CN111090710A - Distribution network multi-time scale graph-model abnormal automatic maintenance method - Google Patents
Distribution network multi-time scale graph-model abnormal automatic maintenance method Download PDFInfo
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Abstract
The invention discloses a distribution network multi-time scale graph model transaction automatic maintenance method, which fully considers the current situation of frequent distribution network topology change, realizes the full-automatic import of a distribution network graph model, and greatly improves the operation management efficiency of a distribution network; two sets of graph model systems of a pre-release graph model and a final graph model are provided, so that the examination and the management are convenient, and the consistency of the graph models and an actual distribution network is ensured; model checking and graph model consistency checking are provided, and the improvement of the distribution network graph model quality is effectively promoted; error isolation and rollback are realized, and a guarantee is provided for long-term stable operation of a graph model maintenance mechanism; after the final graph model is successfully imported, the transaction marks in the network model library and the intermediate debugging library where the pre-distribution graph model is located are cleared in time, so that scheduling operators can master the reconstruction current situation of the feeder line, and closed-loop management of feeder line reconstruction work is realized. The invention can realize the full life cycle monitoring of the operation, the decommissioning and the transformation of the feeder line and equipment, and effectively improve the operation management level of the power distribution network.
Description
Technical Field
The invention relates to a distribution network multi-time scale graph-model abnormal automatic maintenance method, and belongs to the technical field of distribution network automation of a power system.
Background
At present, with the annual improvement of the social development level, the requirement on the management level of the power distribution network is higher and higher. The distribution network topology changes frequently, and how to realize effective management of distribution network graph model transaction becomes an important subject.
In the existing distribution network maintenance, the distribution network feeder line is frequently modified, a large amount of graph model maintenance requirements exist in one area every day, the traditional method relying on hand-drawing has heavy tasks, low efficiency and easy error, and the modification state of the on-site feeder line cannot be displayed in real time; the 'red and black graph mechanism' proposed later provides a network model of two time scales of a red graph and a black graph, solves the problem of graph inconsistency to a certain extent, needs a specially-assigned person to maintain the graph model state, and still has a large workload.
Disclosure of Invention
The purpose is as follows: in order to overcome the defects of heavy maintenance work, low efficiency and easy error of distribution network graphic models in the prior art, in particular to the management of the storage and verification processes of all versions of the graphic models, the invention provides a distribution network multi-time scale graphic model difference automatic maintenance method, which isolates a pre-release graphic model from a final graphic model, carries out debugging based on the pre-release graphic model, and finally releases the measuring point quantity to an operating system, and has high efficiency and strong robustness.
The technical scheme is as follows: in order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a distribution network multi-time scale graph model transaction automatic maintenance method comprises the following steps:
firstly, a graph model transaction background management process monitors a graph model pushing path of a PMS system or a GIS system in real time, and the PMS system or the GIS system pushes the graph model to a power distribution automation system by taking a feeder line as a unit; judging whether the pushing graph model is a pre-sending graph model or a final graph model;
step two, when the push graph model is a pre-release graph model, conducting import operation, importing the pre-release model into a network model library, importing the pre-release model into an intermediate debugging library after the pre-release model passes verification and generating a measuring point, importing the pre-release graph into a graph system, and checking whether the pre-release graph and the pre-release model are consistent;
step three, when the pushed graph model is the final graph model, conducting import operation, importing the final model into a network model library, importing the final model into an operation library and importing a measuring point after the final model passes verification, importing the final graph into a graph system, and checking whether the final graph is consistent with the final model;
and step four, when the final graph model is successfully imported, associating the final graph model with the picture foreground, and clearing the network model library of the pre-published graph model and the inter-debugging library transaction equipment mark.
Also comprises the following steps:
if the import operation in the second step or the third step has errors, the background management process of the graph model transaction can terminate the import flow of the graph model, output error information to the file, and automatically return the file to the PMS system or the GIS system.
The graph model transaction background management process supports error isolation and rollback operation and is used for ensuring that no major error occurs in the middle debugging library and the running library and the graph model maintenance is influenced;
the error isolation and rollback operation comprises the steps of:
setting a first model space and a second model space in a network model library, and the first step: covering the model in the second model space with the first model space; the second step is that: importing a new model into a first model space, and covering a new model of the first model space with a second model space if the new model is successfully imported; if the new model import fails, the second model space is not covered. The process can be used for ensuring the accuracy of the graph model in the second model space, and when the first model space fails to be lost, the correct graph model state can be quickly returned.
And setting a first monitoring space and a second monitoring space in the network model library, wherein the first monitoring space is used for storing the model to be verified, and the second monitoring space is used for importing the successfully verified model in the first monitoring space. For achieving isolation of error patterns.
The distribution automation system comprises a graph model transaction maintenance tool which is used for displaying all pre-distribution graph models and final graph models which are successfully or unsuccessfully imported; and opening the picture of the successfully imported graph model support for auditing, and re-importing the unsuccessfully imported graph model support.
The method for clearing the network model library and the intermediate debugging library transaction equipment mark of the pre-release graph model comprises the following steps:
firstly, setting state quantity of the transaction equipment in a network model library and an intermediate debugging library, wherein the state quantity comprises: add, delete, or modify;
secondly, after the pre-layout pattern is confirmed, a final pattern is formed and is led into a distribution automation system;
and thirdly, eliminating the state quantity of the abnormal equipment of the pre-release graph model in the network model library and the intermediate debugging library, and representing that the feeder line is formally put into operation.
The distribution automation system includes: a network model library, an intermediate debugging library, a graphic system and an operation library; the network model library is used for analyzing the model file to form a library file and carrying out model verification; the intermediate debugging library is used for storing the pre-release model and generating a measuring point; the graphic system is used for storing the graphics and checking the consistency of the graphics and the model; and the operation library is used for comparing and confirming the model and the measuring points, storing the final model and finishing generating the picture foreground.
The pre-release graph model is formed by adding, deleting or modifying equipment on the basis of the initial graph model, and comprises a pre-release model and a pre-release graph.
And the final graph model is formed after the behavior of adding, deleting or modifying the pre-layout model is confirmed, and comprises a final model and a final graph.
The model checking comprises the following steps: and checking whether all the warehousing equipment is renamed, checking whether the voltage grades and the connection relations of all the equipment are correct, and checking whether the attributes of all the warehousing equipment are lost.
The multi-time scale is that a feed line is taken as a unit, a PMS system or a GIS system pushes a pre-distribution graph model of one feed line to a distribution automation system at one time, after the pre-distribution graph model is successfully led in, and after the feed line modification work is finished and confirmed, the final graph model of the feed line is pushed, so that the feed line graph model of the distribution automation system is ensured to be consistent with the field reality, graph model files of a plurality of time scales can be stored in the distribution automation system, the data integrity of the single feed line can be ensured, and the workload of data transmission and processing can be reduced.
Has the advantages that: according to the distribution network multi-time scale graph model transaction automatic maintenance method, the current situation that the distribution network topology changes frequently is fully considered, the full-automatic import of the distribution network graph model is realized, and the operation management efficiency of the distribution network is greatly improved; two sets of graph model systems of a pre-release graph model and a final graph model are provided, so that the examination and the management are convenient, and the consistency of the graph models and an actual distribution network is ensured; model checking and graph model consistency checking are provided, and the improvement of the distribution network graph model quality is effectively promoted; error isolation and rollback are realized, and a guarantee is provided for long-term stable operation of a graph model maintenance mechanism; after the final graph model is successfully imported, the transaction marks in the network model library and the intermediate debugging library where the pre-distribution graph model is located are cleared in time, so that scheduling operators can master the reconstruction current situation of the feeder line, and closed-loop management of feeder line reconstruction work is realized. The invention can realize the full life cycle monitoring of the operation, the decommissioning and the transformation of the feeder line and equipment, and effectively improve the operation management level of the power distribution network.
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FIG. 1 is a flow chart of an automatic maintenance method of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
As shown in fig. 1, a distribution network multi-time scale graph model automatic maintenance method includes the following steps:
firstly, a graph model transaction background management process monitors a graph model pushing path of a PMS system or a GIS system in real time, and the PMS system or the GIS system pushes the graph model to a power distribution automation system by taking a feeder line as a unit; judging whether the pushing graph model is a pre-sending graph model or a final graph model;
the distribution automation system comprises a graph model transaction maintenance tool which is used for displaying all pre-distribution graph models and final graph models which are successfully or unsuccessfully imported; and opening the picture of the successfully imported graph model support for auditing, and re-importing the unsuccessfully imported graph model support.
Step two, when the push graph model is a pre-release graph model, conducting import operation, importing the pre-release model into a network model library, importing the pre-release model into an intermediate debugging library after the pre-release model passes verification and generating a measuring point, importing the pre-release graph into a graph system, and checking whether the pre-release graph and the pre-release model are consistent;
step three, when the pushed graph model is the final graph model, conducting import operation, importing the final model into a network model library, importing the final model into an operation library and importing a measuring point after the final model passes verification, importing the final graph into a graph system, and checking whether the final graph is consistent with the final model;
if the import operation in the second step or the third step has errors, the background management process of the graph model transaction can terminate the import flow of the graph model, output error information to the file, and automatically return the file to the PMS system or the GIS system.
The graph model transaction background management process supports error isolation and rollback operation and is used for ensuring that no major error occurs in the middle debugging library and the running library and the graph model maintenance is influenced;
the error isolation and rollback operation comprises the steps of:
setting a first model space and a second model space in a network model library, and the first step: covering the model in the second model space with the first model space; the second step is that: importing a new model into a first model space, and covering a new model of the first model space with a second model space if the new model is successfully imported; if the new model import fails, the second model space is not covered. The process can be used for ensuring the accuracy of the graph model in the second model space, and when the first model space fails to be lost, the correct graph model state can be quickly returned.
And setting a first monitoring space and a second monitoring space in the network model library, wherein the first monitoring space is used for storing the model to be verified, and the second monitoring space is used for importing the successfully verified model in the first monitoring space. For achieving isolation of error patterns.
And step four, when the final graph model is successfully imported, associating the final graph model with the picture foreground, and clearing the network model library of the pre-published graph model and the inter-debugging library transaction equipment mark.
The method for clearing the network model library and the intermediate debugging library transaction equipment mark of the pre-release graph model comprises the following steps:
firstly, setting state quantity of the transaction equipment in a network model library and an intermediate debugging library, wherein the state quantity comprises: add, delete, or modify;
secondly, after the pre-layout pattern is confirmed, a final pattern is formed and is led into a successful power distribution automation system;
and thirdly, eliminating the state quantity of the abnormal equipment of the pre-release graph model in the network model library and the intermediate debugging library, and indicating that the feeder line is formally arranged and operated.
The distribution automation system includes: a network model library, an intermediate debugging library, a graphic system and an operation library; the network model library is used for analyzing the model file to form a library file and carrying out model verification; the intermediate debugging library is used for storing the pre-release model and generating a measuring point; the graphic system is used for storing the graphics and checking the consistency of the graphics and the model; and the operation library is used for comparing and confirming the model and the measuring points, storing the final model and finishing generating the picture foreground.
The pre-release graph model is formed by adding, deleting or modifying equipment on the basis of the initial graph model, and comprises a pre-release model and a pre-release graph.
And the final graph model is formed after the behavior of adding, deleting or modifying the pre-layout model is confirmed, and comprises a final model and a final graph.
The model checking comprises the following steps: and checking whether all the warehousing equipment is renamed, checking whether the voltage grades and the connection relations of all the equipment are correct, and checking whether the attributes of all the warehousing equipment are lost.
The multi-time scale is that a feed line is taken as a unit, a PMS system or a GIS system pushes a pre-distribution graph model of one feed line to a distribution automation system at one time, after the pre-distribution graph model is successfully led in, and after the feed line modification work is finished and confirmed, the final graph model of the feed line is pushed, so that the feed line graph model of the distribution automation system is ensured to be consistent with the field reality, and graph model files of a plurality of time scales can be stored in the distribution automation system, thereby not only ensuring the data integrity of the single feed line, but also reducing the workload of data transmission and processing.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (9)
1. A distribution network multi-time scale graph model abnormal automatic maintenance method is characterized in that: the method comprises the following steps:
firstly, a graph model transaction background management process monitors a graph model pushing path of a PMS system or a GIS system in real time, and the PMS system or the GIS system pushes the graph model to a power distribution automation system by taking a feeder line as a unit; judging whether the pushing graph model is a pre-sending graph model or a final graph model;
step two, when the push graph model is a pre-release graph model, conducting import operation, importing the pre-release model into a network model library, importing the pre-release model into an intermediate debugging library after the pre-release model passes verification and generating a measuring point, importing the pre-release graph into a graph system, and checking whether the pre-release graph and the pre-release model are consistent;
step three, when the pushed graph model is the final graph model, conducting import operation, importing the final model into a network model library, importing the final model into an operation library and importing a measuring point after the final model passes verification, importing the final graph into a graph system, and checking whether the final graph is consistent with the final model;
and step four, when the final graph model is successfully imported, associating the final graph model with the picture foreground, and clearing the network model library of the pre-published graph model and the inter-debugging library transaction equipment mark.
2. The distribution network multi-time scale graph model transaction automatic maintenance method according to claim 1, characterized in that: also comprises the following steps:
if the import operation in the second step or the third step has errors, the background management process of the graph model transaction can terminate the import flow of the graph model, output error information to the file, and automatically return the file to the PMS system or the GIS system.
3. The distribution network multi-time scale graph model automatic maintenance method according to claim 1 or 2, characterized in that: the graph model transaction background management process supports error isolation and rollback operation, and the error isolation and rollback operation comprises the following steps:
setting a first model space and a second model space in a network model library, and the first step: covering the model in the second model space with the first model space; the second step is that: importing a new model into a first model space, and covering a new model of the first model space with a second model space if the new model is successfully imported; if the new model is failed to be imported, the second model space is not covered;
and setting a first monitoring space and a second monitoring space in the network model library, wherein the first monitoring space is used for storing the model to be verified, and the second monitoring space is used for importing the successfully verified model in the first monitoring space.
4. The distribution network multi-time scale graph model transaction automatic maintenance method according to claim 1, characterized in that: the distribution automation system also comprises a graph model transaction maintenance tool which is used for displaying all pre-distributed graph models and final graph models which are successfully or unsuccessfully imported; and opening the picture of the successfully imported graph model support for auditing, and re-importing the unsuccessfully imported graph model support.
5. The distribution network multi-time scale graph model transaction automatic maintenance method according to claim 1, characterized in that: the method for clearing the network model library and the intermediate debugging library transaction equipment mark of the pre-release graph model comprises the following steps:
5.1 setting the state quantity of the transaction equipment in the network model library and the intermediate debugging library, wherein the state quantity comprises: add, delete, or modify;
5.2 after the pre-layout pattern is confirmed, forming a final pattern, and importing the final pattern into a distribution automation system;
and 5.3, eliminating the state quantity of the transaction equipment of the pre-release graph model in the network model library and the intermediate debugging library, and representing that the feeder line is formally put into operation.
6. The distribution network multi-time scale graph model transaction automatic maintenance method according to claim 1, characterized in that: the distribution automation system includes: a network model library, an intermediate debugging library, a graphic system and an operation library; the network model library is used for analyzing the model file to form a library file and carrying out model verification; the intermediate debugging library is used for storing the pre-release model and generating a measuring point; the graphic system is used for storing the graphics and checking the consistency of the graphics and the model; and the operation library is used for comparing and confirming the model and the measuring points, storing the final model and finishing generating the picture foreground.
7. The distribution network multi-time scale graph model transaction automatic maintenance method according to claim 1, characterized in that: the pre-release graph model is formed by adding, deleting or modifying equipment on the basis of the initial graph model, and comprises a pre-release model and a pre-release graph.
8. The distribution network multi-time scale graph model transaction automatic maintenance method according to claim 1, characterized in that: and the final graph model is formed after the behavior of adding, deleting or modifying the pre-layout model is confirmed, and comprises a final model and a final graph.
9. The distribution network multi-time scale graph model transaction automatic maintenance method according to claim 1, characterized in that: the model checking comprises the following steps: and checking whether all the warehousing equipment is renamed, checking whether the voltage grades and the connection relations of all the equipment are correct, and checking whether the attributes of all the warehousing equipment are lost.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114781658A (en) * | 2022-03-16 | 2022-07-22 | 广西电网有限责任公司南宁供电局 | Distribution network graph-model synchronous checking, positioning and analyzing method and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105913334A (en) * | 2016-04-08 | 2016-08-31 | 国网福建省电力有限公司 | Visualized detection method for online abnormal movements of power distribution automation graph and model |
| 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 |
| CN109377412A (en) * | 2018-12-04 | 2019-02-22 | 贵州电网有限责任公司 | A kind of intensive artwork maintenance system of auxiliary tone and its maintaining method |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105913334A (en) * | 2016-04-08 | 2016-08-31 | 国网福建省电力有限公司 | Visualized detection method for online abnormal movements of power distribution automation graph and model |
| 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 |
| CN109377412A (en) * | 2018-12-04 | 2019-02-22 | 贵州电网有限责任公司 | A kind of intensive artwork maintenance system of auxiliary tone and its maintaining method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114781658A (en) * | 2022-03-16 | 2022-07-22 | 广西电网有限责任公司南宁供电局 | Distribution network graph-model synchronous checking, positioning and analyzing method and system |
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