CN103714124B - Ultra-large-scale low-voltage data processing method - Google Patents
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Abstract
The invention aims at overcoming the prejudice of the prior art, and designs a scientific ultra-large-scale low-voltage data processing method, wherein the existing network architecture is utilized, thus data storage and retrieval are much facilitated, and abnormal data therein can be analysed in time; the missing of data is also avoided during the whole system running process. The technical scheme adopted by the ultra-large-scale low-voltage data processing method disclosed by the invention is as follows: the ultra-large-scale low-voltage data processing method comprises the steps of storing the whole database in a single file on a host machine, creating a cache for low-voltage grid data in a memory according to the belonged running unit of operating personnel, forming the subset of the whole low-voltage grid, and the like. The ultra-large-scale low-voltage data processing method disclosed by the invention belongs to an improvement on the traditional technology; with the adoption of the ultra-large-scale low-voltage data processing method disclosed by the invention, the minimum calculation unit can be effectively set; due to the manner of setting a spatial grid index and combining with an R-tree index, the efficiency of indexing is greatly increased and the calculation amount is reduced.
Description
Technical field
The present invention relates to a kind of data processing method, more particularly to a kind of processing method of low voltage electric network data.
Technical background
According to Utilities Electric Co.'s overall planning, it is desirable to from distribution transformer to low pressure on the basis of existing distribution generalized information system
Electrical network extends, and complete " transformer station -10kV circuit-distribution transforming-low-voltage circuits-is set up on unified geographical information platform
The full voltage of client ", electric network model of the battalion with integration, the Topology connection that unified standard is set up between electric network models at different levels are closed
System, and the mode of hierarchical analysis, Layering manifestation is taken, reach complete full voltage level Grid model, data unification, show clear
The construction object of clear, simple operation, is that sales service, the deepening development with network service in future lays the foundation.
Low voltage electric network is the end of whole defeated supply network, direct to be connected with vast Electricity customers, possesses data volume huge
Greatly, the characteristics of concurrent user is more.By taking Zhejiang as an example, the whole province medium voltage network basic routing line about 2.2 ten thousand is always about 210,000 kilometers,
About 2,000,000, shaft tower, with altering an agreement 500,000, and the scale of low voltage electric network an order of magnitude at least more than medium voltage network, it is so super
Large-scale electric network data, while will be used by substantial amounts of sales service personnel and distribution business personnel, to low pressure data process
Design proposes very high requirement.
For big data processes the patent of invention of Publication No. CN102881162A《The data processing of large-scale traffic information
And fusion method》A kind of one data processing that large-scale traffic information is disclosed herein and fusion method, belong to transport information reality
When treatment technology, including：The standard of true value system is obtained according to the multi-source traffic data that test carriage and each sensor acquisition are arrived
Data, and determine the dynamic assignment method of parameter；Reject sensor acquisition to data acquisition system in abnormal data, and gone through
The compensation of history data；Multi-source traffic data real-time graded information fusion to completing compensation data.The invention is by setting up true value
System obtains the correct initial assignment parameter of various acquisition modes, and the data to truly collecting carry out abnormity removing, missing number
Ensured the accuracy and integrity of data according to rationally filling up according to historical data, different classes of acquisition mode is obtained
Data be classified step by step fusion treatment to ensure the reliability of data, the rapidity of fusion process, and in fusion process
Consider the impact that traffic events, traffic control, occupation of land construction, vehicle accident are brought to data.
Although this document gives us an inspiration for big data processing mode, in practical work process after all
Field of traffic and power domain still have larger difference, and the event for facing is also different, therefore are difficult directly using such
Data processing method.
《Automation of Electric Systems》Disclosed in magazine 18 phases in 2012《Low and medium voltage distribution network uniform data is gathered and monitoring system
System design and realization》The present situation and the problem for existing of low and medium voltage distribution network data acquisition analysis system are also described in one text.
With reference to the actual demand that low and medium voltage distribution network operation and management level is lifted, it is proposed that low and medium voltage distribution network uniform data is gathered and prison
Control system structure design scheme;According to the system design cooling load for determining, system intelligent data acquisition, data communication and biography are given
5 functions such as defeated system, real time data processing, user power utilization information management and monitoring, intelligent power distribution unit-area management and monitoring
Implementation.The paper proposes system safe design and the interface scheme with existed system.But data are directed in this article
The details of process is not described, and those skilled in the art cannot still know how quickly and efficiently to deal with such quantity
The data of level.
The content of the invention
The purpose of the present invention is the prejudice for overcoming prior art, designs the ultra-large low pressure data process side of a set of science
Method, using existing network architecture, the storage and retrieval of data of being more convenient for, and can analyze abnormal data therein in time.
Also the omission of data is avoided in whole system running.
The ultra-large low pressure data processing method of the present invention solves the technical scheme adopted by its technical problem：
Ultra-large low pressure data processing method, is built up in service end and concentrates deployment, the power grid GIS of client dispersion application
In framework, using ArcSDE as the service end data channel between GIS clients and relational database, using SQLite as local
Cache database, will be the electric network data of non-editing mode locally downloading, and incremental data, bag are only downloaded during follow-up maintenance
Include step 1：The whole data base is stored in a single file on host, and low voltage electric network is created in internal memory
The caching of data, the caching of electric network data are set up by the affiliated run unit of operator, form the subset of whole low voltage electric network；
Step 2：Minimum unit amount data are filled in the caching of each electric network data；
Step 3：In the caching of electric network data, grid spatial index is set, will the region division size of lines anyhow
Equal or different grid, records the spatial entities included by each grid, and 4 forked type R trees are adopted in single grid
Index；
Step 4：Data to having logged on carry out accidental validation, propose alarm to abnormal data.
Preferably, the affiliated run unit of operator described in step 1 with the branch office of county telephone central office or office of city as ultimate unit,
Each ultimate unit divides an individually caching interval.As all operations are all completed in internal memory, therefore its operational efficiency
It is very high, and manage also very convenient.
Preferably, when data are loaded and safeguarded, its minimum unit is set as low-voltage platform area.By to low pressure data
Separated time partition management, set its minimax administrative unit, ultra-large low pressure data can be divided into big one by one
Little data cell that is suitable, meeting application needs, can greatly improve the efficiency of data query and editor.
Preferably, in the step 3, the coordinate of lines anyhow of net region adopts actual region physics latitude coordinates.So
The matching being designed with beneficial to unified and actual area.
In the step 3, the concrete grammar of setting grid spatial index is：1st, coordinate points are selected；2nd, relief area is set；
3rd, dissolve that space is adjacent, specified attribute identical geographical entity is an entity；4th, B-spline curves are fitted.Wherein buffer
Area is referred to indicate the one fixed width that certain geographical entity is set up around which to the propinquity or disturbance degree of its surrounding
Banded regions.Relief area is set up, it, using a kind of very frequently spatial analysis, is that spacial influence is measured in GIS to be
A kind of important method.Dissolving space is adjacent, can greatly reduce the entity number with identical characteristics by fusion, in 100*
In 100 grid lattice, it might even be possible to the data volume being reduced within 10 digits.And it is foursquare visual usual in a grid
It is very stiff, discrete point in mesh surfaces, the consecutive variations field really fanned out from point to area generally can be using continuous bent
Line is fitted process, and here is fitted using B-spline curves.
Preferably, the method that the data in the step 4 to having logged on carry out accidental validation is：It is empty according to net type first
Between index creation to go out lines coordinate anyhow interval, a coordinate is generated at random by tandom number generator, first judges that the coordinate is
It is no in the interval of one's respective area, if not the data are then abandoned, continue to generate next coordinate；If the data are in one's respective area
In coordinate interval, then data in the coordinate figure of its adjacent 8 position are read by the numerical value, the data of the value are estimated, finally will
Estimated value and actual coordinate value are verified, and judge whether the coordinate position data is normal.
Preferably, the caching interval edited that is located is locked in being additionally included in editing process, it is to avoid other people enter simultaneously
Row operation.Equipment dynamic lock-in techniques are locked when engineering activity is created, but dynamic is locked in editing process,
So on the premise of editor's conflict is avoided, it is ensured that minimum lock-in range, more people concurrently can be operated.
The invention belongs to one kind improvement to conventional art, by ultra-large low pressure data process side of the present invention
Method can effectively arrange minimum calculation unit, by way of arranging grid spatial index and combining R trees index, drastically increase
The efficiency of index, reduces amount of calculation.
Specific embodiment
Ultra-large low pressure data processing method, is built up in service end and concentrates deployment, the power grid GIS of client dispersion application
In framework.GIS-Geographic Information System（GIS, Geographic Information System）It is a comprehensive branch of learning, in combination
It is of science to be widely applied to different fields with cartography and remote sensing and computer science, be for being input into, storing,
The computer system of inquiry, analysis and display geodata, with the development of GIS, also has GIS to be called " Geographical Information Sciences "
（Geographic Information Science）, in recent years, also have GIS to be called " geographic information services "（Geographic
Information service）.GIS is a kind of computer based instrument, and it can be analyzed to spatial information and process
（In brief, it is figure to be carried out into phenomenon present on the earth and the event for occurring and is analyzed）.GIS technology is map this only
Special visualization effect and geography-analysis function and general database manipulation（Such as inquiry and statistical analysiss etc.）It is integrated in one
Rise.GIS maximum with other information system difference is that the storage management to spatial information is analyzed, so which is in the extensive public
With event is explained in personal enterprises and institutions, is predicted the outcome, be there is practical value in plan strategy etc..
ArcSDE（SDE is Spatial Database Engine, spatial database engine）It is ArcGIS and relation data
GIS passages between storehouse.It allows user that geography information is managed in various data management systems, and answers all of ArcGIS
These data can be used with program.Led to as the service end data between GIS clients and relational database using ArcSDE
Road, using SQLite as local cache database, will be the electric network data of non-editing mode locally downloading, in follow-up maintenance process
In only download incremental data, including：
Step 1：The whole data base is stored in a single file on host, in internal memory creates low
The caching of piezoelectricity network data, the caching of electric network data are set up by the affiliated run unit of operator, form whole low voltage electric network
Subset；
Step 2：Minimum unit amount data are filled in the caching of each electric network data；
Step 3：In the caching of electric network data, grid spatial index is set, will the region division size of lines anyhow
Equal or different grid, records the spatial entities included by each grid.The characteristics of for ultra-large low pressure data, it is
The recall precision of spatial data is improved, we are provided with corresponding spatial index in each layer data caching.Spatial index is
Refer to one kind that certain spatial relationship between location and shape or spatial object according to spatial object is arranged in sequence
Data structure, wherein the mark of the summary info comprising spatial object, such as object, boundary rectangle and pointing space object entity
Pointer.The superior overall performance for directly affecting spatial database and GIS-Geographic Information System of the performance of spatial index.
In low pressure data storehouse, the grid spatial index that we are provided using ArcGIS will region lines anyhow
Equal in magnitude or not etc. grid is divided, the spatial entities included by each grid are recorded.When space querying is carried out, first
Query object place grid is calculated, then spatial entities selected by quick search in the grid again, greatly speeded up space
The inquiry velocity of index.But grid index is a kind of index of multi-to-multi, redundancy can be caused, stress and strain model must be thinner, search
Precision is higher, and certain redundancy is also bigger, and the disk space of consuming and search time are also longer.Therefore, set in low pressure data storehouse
In meter, we are divided for the space characteristics of power network object, and space characteristics approximate object is stored together, and foundation
Its space characteristics sets up the grid being adapted to, it is ensured that the efficiency of inquiry.And indexed using 4 forked type R trees in single grid；R trees
A kind of form that B-tree develops to hyperspace, spatial object is divided by it by scope, the corresponding region of each node and
One disk page, its data structure are as follows：
（1）R trees are that n forks are set, and n is referred to as the fan of R trees（fan）.
（2）Each node one rectangle of correspondence.
（3）The object less than or equal to n is contained on leafy node, its corresponding square is the outsourcing rectangle of all objects.
（4）The rectangle of non-leaf node is the outsourcing rectangle of all child node rectangles.
R trees are a kind of dynamic indexing structures, i.e.,：Its inquiry can be carried out simultaneously with insertion or deletion, and need not be determined
Phase tree construction is reorganized.As the unit of each grid design of the present invention is less, therefore at most n can only be set
It is set to 4.Higher fork number cannot also improve index efficiency.
Step 4：Data to having logged on carry out accidental validation, propose alarm to abnormal data.
The affiliated run unit of operator wherein described in step 1 with the branch office of county telephone central office or office of city as ultimate unit, often
Individual ultimate unit divides an individually caching interval.As all operations are all completed in internal memory, therefore its operational efficiency is non-
Chang Gao, and manage also very convenient.When data are loaded and safeguarded, its minimum unit is set as low-voltage platform area.By to low
The separated time partition management of pressure data, sets its minimax administrative unit, ultra-large low pressure data can be divided into one
Each and every one suitable size, the data cell for meeting application needs, can greatly improve the efficiency of data query and editor.The step
In rapid 3, the coordinate of lines anyhow of net region adopts actual region physics latitude coordinates.It is such to be designed with beneficial to unified and real
The matching in border region.In the step 3, the concrete grammar of setting grid spatial index is：1st, coordinate points are selected；2nd, arrange slow
Rush area；3rd, dissolve that space is adjacent, specified attribute identical geographical entity is an entity；4th, B-spline curves are fitted.
During concrete operations, if known n plane discrete point, is designated as Pi（i=1,2,…,n）.
1st article of B-spline Curve is drawn with P1, P2, P3, P4；
2nd article of B-spline Curve is drawn with P2, P3, P4, P5；
┇┇┇
The n-th -3 B-spline Curve are drawn with Pn-3, Pn-2, Pn-1, Pn.
The each section of curve natural sparse model drawn in aforementioned manners.
In every B-spline curves
If four discrete points are P0, P1, P2, P3；
If midpoint is：
Line starting point S is located at Δ P0P1P2Center line P1M1On, away from P1PointPlace；End of Curve is located at Δ P1P2P3In
Line P2M2On, away from P2PointPlace；
Line starting point tangent line is parallel to P0P2,
Terminal tangent line is parallel to P1P3.Cubic B-spline in grid spatial index can be just set out by such structure
Curve.
Data in the step 4 to having logged on carry out the method for accidental validation：First according to net type spatial index
It is created that lines coordinate is interval anyhow, a coordinate is generated at random by tandom number generator, first judges the coordinate whether at this
In the interval of region, if not the data are then abandoned, continue to generate next coordinate；If the data are in one's respective area coordinate area
Between in, then data in the coordinate figure of its adjacent 8 position are read by the numerical value, the data of the value are estimated, finally by estimated value
Verified with actual coordinate value, judged whether the coordinate position data is normal.
In order to avoid maloperation, the caching interval of the editor that is located is locked in editing process, it is to avoid other people are simultaneously
Operated.Equipment dynamic lock-in techniques are locked when engineering activity is created, but dynamic adds in editing process
Lock, so on the premise of editor's conflict is avoided, it is ensured that minimum lock-in range, allows more people concurrently carry out work
Make.
The present invention has been directed to Some Domestic area now, is directed to more than 6000 bar of transmission line of electricity, distribution line 20000
Remaining bar, more than 2000, transformer station.The information of these equipment can be processed at a high speed in time by the present invention.After operating personnel's use all
There is good feedback.
Claims (5)
1. ultra-large low pressure data processing method, is built up in service end and concentrates deployment, the power grid GIS of client dispersion application
In framework, using ArcSDE as the service end data channel between GIS clients and relational database, using SQLite as local
Cache database, will be the electric network data of non-editing mode locally downloading, and incremental data is only downloaded during follow-up maintenance, its
It is characterised by：Including：
Step 1：The whole local cache database is stored in a single file on host, is created in internal memory
The caching of low voltage electric network data is built, the caching of electric network data is set up by the affiliated run unit of operator, forms whole low pressure
The subset of electrical network；
Step 2：Minimum unit amount data are filled in the caching of each electric network data；
Step 3：In the caching of electric network data, grid spatial index is set, will region lines anyhow divide equal in magnitude
Or grid not etc., the spatial entities included by each grid are recorded, and is indexed using 4 forked type R trees in single grid；
Step 4：Data to having logged on carry out accidental validation, propose alarm to abnormal data；Net region in the step 3
The coordinate of lines anyhow adopt actual region physics latitude coordinates；The concrete side of grid spatial index is set in the step 3
Method is：1st, coordinate points are selected；2nd, relief area is set；3rd, dissolve that space is adjacent, specified attribute identical geographical entity is a reality
Body；4th, B-spline curves are fitted.
2. ultra-large low pressure data processing method as claimed in claim 1, it is characterised in that：Operation described in step 1
With the branch office of county telephone central office or office of city as ultimate unit, each ultimate unit divides a single buffer area to the affiliated run unit of personnel
Between.
3. ultra-large low pressure data processing method as claimed in claim 1, it is characterised in that：In the step 2, in data
When loading and safeguard, its minimum unit is set as low-voltage platform area.
4. ultra-large low pressure data processing method as claimed in claim 1, it is characterised in that：To in the step 4
The data of login carry out the method for accidental validation：It is created that lines coordinate is interval anyhow according to grid spatial index first,
One coordinate is generated at random by tandom number generator, the coordinate is first judged whether in the interval of one's respective area, if not then putting
The data are abandoned, continues to generate next coordinate；If the data in one's respective area coordinate interval in, by the digital independent its
Data in the coordinate figure of adjacent 8 positions, estimate the data value of the data, finally by the data value in estimated value and actual coordinate
Verified, judged whether the coordinate position data is normal.
5. the ultra-large low pressure data processing method as described in claim 1-4 any of which, it is characterised in that：It is additionally included in
The caching interval of the editor that is located is locked in editing process, it is to avoid other people are operated simultaneously.
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| CN104394186A (en) * | 2014-09-23 | 2015-03-04 | 山东鲁能软件技术有限公司 | Distributed cache for dynamic segmentation of grid resource based on GIS (Geographic Information System) platform |
| CN104392386A (en) * | 2014-09-23 | 2015-03-04 | 山东鲁能软件技术有限公司 | Power network resource GIS application grid segmentation method based on GIS platform |
| CN105718480B (en) * | 2014-12-05 | 2019-03-22 | 星际空间（天津）科技发展有限公司 | A method of the magnanimity three-dimensional data scheduling based on geography information |
| CN107133272B (en) * | 2017-04-07 | 2019-12-03 | 南京南瑞集团公司 | A kind of end Web magnanimity power network resources GIS data dynamic dispatching and rendering method |
| CN113190645A (en) * | 2021-05-31 | 2021-07-30 | 国家电网有限公司大数据中心 | Index structure establishing method, device, equipment and storage medium |
| CN113792051B (en) * | 2021-09-17 | 2023-08-25 | 河北幸福消费金融股份有限公司 | Data processing method, system, equipment and storage medium based on multi-mode lock |
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