CN105956772A - Equipment transaction analysis method based on power distribution network model data - Google Patents
Equipment transaction analysis method based on power distribution network model data Download PDFInfo
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Abstract
The invention belongs to the technical field of equipment model transaction analysis in the electric power industry, and provides an equipment transaction analysis method based on power distribution network model data. The method comprises the steps of: importing figure model files and storing the figure model files to corresponding data tables; carrying out transaction detection initialization, and generating a plurality of transaction lists; carrying out transaction detection, scanning a figure model file directory regularly, determining whether to create a new transaction list, and entering a file processing process; putting in models in a database; and verifying the model files entering the database; adopting a transaction analysis algorithm based on map to carry out equipment transaction analysis, and analyzing equipment transaction difference information; exporting transaction analysis result data, and confirming and checking the transaction difference information by a user; and after the transaction information is confirmed, realizing transaction model synchronization. According to the invention, the accuracy and the availability of the transaction analysis result are effectively improved, a user can more conveniently use the method, the efficiency of equipment model transaction analysis is improved, the time for transaction analysis is shortened, and the experience result of transaction analysis is enhanced for the user.
Description
Technical field
The present invention relates to power industry device model unusual fluctuation analysis technical field, be a kind of based on electricity distribution network model data
Equipment alteration analyzes method.
Background technology
At present, power distribution automation main station system model scope covers major network and distribution, including 10kV distribution artwork data
And major network artwork data.In addition to providing the graphic and model integration instrument of self, system also to possess from external system importing model
Modeling tool, including from districted dispatch system import voltage levels electric network model, be press-fitted from generalized information system or PMS system introducing
Pessimistic concurrency control, imports low-voltage equipment model etc. from marketing system.Present stage, major part distribution network model mostlys come from generalized information system,
Owing to the situation of actual track often to be safeguarded and to revise, cause the change of distribution artwork, produce model unusual action information, for
Analyze the difference of each model unusual fluctuation quickly and accurately, need a kind of method of efficient stable new legacy data is compared
Right, generate different information.
At present, existing unusual fluctuation analytical technology uses the mode of full storehouse cascade analysis mostly, and data carry out the level of complexity
Comparison analysis is looked in joint investigation；But in unusual fluctuation analysis result, in addition to equipment different information, further comprises measurement, plant stand, voltage
The information of these non-equipment classes of grade, if circuit is more in distribution main website, data volume is relatively big, uses this analysis mode to lead
Cause analysis time longer, the problems such as analysis result redundancy is high, poor user experience.
Summary of the invention
The invention provides a kind of equipment alterations based on electricity distribution network model data and analyze method, overcome above-mentioned existing skill
The deficiency of art, its can effectively solve existing equipment alteration analyze in due in distribution main website circuit many, data volume causes greatly
The problem that analysis result redundancy is high, more effectively solves existing unusual fluctuation and analyzes method unreasonable unusual fluctuation analysis time caused relatively
Long, the problem that unusual fluctuation analysis efficiency is low.
The technical scheme is that and realized by following measures: a kind of equipment based on electricity distribution network model data are different
Dynamic analysis method, comprises the following steps:
Step 1: the model data of source end system sends in the way of artwork file electrical power distribution automatization system model, distribution is certainly
Dynamicization system model verifies, resolves and distinguishes artwork file to artwork file, and artwork file is deposited into the data of correspondence
In table；
Step 2: unusual fluctuation test initialization, receives the unusual fluctuation from artwork file and asks, generate a unusual fluctuation list initializing state,
Recording the artwork fileinfo that this unusual fluctuation relates to, repeatedly unusual fluctuation request will form multiple unusual fluctuation list；
Step 3: unusual fluctuation detects, by artwork file directory timing scan, it may be judged whether receive new artwork file, work as inspection
When measuring new file, create new unusual fluctuation list, enter file process process afterwards；
Step 4: model is put in storage, verifies the artwork file of warehouse-in, when artwork file is not validated, then generates verification
Report, and will not be in import library；When artwork file is by verification, then carry out equipment alteration analysis；
Step 5: equipment alteration analysis uses unusual fluctuation parser based on map, after one or more models are put in storage, will newly enter
Model data in offline versions storehouse, in offline versions storehouse, is entered by the model data store in storehouse with the data in online version storehouse
Row compares, and analyzes equipment alteration different information；
Step 5-1: the data newly put in storage are left in map data structure, it may be assumed that map(Key, Value) structure, wherein, Key
For device id information, Value is device attribute；
Step 5-2: each record in the offline versions file after online version file and renewal is all stored in map data knot
In structure, first with online version file for inquiring about the data source of data, by each record in offline versions file all online
Version file is circulated lookup, in the presence of recording not, is then labeled as newly-increased record；In the presence of record, then compare
The device attribute of each record in Value, if device attribute is completely the same, is then zero difference, if equipment existence is poor
Different, then it is labeled as amendment；
Step 5-3: with offline versions file for inquiry data source, by each record in online version file in offline versions
File being circulated lookup, if can not find record, then being labeled as deleting；
Step 6: unusual fluctuation analysis terminates, derives unusual fluctuation analysis result data, sends unusual fluctuation analysis to the user with examination & verification authority
As a result, unusual fluctuation different information is confirmed and audits by user；
Step 7: after unusual action information confirms, it is achieved unusual fluctuation mold sync, it may be assumed that the model information newly put in storage is synchronized to distribution real-time
In storehouse, distribution main website platform uses the new distribution network model data imported.
Further optimization and/or improvements to foregoing invention technical scheme are presented herein below:
Above-mentioned when source end system model generation device information update, producing new model data in step 1, distribution is automatic
Change system receives new model data and produces new unusual fluctuation list, is put in storage by model file according to the storage mode of model data,
Form offline versions model file storehouse.
Above-mentioned in step 2, the state of unusual fluctuation list can be divided into: initializes state, activated state and history state；Wherein, activate
State be subdivided into pending, artwork is successfully accessed, artwork access failure, examination & verification by with examination & verification do not pass through, history state has been subdivided into
Effect history and invalidation history.
Above-mentioned in step 3, unusual fluctuation detection process be divided into unusual fluctuation test initialization to activate unusual fluctuation list connect to artwork file
Enter that to submit to examination & verification to examination & verification to be effective to history unusual fluctuation list by unusual fluctuation to the artwork file that is successfully accessed effective.
The present invention uses unusual fluctuation based on map structure to analyze method, from the model file of offline versions and online version
Data pattern file extracts model data information be analyzed, find equipment alteration different information, by different information
After re-forming database script and performing this script, the model information of new warehouse-in can be synchronized in distribution real-time database, distribution master
Platform can use the distribution network model data of new importing.The present invention is effectively improved the precision of unusual fluctuation analysis result and can use
Degree, more convenient user uses, and is effectively improved the efficiency that device model unusual fluctuation is analyzed, and shortens the time that unusual fluctuation is analyzed, and strengthens user
The experience effect that unusual fluctuation is analyzed.
Accompanying drawing explanation
Accompanying drawing 1 is the inventive method flow chart.
Accompanying drawing 2 is unusual fluctuation detection model flow chart of the present invention.
Accompanying drawing 3 is the particular flow sheet of step 5 of the present invention.
Detailed description of the invention
The present invention is not limited by following embodiment, can determine specifically according to technical scheme and practical situation
Embodiment.
In the present invention, for the ease of describing, the description of the relative position relation of each parts is all according to Figure of description 1
Butut mode be described, such as: the position relationship of forward and backward, upper and lower, left and right etc. is based on the Butut of Figure of description
Direction determines.
Below in conjunction with embodiment and accompanying drawing, the invention will be further described:
As shown in accompanying drawing 1,2,3, should equipment alterations based on electricity distribution network model data analysis method comprise the following steps:
Step 1: the model data of source end system sends in the way of artwork file electrical power distribution automatization system model, distribution is certainly
Dynamicization system model verifies, resolves and distinguishes artwork file to artwork file, and artwork file is deposited into the number of correspondence
According in table；
Step 2: unusual fluctuation test initialization, receives the unusual fluctuation from artwork file and asks, generate a unusual fluctuation list initializing state,
Recording the artwork fileinfo that this unusual fluctuation relates to, repeatedly unusual fluctuation request will form multiple unusual fluctuation list；
Step 3: unusual fluctuation detects, by artwork file directory timing scan, it may be judged whether receive new artwork file, work as inspection
When measuring new file, create new unusual fluctuation list, enter file process process afterwards；
Step 4: model is put in storage, verifies the artwork file of warehouse-in, when artwork file is not validated, then generates verification
Report, and will not be in import library；When artwork file is by verification, then carry out equipment alteration analysis；
Step 5: equipment alteration analysis uses unusual fluctuation parser based on map, after one or more models are put in storage, will newly enter
Model data in offline versions storehouse, in offline versions storehouse, is entered by the model data store in storehouse with the data in online version storehouse
Row compares, and analyzes equipment alteration different information；
Step 5-1: the data newly put in storage are left in map data structure, it may be assumed that map(Key, Value) structure, wherein, Key
For device id information, Value is device attribute；
Step 5-2: each record in the offline versions file after online version file and renewal is all stored in map data knot
In structure, first with online version file for inquiring about the data source of data, by each record in offline versions file all online
Version file is circulated lookup, in the presence of recording not, is then labeled as newly-increased record；In the presence of record, then compare
The device attribute of each record in Value, if device attribute is completely the same, is then zero difference, if equipment existence is poor
Different, then it is labeled as amendment；
Step 5-3: with offline versions file for inquiry data source, by each record in online version file in offline versions
File being circulated lookup, if can not find record, then being labeled as deleting；
Step 6: unusual fluctuation analysis terminates, derives unusual fluctuation analysis result data, sends unusual fluctuation analysis to the user with examination & verification authority
As a result, unusual fluctuation different information is confirmed and audits by user；
Step 7: after unusual action information confirms, it is achieved unusual fluctuation mold sync, it may be assumed that the model information newly put in storage is synchronized to distribution real-time
In storehouse, distribution main website platform uses the new distribution network model data imported.
As shown in accompanying drawing 1,2,3, in above-mentioned steps 5, after model data warehouse-in, understand as an offline versions file,
Extract form according to model file, form offline versions file.Online version file is complete phase with the form of offline versions file
With, online version file is according to the offline versions at that time preserved after last model unusual fluctuation confirmation synchronization, it may be assumed that online version
Before presents is the unusual fluctuation model warehouse-in that this is new, all model data information of extraction, off-line version from model database
After presents is the model unusual fluctuation warehouse-in that this is new, the model data information of extraction from model database.
Can according to actual needs, method of analyzing above-mentioned equipment alterations based on electricity distribution network model data is made to optimize further
Or/and improve:
As shown in accompanying drawing 1,2, in step 1, when source end system model generation device information update, produce new model literary composition
Part, electrical power distribution automatization system receives new model file can produce new unusual fluctuation list, will according to the storage mode of model data
Model file is put in storage, forms the offline versions library of model data.
As shown in accompanying drawing 1,2, in step 2, the state of unusual fluctuation list can be divided into: initializes state, activated state and history state,
Wherein, activated state be subdivided into pending, artwork is successfully accessed, artwork access failure, examination & verification by with examination & verification do not pass through, history state
It is subdivided into effective history and invalidation history.Unusual fluctuation list state is promoted to change above by the different disposal of unusual fluctuation list is operated
Becoming, including the detection of unusual fluctuation list, unusual fluctuation single activation, unusual fluctuation list process, unusual fluctuation list is audited, unusual fluctuation list comes into force, activate cancellation and unusual fluctuation
Single cancellation.
As shown in accompanying drawing 1,2,3, in step 3, unusual fluctuation detection process is divided into unusual fluctuation test initialization to activating unusual fluctuation list
Accessing to, to artwork file, the artwork file that is successfully accessed, to submit to examination & verification to examination & verification to be effective to history unusual fluctuation list by unusual fluctuation effective.
In practical operation, activate unusual fluctuation list and can start the warehouse-in handling process selecting different unusual fluctuation lists.In data processing,
Owing to model information has the possibility of overlap in different unusual fluctuation lists, can only there is one at synchronization and activate unusual fluctuation list；Right
In multiple unusual fluctuation lists being in state of activation, the operation cancelling activation can be used to postpone this unusual fluctuation list and to process, it is also possible to by different
This unusual fluctuation list is abandoned by dynamic single cancellation operation, and unusual fluctuation list will be arranged to history invalid unusual fluctuation list；It is to activate that artwork file accesses
The process of unusual fluctuation list, comprises the process that artwork file enters offline versions storehouse.Artwork file is successfully accessed, and unusual fluctuation list can open
Dynamic unusual fluctuation auditing flow；User audits unusual fluctuation single pass-through, then can start unusual fluctuation list and come into force.Above-described artwork file refers both to
Artwork file.
Above technical characteristic constitutes embodiments of the invention, and it has stronger adaptability and implementation result, can basis
It is actually needed the non-essential technical characteristic of increase and decrease, meets the demand of different situations.
Claims (4)
1. equipment alterations based on electricity distribution network model data analyze method, it is characterised in that comprise the following steps:
Step 1: the model data of source end system sends in the way of artwork file electrical power distribution automatization system model, distribution is certainly
Dynamicization system model verifies, resolves and distinguishes artwork file to artwork file, and artwork file is deposited into the data of correspondence
In table；
Step 2: unusual fluctuation test initialization, receives the unusual fluctuation from artwork file and asks, generate a unusual fluctuation list initializing state,
Recording the artwork fileinfo that this unusual fluctuation relates to, repeatedly unusual fluctuation request will form multiple unusual fluctuation list；
Step 3: unusual fluctuation detects, by artwork file directory timing scan, it may be judged whether receive new artwork file, work as inspection
When measuring new file, create new unusual fluctuation list, enter file process process afterwards；
Step 4: model is put in storage, verifies the artwork file of warehouse-in, when artwork file is not validated, then generates verification
Report, and will not be in import library；When artwork file is by verification, then carry out equipment alteration analysis；
Step 5: equipment alteration analysis uses unusual fluctuation parser based on map, after one or more models are put in storage, will newly enter
Model data in offline versions storehouse, in offline versions storehouse, is entered by the model data store in storehouse with the data in online version storehouse
Row compares, and analyzes equipment alteration different information；
Step 5-1: the data newly put in storage are left in map data structure, it may be assumed that map(Key, Value) structure, wherein, Key
For device id information, Value is device attribute；
Step 5-2: each record in the offline versions file after online version file and renewal is all stored in map data knot
In structure, first with online version file for inquiring about the data source of data, by each record in offline versions file all online
Version file is circulated lookup, in the presence of recording not, is then labeled as newly-increased record；In the presence of record, then compare
The device attribute of each record in Value, if device attribute is completely the same, is then zero difference, if equipment existence is poor
Different, then it is labeled as amendment；
Step 5-3: with offline versions file for inquiry data source, by each record in online version file in offline versions
File being circulated lookup, if can not find record, then being labeled as deleting；
Step 6: unusual fluctuation analysis terminates, derives unusual fluctuation analysis result data, sends unusual fluctuation analysis to the user with examination & verification authority
As a result, unusual fluctuation different information is confirmed and audits by user；
Step 7: after unusual action information confirms, it is achieved unusual fluctuation mold sync, it may be assumed that the model information newly put in storage is synchronized to distribution real-time
In storehouse, distribution main website platform uses the new distribution network model data imported.
Equipment alterations based on electricity distribution network model data the most according to claim 1 analyze method, it is characterised in that in step
In rapid 1, when source end system model generation device information update, producing new model data, electrical power distribution automatization system receives
New model data produces new unusual fluctuation list, is put in storage by model file according to the storage mode of model data, forms offline versions
Model file storehouse.
Equipment alterations based on electricity distribution network model data the most according to claim 1 analyze method, it is characterised in that in step
In rapid 2, the state of unusual fluctuation list can be divided into: initializes state, activated state and history state；Wherein, activated state is subdivided into pending, figure
Mould is successfully accessed, artwork access failure, examination & verification by with examination & verification do not pass through, history state is subdivided into effective history and invalidation history.
Equipment alterations based on electricity distribution network model data the most according to claim 1 analyze method, it is characterised in that in step
In rapid 3, unusual fluctuation detection process is divided into unusual fluctuation test initialization to activating the figure that unusual fluctuation list accesses to be successfully accessed to artwork file
It is effective that mould file submits to examination & verification to examination & verification to be effective to history unusual fluctuation list by unusual fluctuation.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106777220A (en) * | 2016-12-23 | 2017-05-31 | 积成电子股份有限公司 | A kind of processing method of the continuous unusual fluctuation of power distribution network artwork |
| CN108228726A (en) * | 2017-12-11 | 2018-06-29 | 厦门亿力吉奥信息科技有限公司 | The increment unusual fluctuation content acquisition method and storage medium of power distribution network red and black figure |
| CN109542977A (en) * | 2018-10-29 | 2019-03-29 | 国网新疆电力有限公司昌吉供电公司 | Future-state distribution artwork data processing method based on IEC standard |
| CN111597280A (en) * | 2020-04-15 | 2020-08-28 | 广东电网有限责任公司电力调度控制中心 | EMS power transformation graph model and power grid GIS platform graph model increment adaptation system and method |
| CN112130924A (en) * | 2020-08-18 | 2020-12-25 | 贝壳技术有限公司 | Application system data analysis method and device |
| CN115496626A (en) * | 2022-10-24 | 2022-12-20 | 国网浙江省电力有限公司象山县供电公司 | Distribution network graph model transaction identification processing method and system |
| CN117216592A (en) * | 2023-11-07 | 2023-12-12 | 青岛港国际股份有限公司 | Idle analysis system and analysis method for assets |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106777220A (en) * | 2016-12-23 | 2017-05-31 | 积成电子股份有限公司 | A kind of processing method of the continuous unusual fluctuation of power distribution network artwork |
| CN108228726A (en) * | 2017-12-11 | 2018-06-29 | 厦门亿力吉奥信息科技有限公司 | The increment unusual fluctuation content acquisition method and storage medium of power distribution network red and black figure |
| CN109542977A (en) * | 2018-10-29 | 2019-03-29 | 国网新疆电力有限公司昌吉供电公司 | Future-state distribution artwork data processing method based on IEC standard |
| CN109542977B (en) * | 2018-10-29 | 2023-04-28 | 国网新疆电力有限公司昌吉供电公司 | Future state distribution network graph data processing method based on IEC standard |
| CN111597280A (en) * | 2020-04-15 | 2020-08-28 | 广东电网有限责任公司电力调度控制中心 | EMS power transformation graph model and power grid GIS platform graph model increment adaptation system and method |
| CN111597280B (en) * | 2020-04-15 | 2023-08-18 | 广东电网有限责任公司电力调度控制中心 | Incremental adaptation method for EMS transformation graph model and power grid GIS platform graph model |
| CN112130924A (en) * | 2020-08-18 | 2020-12-25 | 贝壳技术有限公司 | Application system data analysis method and device |
| CN115496626A (en) * | 2022-10-24 | 2022-12-20 | 国网浙江省电力有限公司象山县供电公司 | Distribution network graph model transaction identification processing method and system |
| CN117216592A (en) * | 2023-11-07 | 2023-12-12 | 青岛港国际股份有限公司 | Idle analysis system and analysis method for assets |
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Application publication date: 20160921 |