CN104361110A - Mass electricity consumption data analysis system as well as real-time calculation method and data mining method - Google Patents
Mass electricity consumption data analysis system as well as real-time calculation method and data mining method Download PDFInfo
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- CN104361110A CN104361110A CN201410710769.2A CN201410710769A CN104361110A CN 104361110 A CN104361110 A CN 104361110A CN 201410710769 A CN201410710769 A CN 201410710769A CN 104361110 A CN104361110 A CN 104361110A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
- G06Q10/06375—Prediction of business process outcome or impact based on a proposed change
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- 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
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The invention discloses a mass electricity consumption data analysis system, which comprises a data source, a data obtaining module, a data storage module, a data calculation module, a basic service module and an electricity consumption analysis platform, wherein the data calculation module is used for carrying out 98 distributed parallel computing on mass electricity consumption data of the data calculation module by adopting SmartMing and/or Rhadoop analysis tools and/or Spark frameworks, the basic service module provides GIS (geographic information system) service and visual service and carries out data analysis according to a calculation result of the data calculation module, and the electricity consumption analysis platform is used for carrying out metering device analysis, real-time line loss calculation, electricity consumption behavior analysis, feeder line analysis, electrical load predication and load real-time predication according to the basic service module. The invention also discloses a mass electricity consumption data real-time calculation method based on the mass electricity consumption data analysis system and a mass electricity consumption data mining method based on the mass electricity consumption data analysis system. The mass electricity consumption data can be subjected to analysis processing, and the processing efficiency is high.
Description
Technical field
The present invention relates to electricity consumption data processing field, particularly relate to a kind of magnanimity electricity consumption data analysis system.
Background technology
Along with the high speed development of electrical network scale, informationization technology means have been widely used in the every aspect of electrical network, achieve remarkable result, for meeting the needs of national economy and social development, improving customer service quality and having made powerful support.Metering automation, the acquisition system of electric power enterprise also constantly perfect universal, thus create the electricity consumption data of magnanimity.
And the application management and control of enterprise to electricity consumption data lags behind the growth of electricity consumption data far away, its management difficulty and complicacy are also multiplied.In the electricity consumption data of magnanimity, just must can draw effective conclusion through long finishing analysis as decision maker, add managerial difficulty undoubtedly.
The electricity consumption real-time property that current electric grid gathers is high and data volume is huge, and bottleneck appears in traditional data storage method performance, and the problems such as response time length, reliability and stability also appear in statistical study on this basis.Therefore mining algorithm is used intelligent power field and is carried out customer analysis by technician, but there is operand when processing large for large-scale magnanimity electricity consumption data, adopts traditional mining algorithm efficiency too low.
Summary of the invention
Technical matters to be solved by this invention is, provides a kind of magnanimity electricity consumption data analysis system, can to the process of magnanimity electricity consumption data analysis, and treatment effeciency is high.
In order to solve the problems of the technologies described above, the invention provides a kind of magnanimity electricity consumption data analysis system, comprising:
Data source, for providing magnanimity electricity consumption data;
Data acquisition module, obtains magnanimity electricity consumption data for adopting web services mode and/or ETL mode from described data source;
Data memory module, stores for the magnanimity electricity consumption data obtained described data acquisition module;
Data computation module, for adopting SmartMing and/or Rhadoop analysis tool and/or Spark framework, carries out Distributed Parallel Computing to the magnanimity electricity consumption data of described data computation module;
Infrastructure service module, for providing GIS service and Visualization Service, and carries out data analysis according to the result of calculation of described data computation module;
Electrical energy consumption analysis platform, for carrying out measuring apparatus analysis, real-time line loss calculation, electricity consumption behavioural analysis, feeder line analysis, load forecast and load real-time estimate according to described infrastructure service module.
Present invention also offers a kind of magnanimity electricity consumption data real-time computing technique based on described magnanimity electricity consumption data analysis system, comprising:
Adopt the ETL mode in described data acquisition module from described data source, obtain magnanimity electricity consumption data;
According to the index reached required for calculating in real time, based on the Spark framework of described data computation module, adopt memory parallel computing technique to carry out data processing to described magnanimity electricity consumption data, and carry out denoising, filtration repetition theme/delete and irrelevant redundancy and the junk information of setting objectives;
Based on the Spark framework of described data computation module, adopt memory parallel computing technique to gather data processed result, and summarized results is stored in data warehouse;
Represent in conjunction with the described GIS service of described infrastructure service module and/or the data of Visualization Service to data warehouse.
Present invention also offers a kind of magnanimity electricity consumption data mining method based on described magnanimity electricity consumption data analysis system, comprising:
Adopt the Web service mode in described data acquisition module and ETL mode from described data source, obtain magnanimity electricity consumption data;
The map technology of hadoop in Rhadoop analysis tool described in described data computation module is adopted to be stored in HDFS by described magnanimity electricity consumption data,
The magnanimity electricity consumption data of the distributed computing technology of hadoop in Rhadoop analysis tool described in described data computation module are adopted to carry out data processing;
Adopt the data mining algorithm of Spark framework or RHadoop analysis tool described in data computation module to carry out analytical calculation to data processed result, and analysis result is stored in MySQL database;
Represent in conjunction with the described GIS service of described infrastructure service module and/or the data of Visualization Service to MySQL database.
The present invention can to the process of magnanimity electricity consumption data analysis, improve the ALARA Principle degree of mass data and the warehouse-in efficiency of mass data, the demand of satisfying magnanimity the inquiry of historical data statistical study, improve the speed that data calculate, treatment effeciency is high, provides abundant analytic statistics to meet business and management expectancy on this basis, and existing system can be allowed to process data acquisition session swimmingly, the simple application of reply represents, and meets more and more efficient statistical study demand.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the structured flowchart of the embodiment of magnanimity electricity consumption data analysis system provided by the invention;
Fig. 2 is the schematic flow sheet of the embodiment of the magnanimity electricity consumption data real-time computing technique based on the electricity consumption of magnanimity shown in Fig. 1 data analysis system provided by the invention;
Fig. 3 is the schematic flow sheet of the embodiment of the magnanimity electricity consumption data mining method based on the electricity consumption of magnanimity shown in Fig. 1 data analysis system provided by the invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
Fig. 1 is the structured flowchart of the embodiment of magnanimity electricity consumption data analysis system provided by the invention, as shown in Figure 1, comprising:
Data source, for providing magnanimity electricity consumption data;
Data acquisition module, obtains magnanimity electricity consumption data for adopting web services mode and/or ETL mode from described data source;
Data memory module, stores for the magnanimity electricity consumption data obtained described data acquisition module;
Data computation module, for adopting SmartMing and/or Rhadoop analysis tool and/or Spark framework, carries out Distributed Parallel Computing to the magnanimity electricity consumption data of described data computation module;
Infrastructure service module, for providing GIS service and Visualization Service, and carries out data analysis according to the result of calculation of described data computation module;
Electrical energy consumption analysis platform, for carrying out measuring apparatus analysis, real-time line loss calculation, electricity consumption behavioural analysis, feeder line analysis, load forecast and load real-time estimate according to described infrastructure service module.
Wherein, described data source be metering automation system, energy management system, marketing system, battalion join in integration data center and external data one or more.
Wherein, described data memory module comprises data warehouse and the real-time database combined with relevant database.Such as, MySQL database and oracle database.
Wherein, electrical energy consumption analysis platform specifically comprises:
Measuring apparatus analytic unit, for judging measuring apparatus state according to the data results of described infrastructure service module, thus the cycle of minimizing tour error;
Real-time line loss calculation unit, carries out line loss calculation in real time for the smallest particles degrees of data based on each stoichiometric point, and adopts described GIS service line loss to be fed back in GIS map;
Electricity consumption behavioural analysis unit, for according to the data results of described infrastructure service module to client's electricity consumption behavioural analysis, for Electricity customers fine-grained management provides decision-making foundation;
Feeder line analytic unit, in conjunction with described GIS service to feeder line real-time analysis;
Load forecast unit, for the historical data by temporal data model off-line analysis one-phase, thus carries out the load forecast of short-term;
Load real-time estimate unit, for carrying out real-time estimate according to the data results of described infrastructure service module to load.
Fig. 2 is the schematic flow sheet of the embodiment of the magnanimity electricity consumption data real-time computing technique based on the electricity consumption of magnanimity shown in Fig. 1 data analysis system provided by the invention, as shown in Figure 2, comprises step:
S201, adopt the ETL mode in described data acquisition module from described data source, obtain magnanimity electricity consumption data;
S202, the index reached required for real-time calculating, based on the Spark framework of described data computation module, adopt memory parallel computing technique to carry out data processing to described magnanimity electricity consumption data, and carry out denoising, filtration repetition theme/delete and irrelevant redundancy and the junk information of setting objectives;
S203, Spark framework based on described data computation module, adopt memory parallel computing technique to gather data processed result, and be stored in data warehouse by summarized results;
S204, to represent in conjunction with the described GIS service of described infrastructure service module and/or the data of Visualization Service to data warehouse.
Fig. 3 is the schematic flow sheet of the embodiment of the magnanimity electricity consumption data mining method based on the electricity consumption of magnanimity shown in Fig. 1 data analysis system provided by the invention, as shown in Figure 3, comprises step:
S301, adopt the Web service mode in described data acquisition module and ETL mode from described data source, obtain magnanimity electricity consumption data;
S302, the map technology of hadoop in Rhadoop analysis tool described in described data computation module is adopted to be stored in HDFS by described magnanimity electricity consumption data,
S303, the magnanimity electricity consumption data of the distributed computing technology of hadoop in Rhadoop analysis tool described in described data computation module are adopted to carry out data processing;
Described in S304, employing data computation module, the data mining algorithm of Spark framework or RHadoop analysis tool carries out analytical calculation to data processed result, and is stored in MySQL database by analysis result;
S305, to represent in conjunction with the described GIS service of described infrastructure service module and/or the data of Visualization Service to MySQL database.
The present invention can to the process of magnanimity electricity consumption data analysis, improve the ALARA Principle degree of mass data and the warehouse-in efficiency of mass data, the demand of satisfying magnanimity the inquiry of historical data statistical study, improve the speed that data calculate, treatment effeciency is high, provides abundant analytic statistics to meet business and management expectancy on this basis, and existing system can be allowed to process data acquisition session swimmingly, the simple application of reply represents, and meets more and more efficient statistical study demand.
Above disclosedly be only a kind of preferred embodiment of the present invention, certainly can not limit the interest field of the present invention with this, therefore according to the equivalent variations that the claims in the present invention are done, still belong to the scope that the present invention is contained.
Claims (6)
1. a magnanimity electricity consumption data analysis system, is characterized in that, comprising:
Data source, for providing magnanimity electricity consumption data;
Data acquisition module, obtains magnanimity electricity consumption data for adopting web services mode and/or ETL mode from described data source;
Data memory module, stores for the magnanimity electricity consumption data obtained described data acquisition module;
Data computation module, for adopting SmartMing and/or Rhadoop analysis tool and/or Spark framework, carries out Distributed Parallel Computing to the magnanimity electricity consumption data of described data computation module;
Infrastructure service module, for providing GIS service and Visualization Service, and carries out data analysis according to the result of calculation of described data computation module;
Electrical energy consumption analysis platform, for carrying out measuring apparatus analysis, real-time line loss calculation, electricity consumption behavioural analysis, feeder line analysis, load forecast and load real-time estimate according to described infrastructure service module.
2. magnanimity electricity consumption data analysis system as claimed in claim 1, it is characterized in that, described data source is metering automation system, energy management system, marketing system, battalion join in integration data center and external data one or more.
3. magnanimity electricity consumption data analysis system as claimed in claim 1, is characterized in that, the database that described data memory module comprises data warehouse and combines with relevant database in real time.
4. magnanimity electricity consumption data analysis system as claimed in claim 1, it is characterized in that, electrical energy consumption analysis platform comprises:
Measuring apparatus analytic unit, for judging measuring apparatus state according to the data results of described infrastructure service module, thus the cycle of minimizing tour error;
Real-time line loss calculation unit, carries out line loss calculation in real time for the smallest particles degrees of data based on each stoichiometric point, and adopts described GIS service line loss to be fed back in GIS map;
Electricity consumption behavioural analysis unit, for according to the data results of described infrastructure service module to client's electricity consumption behavioural analysis, for Electricity customers fine-grained management provides decision-making foundation;
Feeder line analytic unit, in conjunction with described GIS service to feeder line real-time analysis;
Load forecast unit, for the historical data by temporal data model off-line analysis one-phase, thus carries out the load forecast of short-term;
Load real-time estimate unit, for carrying out real-time estimate according to the data results of described infrastructure service module to load.
5., based on a magnanimity electricity consumption data real-time computing technique for magnanimity electricity consumption data analysis system according to claim 1, it is characterized in that, comprising:
Adopt the ETL mode in described data acquisition module from described data source, obtain magnanimity electricity consumption data;
According to the index reached required for calculating in real time, based on the Spark framework of described data computation module, adopt memory parallel computing technique to carry out data processing to described magnanimity electricity consumption data, and carry out denoising, filtration repetition theme/delete and irrelevant redundancy and the junk information of setting objectives;
Based on the Spark framework of described data computation module, adopt memory parallel computing technique to gather data processed result, and summarized results is stored in data warehouse;
Represent in conjunction with the described GIS service of described infrastructure service module and/or the data of Visualization Service to data warehouse.
6., based on a magnanimity electricity consumption data mining method for magnanimity electricity consumption data analysis system according to claim 1, it is characterized in that, comprising:
Adopt the Web service mode in described data acquisition module and ETL mode from described data source, obtain magnanimity electricity consumption data;
The map technology of hadoop in Rhadoop analysis tool described in described data computation module is adopted to be stored in HDFS by described magnanimity electricity consumption data,
The magnanimity electricity consumption data of the distributed computing technology of hadoop in Rhadoop analysis tool described in described data computation module are adopted to carry out data processing;
Adopt the data mining algorithm of Spark framework or RHadoop analysis tool described in data computation module to carry out analytical calculation to data processed result, and analysis result is stored in MySQL database;
Represent in conjunction with the described GIS service of described infrastructure service module and/or the data of Visualization Service to MySQL database.
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