum
According to application aspect basic platform instrument is provided for data analysis application module and using display module；
Data analysis application module：Creation analysis algorithms library, carries out user power utilization behavioural characteristic analysis, builds application model
And algorithms library, according to analysis result, carry out Design of power saving, power consumption prediction, Optimal network frame and flood peak staggered regulation；
Using display module：Result to data analysis application module carries out data display.
Described data acquisition module access transmission of electricity, distribution, real-time/near-realtime data of electricity consumption, electric power basic data and
Structural data including social economy.
Described public service module includes conventional data mining algorithm storehouse, Statistic analysis models storehouse, data management service
Component and visualization component.
Described data analysis application module includes components of data analysis and data application component.
Described data analysis application module includes energy-saving application component, power consumption prediction application component, Optimal network frame application
Component and flood peak staggered regulation application component.
Compared with prior art, the present invention has advantages below：
(1) rely on standard device model, complete data cleaning, distributed platform migration and standardized set into：In number
According to integrated and cleaning layer, by the Data Migration of data buffer area to big data platform, using big data platform hybrid distributed formula
Storage and parallel processing architecture, to meet the service application such as performance indications and data cleansing, analysis, excavation support demand, simultaneously
Optimize the data after storage processing, it is more beneficial for foreground displaying and interactive experience；
(2) exploitation completes big data application system support platform there is provided a collection of basic platform instrument, realizes module
The data algorithm support of change, visual data management service, the visualization component of standardization：In terms of data analysis there is provided
The general-purpose algorithm storehouses such as Mahout, R_statistics, parallel algorithm storehouse, the cluster towards big data of support upper layer data application
The data analysing method of analysis, association analysis etc.；In terms of data management, by data management service, facilitate the business of data
Circulation, visual monitor management；In terms of data application, by professional and general visualization component, facilitate application scenarios
Realize；
(3) exploitation completes user behavior analysis, power consumption prediction application module, realizes branch of the big data to power business
Support：
(4) in data display aspect, with reference to a variety of visual presentation components provided in task one, to demonstration project scope
The application result such as interior user power utilization behavioural characteristic, power consumption prediction carries out data display, realizes branch of the big data to power business
Support, lifting intelligence matches somebody with somebody electricity consumption level.
Brief description of the drawings
Fig. 1 is intelligent adapted TV university Data application system total figure Organization Chart.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is a part of embodiment of the present invention, rather than whole embodiments.Based on this hair
Embodiment in bright, the every other reality that those of ordinary skill in the art are obtained on the premise of creative work is not made
Example is applied, should all belong to the scope of protection of the invention.
Embodiment
As shown in figure 1, intelligent adapted TV university Data application system is divided into data acquisition, data integration and cleaning, public clothes
Business, data analysis and application, using five layers of displaying, the technical scheme that system is used for：First, in data collection layer, realize
Standardization access to multi-source, heterogeneous data source.This demonstration project lands Shanghai Pudong New Area, it is contemplated that 2,260,000 electric power of access are used
Family, integrated 9 business datum sources, 7 wherein in power system, 2 outside power system.According to the achievement in research of task one, knot
The reality of demonstration project, analysis and classification data source characteristic are closed, there is provided class database using the design of standardized data interface specification
The standard interfaces such as type interface, file system type interface, type of message interface, realize and include transmission of electricity, distribution, the reality of electricity consumption
When/near-realtime data, electric power basic data and social economy including structural data access, realize include GIS figures, gas
Left concentratedly as the access of the unstructured datas such as figure, text document, and by access data to data buffer area.
Secondly, in data integration and cleaning layer, by the Data Migration of data buffer area to big data platform, using big data
Platform hybrid distributed formula is stored and parallel processing architecture, should to meet the business such as performance indications and data cleansing, analysis, excavation
With support demand, while optimizing the data after storage processing, it is set to be more beneficial for foreground displaying and interactive experience.
Data integration and cleaning sequence include：Data buffer zone is to original storehouse, original storehouse to middle database, middle database to result
The part of storehouse three.Wherein Part I (data buffer zone to original storehouse) is that the initial data of each operation system is moved into big data
The Inceptor data warehouses of platform, initial data is provided for subsequent distribution formula data processing；Part II (original storehouse to centre
Storehouse) be initial data is merged by big data platform, associated, the operation such as duplicate removal, ranks transposition, and by the number after processing
Inceptor data warehouses are arrived by new table structure storage according to the data after cleaning, the formation quality of data is reliable, association is clear
Intermediate data, provides good data for follow-up each application specialty analysis basic；Part III be the data that will clearly complete from
Inceptor data warehouses move to the Hyperbase databases for foreground visual query of being more convenient for, and improve search efficiency and use
Experience at family.
It is main to use according to the different pieces of information such as data-intensive or computation-intensive computing requirement in terms of data processing
Distributed batch processing calculates three kinds of modes such as MapReduce etc., distributed memory calculating Spark etc., high-performance calculation MPI and realized
Intensive, the high-speed computation process of big data；Wherein high-performance calculation is mainly used in meeting based on iteration optimization, computation-intensive
Optimal network frame, flood peak staggered regulation service application scene demand.
3rd, in public service layer, modularization builds a collection of public service component, is follow-up business analysis and application displaying
Basic platform instrument is provided, mainly comprising conventional data mining algorithm storehouse, Statistic analysis models storehouse, data management service, visual
Change the parts such as component.There is provided the general-purpose algorithms such as Mahout, R_statistics, parallel algorithm storehouse in terms of data analysis
Storehouse, the data analysing method towards clustering, the association analysis of big data etc. of support upper layer data application；In data management
Aspect, by data management service, facilitates work flow, the visual monitor management of data；In terms of data application, by special
Industry and general visualization component, facilitate the realization of application scenarios.
Again, in data application aspect, the demonstration landing of task two, the correlative study achievement of task three is realized, it is included
Business datum analysis, business datum application, service application interact three aspects.In terms of business datum analysis, special calculate is built
Faku County, by the amendment to source data, using means such as association analysis, clusterings, realizes and is based on geography information, Ke Huxin
The user power utilization behavioural characteristic analysis of breath, power information etc., and the realization of supporting business algorithm and business model.In business datum
Application aspect, for different scenes business demand, data sharing, business are independent, build application model and algorithms library.First, right
In energy-saving application, based on electricity consumption behavior, environment sensing etc., assess electricity consumption energy conservation potential and power-saving strategies are provided there is provided based on use
The distribution idle work optimization regulation strategy of family electrical characteristics.Second, for power consumption prediction application, based on electricity consumption behavior, weather information,
Special event etc., realizes the power consumption prediction of different user；Based on geography information, electricity consumption behavior, social economy etc., realize that fusion is empty
Between geodata electricity consumption variation tendency and colony's power consumption prediction.Third, for Optimal network frame application, based on power consumption prediction, using
There is provided consider multifactor Distribution Network Frame prioritization scheme for electrical characteristics, power reguirements, geography information, distributed power source access etc..Its
Four, for flood peak staggered regulation application, based on power scheduling, with electrical characteristics, weather information etc., project evaluation chain, which is avoided the peak hour, resource and avoids the peak hour latent
Power, and flood peak staggered regulation strategy is provided.In terms of service application interaction, using technologies such as high speed interactive engine, memory cache data,
Realization is interacted with the high speed of data display.
Finally, in data display aspect, with reference to a variety of visual presentation components provided in task one, to demonstration project model
The application result such as user power utilization behavioural characteristic, economize on electricity, power consumption prediction, Optimal network frame, flood peak staggered regulation in enclosing carries out data display,
Support of the big data to power business is realized, lifting intelligence matches somebody with somebody electricity consumption level.
Because adapted power network big data faces the characteristics of data type is more, data volume is big, data processing performance requirement is high, because
This will design and develop the architectural framework for meeting the management of adapted power network big data and application, it is necessary to be adopted using newest big data
Collection, storage and treatment technology.The performance and exploitation that high speed is realized under the conditions of big data meet application layer data analysis demand
Architecture is one of key technology of this problem.Multi-node parallel data storage technology is used in terms of data acquisition, is realized
The technical indicator of time data memory；The expansible NoSql databases towards adapted TV university data are studied in terms of data storage
With high-speed internal memory database.Batch processing, the figure of the intensive adapted TV university data application of data-oriented are studied in terms of data processing
Calculate and internal memory computing architecture, and towards the high-performance calculation framework of computation-intensive adapted TV university data application, exploitation is full
The mixed type storage of sufficient adapted TV university data diversity demand and computing architecture.
By building intelligent adapted TV university data demonstration project, concentration realizes the various achievements in research of this problem, adapted
The common technologies such as TV university data system framework, multi-source heterogeneous data integration, storage, processing and visualization, study user power utilization number
According to storage, analysis, the concrete methods of realizing corrected, by the multilayer secondary association with electricity consumption inside and outside data and cluster, analysis is used
Family electricity consumption behavioural characteristic, realizes the adapted TV university data typical cases such as economize on electricity, power consumption prediction, the electric Optimal network frame of adapted, flood peak staggered regulation
Service application.Can be the construction mode and fortune for exploring intelligent adapted TV university Data application system by the construction of this demonstration project
Battalion pattern provides typical case, the road of " achievable, reproducible, can promote " of the intelligent adapted TV university Data application system of developing.
The foregoing is only a specific embodiment of the invention, but protection scope of the present invention is not limited thereto, any
Those familiar with the art the invention discloses technical scope in, various equivalent modifications can be readily occurred in or replaced
Change, these modifications or substitutions should be all included within the scope of the present invention.Therefore, protection scope of the present invention should be with right
It is required that protection domain be defined.
Claims (5)
1. a kind of intelligent power distribution big data application system, it is characterised in that the system includes：
Data acquisition module：Standardized data interface is provided, the standardization access of multi-source, heterogeneous data source is carried out；
Data integration cleaning module：The data that data acquisition module is accessed are merged, associated, duplicate removal and ranks transposition；
Public service module：Data after being handled using data integration cleaning module, should in data analysis, data management and data
With aspect basic platform instrument is provided for data analysis application module and using display module；
Data analysis application module：Creation analysis algorithms library, carries out user power utilization behavioural characteristic analysis, builds application model and calculation
Faku County, according to analysis result, carries out Design of power saving, power consumption prediction, Optimal network frame and flood peak staggered regulation；
Using display module：Result to data analysis application module carries out data display.
2. a kind of intelligent power distribution big data application system according to claim 1, it is characterised in that described data acquisition
Structuring number including module access transmission of electricity, distribution, real-time/near-realtime data of electricity consumption, electric power basic data and social economy
According to.
3. a kind of intelligent power distribution big data application system according to claim 1, it is characterised in that described public service
Module includes conventional data mining algorithm storehouse, Statistic analysis models storehouse, data management service component and visualization component.
4. a kind of intelligent power distribution big data application system according to claim 1, it is characterised in that described data analysis
Application module includes components of data analysis and data application component.
5. a kind of intelligent power distribution big data application system according to claim 1, it is characterised in that described data analysis
Application module includes energy-saving application component, power consumption prediction application component, Optimal network frame application component and flood peak staggered regulation application component.
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| CN107707029A (en) * | 2017-10-23 | 2018-02-16 | 珠海许继芝电网自动化有限公司 | Low and medium voltage distribution network integrated monitoring and management system |
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| CN111949246A (en) * | 2020-08-13 | 2020-11-17 | 国家电网有限公司 | Method and device for creating new energy power industry application |
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202373025U (en) * | 2011-12-16 | 2012-08-08 | 山西省电力公司长治供电分公司 | Intelligent device for dispatching business integration and data integration |
| US20130268196A1 (en) * | 2012-04-05 | 2013-10-10 | Quang Binh Dam | System and method of automated acquisition, correlation and display of power distribution grid operational parameters and weather events |
| CN104008437A (en) * | 2013-02-25 | 2014-08-27 | 陈国祥 | Visualization display system of intelligent power network, and method thereof |
| CN104462314A (en) * | 2014-11-28 | 2015-03-25 | 国家电网公司 | Power grid data processing method and device |
| CN104820670A (en) * | 2015-03-13 | 2015-08-05 | 国家电网公司 | Method for acquiring and storing big data of power information |
| CN106202566A (en) * | 2016-08-02 | 2016-12-07 | 山东鲁能软件技术有限公司 | A kind of magnanimity electricity consumption data mixing based on big data storage system and method |
| CN106599038A (en) * | 2016-11-04 | 2017-04-26 | 国网江苏省电力公司 | Visualization statistic publishing system oriented on power application |
-
2017
- 2017-06-23 CN CN201710484843.7A patent/CN107273524A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202373025U (en) * | 2011-12-16 | 2012-08-08 | 山西省电力公司长治供电分公司 | Intelligent device for dispatching business integration and data integration |
| US20130268196A1 (en) * | 2012-04-05 | 2013-10-10 | Quang Binh Dam | System and method of automated acquisition, correlation and display of power distribution grid operational parameters and weather events |
| CN104008437A (en) * | 2013-02-25 | 2014-08-27 | 陈国祥 | Visualization display system of intelligent power network, and method thereof |
| CN104462314A (en) * | 2014-11-28 | 2015-03-25 | 国家电网公司 | Power grid data processing method and device |
| CN104820670A (en) * | 2015-03-13 | 2015-08-05 | 国家电网公司 | Method for acquiring and storing big data of power information |
| CN106202566A (en) * | 2016-08-02 | 2016-12-07 | 山东鲁能软件技术有限公司 | A kind of magnanimity electricity consumption data mixing based on big data storage system and method |
| CN106599038A (en) * | 2016-11-04 | 2017-04-26 | 国网江苏省电力公司 | Visualization statistic publishing system oriented on power application |
Non-Patent Citations (1)
| Title |
|---|
| 田世明: "智能配用电大数据关键技术研究", 《供用电》 * |
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| CN108305691A (en) * | 2018-03-01 | 2018-07-20 | 龙汾科技（深圳）有限公司 | A kind of intelligent wearable device of infantile health data collection |
| CN108909482A (en) * | 2018-06-27 | 2018-11-30 | 芜湖盘云石磨新能源科技有限公司 | New-energy automobile charging pile and distribution network coordinated control system based on big data |
| CN109067837A (en) * | 2018-07-03 | 2018-12-21 | 沈阳电电科技有限公司 | Controller switching equipment Internet of Things and information collecting platform |
| CN109284314A (en) * | 2018-08-20 | 2019-01-29 | 国网安徽省电力有限公司合肥供电公司 | A kind of high pressure customer access system and method based on power grid visualization |
| CN109130935A (en) * | 2018-08-30 | 2019-01-04 | 广东电网有限责任公司 | A kind of electric car intelligent charge monitoring system |
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| CN109271384A (en) * | 2018-09-06 | 2019-01-25 | 语联网（武汉）信息技术有限公司 | Large database concept and its method for building up, the device and electronic equipment of interpreter's behavior |
| CN109242446A (en) * | 2018-10-16 | 2019-01-18 | 南京工业大学 | A kind of city intelligent energy panorama control platform |
| CN109636012A (en) * | 2018-11-26 | 2019-04-16 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Intelligence sentences the processing system that card predicted events occur |
| CN109670015A (en) * | 2018-12-12 | 2019-04-23 | 中科恒运股份有限公司 | Data analysing method, computer readable storage medium and terminal device |
| CN111427930A (en) * | 2020-03-30 | 2020-07-17 | 广东电科院能源技术有限责任公司 | Low-voltage photovoltaic energy storage microgrid device monitoring management system, method and device |
| WO2021217695A1 (en) * | 2020-04-29 | 2021-11-04 | 深圳市双合电气股份有限公司 | Smart data collection and sorting system for smart factory framework-based power supply and distribution grid |
| CN111897863A (en) * | 2020-07-31 | 2020-11-06 | 珠海市新德汇信息技术有限公司 | Multi-source heterogeneous data fusion and convergence method |
| CN111949246A (en) * | 2020-08-13 | 2020-11-17 | 国家电网有限公司 | Method and device for creating new energy power industry application |
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