CN113870051A - Graph-model bidirectional error-free calibration method for power distribution network - Google Patents
Graph-model bidirectional error-free calibration method for power distribution network Download PDFInfo
- Publication number
- CN113870051A CN113870051A CN202111134926.6A CN202111134926A CN113870051A CN 113870051 A CN113870051 A CN 113870051A CN 202111134926 A CN202111134926 A CN 202111134926A CN 113870051 A CN113870051 A CN 113870051A
- Authority
- CN
- China
- Prior art keywords
- model
- graph
- data
- verification
- topology
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 40
- 230000002457 bidirectional effect Effects 0.000 title claims abstract description 27
- 238000012795 verification Methods 0.000 claims abstract description 116
- 238000007906 compression Methods 0.000 claims description 20
- 230000006835 compression Effects 0.000 claims description 20
- 238000000547 structure data Methods 0.000 claims description 7
- 238000013524 data verification Methods 0.000 claims description 6
- 206010021703 Indifference Diseases 0.000 claims description 5
- 230000004069 differentiation Effects 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 abstract description 4
- 235000019580 granularity Nutrition 0.000 description 8
- 238000012545 processing Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000013144 data compression Methods 0.000 description 4
- 230000010354 integration Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
Images
Classifications
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- Databases & Information Systems (AREA)
- General Physics & Mathematics (AREA)
- Water Supply & Treatment (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a graph-model bidirectional error-free verification method for a power distribution network, and belongs to the technical field of calculation, calculation or counting. The method comprises the steps of forward checking from a model topology to a graph topology and reverse checking from the graph topology to the model topology, wherein the steps are called as 1:1 graph modulo no difference check. Meanwhile, the power grid generally has thematic maps with various abstraction levels, the model with the finest granularity is abstracted correspondingly according to the abstraction level of the graph, and then forward verification from the model to the graph and reverse verification from the graph to the model are carried out, which are called as N: 1 graph modulo no difference check. The graph model is verified by the verification method, the graph model data can be verified and compared from multiple angles and multiple sides, and the consistency of the graph model data is better ensured.
Description
Technical Field
The invention relates to an operation and scheduling automation technology of a power system, in particular to a graph-model bidirectional error-free verification method for a power distribution network, and belongs to the technical field of calculation, calculation or counting.
Background
The graph-model integration technology is a technology for storing and managing by establishing a corresponding relationship of mutual conversion of graphs and data. In an electric power system, the application of a graph-model integration technology is more and more extensive, and particularly, a graph-model conversion and verification technology developed for a distribution automation main station system is also greatly developed. The graph-model checking method is a key function in graph-model integration and is used for ensuring the one-to-one correspondence relationship between graphs and database models. However, in practical applications, model data errors or graphic data errors often occur, even errors of inconsistent graphic data occur, which cause application data errors in the distribution automation master station system, and in more serious cases may cause errors in judgment or operation of power grid operation and scheduling personnel.
The existing graph-model checking method mainly focuses on the checking of the transformer substation graph-model at the main network side, only involves 1:1 unidirectional consistency checking, does not consider the multi-dimensional attribute checking of graph-model data, and has the defect of insufficient checking comprehensiveness. In order to meet the requirements of comprehensiveness, tightness, reasonableness, flexibility, consistency and the like of the graph-model verification of the power distribution network, the invention aims to provide a bidirectional indifference verification method for conducting multi-dimensional attribute verification on graph-model data and meeting the practical application requirements of the minimal fine-grained indifference verification of graphs at different abstract levels.
Disclosure of Invention
The invention aims to provide a power distribution network graph-model bidirectional error-free checking method aiming at the defects of the background technology, the aim of accurately checking the power distribution network graph-model data is achieved by carrying out bidirectional checking on the multidimensional attribute of the graph-model data, and the technical problems that the unidirectional simple graph-model checking technology has errors and cannot meet the actual application requirements of the power distribution network graph-model data graph-model checking are solved.
The invention adopts the following technical scheme for realizing the aim of the invention:
a power distribution network graph-model bidirectional error-free verification method comprises the following five steps.
Step one, preparing graph model data:
and acquiring a power grid CIM/XML model file and various CIM/SVG theme graphic files based on the IEC61970 standard from the power distribution automation master station system.
Step two, model data compression:
and abstracting or compressing the CIM/XML model file with the minimum fine granularity according to different abstraction levels of the CIM/SVG theme graphic file to obtain model data containing N levels.
Step three, checking view definition:
step 3-1, compressing the model data obtained in the step two to an Nth layer according to a defined graph compression rule, and then obtaining a verification view of the model data of the Nth layer, wherein the graph compression rule comprises but is not limited to feeder segment compression, disconnecting link compression and earth knife compression;
step 3-2, defining a checking rule, wherein the model checking rule comprises but is not limited to: the method comprises the following steps of model file format verification, model attribute value verification, model topology connection relation verification, model power supply point verification and model island verification, wherein a graph verification rule comprises but is not limited to: checking the format of the graphic file, checking the attribute of the graphic, checking the value of the attribute of the graphic, checking the connection relation of the graphic and the like;
and 3-3, selecting the graph-model data attribute to be verified from the rules according to the verification view, such as the equipment, container or asset to be verified and the attribute value thereof.
Step four, performing N from step 4-1 to step 4-3 on the model data of the Nth layer and the corresponding check view: 1, consistency check, namely performing consistency check on the model data of the Nth layer and the corresponding check view according to the steps 1:1, consistency check, using equipment in the model data of the Nth layer as a unit, searching equipment in a check view corresponding to the model data of the Nth layer, and performing consistency check according to the following steps of 1:1, comparing the device data one by a consistency check method, and specifying model data of different levels and corresponding check views according to requirements to perform the steps of 1:1, consistency check;
step 4-1, taking the model data as a reference, and carrying out forward graph-mode verification from the model topology to the graph topology: classifying equipment data which do not exist in the model and exist in the graph into a graph differentiated data class; defining and checking equipment data, container data and asset data which are all present in the model and the graph according to a checking rule, and classifying partial data with difference in attributes or attribute values into graph model common differential data; defining and checking equipment data, container data and asset data which are all present in the model and the graph according to a checking rule, and classifying the equipment data, the container data and the asset data with the completely same attribute values into the graph model and sharing the same data;
step 4-2, comparing the model topology data with the graph topology data of the check view to obtain a topology differentiation data check result;
and 4-3, carrying out reverse graph-model verification from the graph topology to the model topology by taking the graph data as a reference: devices not present in the graph but present in the model are classified as model differentiated data; the equipment data existing in both the graph and the model are verified according to the verification rule definition, and data with part of attributes or different attribute values are classified into graph and model common differential data; checking the equipment data existing in both the graph and the model according to the definition of a check rule, and classifying the completely same equipment data into the graph and the model which share the same data;
step five: and outputting a verification result, combining the same verification result in the common differential data of the forward graph model and the reverse graph model obtained by the verification of the forward graph model and the reverse graph model to obtain a final common differential data verification result of the graph model, forming the differential data of the graph model, the common differential data of the graph model and the differential data of the topology, classifying according to the verification result, and outputting into an error report file.
By adopting the technical scheme, the invention has the following beneficial effects:
(1) the invention compresses the minimum granularity model data by defining different models, graphs and graph-model indifference check rules, compresses the compressed model data according to the actual application requirements (for example, performing graph-model check on a switch layer) to obtain check views of the specified layer model data, obtains check views of different description angles for the same specified layer model data through different graph check rules, selects the check rules according to the check views of the specified layer model data, further performs bidirectional check on the graph data and the graph-model data, and performs check and comparison on the graph-model data from multiple angles and multiple data attribute dimensions, thereby better ensuring the consistency of the graph-model data, improving the accuracy of the graph-model check, and meeting the requirements of the comprehensiveness, the tightness, the reasonability, the flexibility, the precision, the accuracy and the like of the graph-model check of the power distribution network, Consistency and the like.
(2) Aiming at the actual application requirements of a power distribution network with multiple thematic maps of different abstract levels, the invention abstracts and compresses model data at different levels to ensure that the granularity of the compressed model meets the actual application requirements, omits unnecessary information, and carries out graph-mode bidirectional verification on the graph-mode data at different granularities to meet the requirement of graph-mode indifference verification of the thematic maps of different abstract levels of the power distribution network.
(3) And the verification result is displayed in a certain form or format, and power supply network operation and maintenance personnel search and locate the data and correct the data, so that the requirements of distribution network maintenance and operation are met.
Drawings
Fig. 1 is a flowchart of a bidirectional error-free verification method for a power distribution network according to the present invention.
FIG. 2 is a schematic diagram of a forward graph modulo the function of a no-difference check.
FIG. 3 is a schematic diagram of a reverse graph modulo the function of a non-differential check.
FIG. 4 is a diagram of the present invention with reference to a configuration rule base.
Fig. 5 is a schematic diagram of a feeder segment compression rule in an embodiment of the present invention.
Fig. 6 is a schematic diagram illustrating a result of graph-model bi-directional error-free verification according to an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is explained in detail in the following with reference to the attached drawings.
A distribution network graph-model bidirectional error-free verification method comprises a forward verification from a model topology to a graph topology and a reverse verification from the graph topology to the model topology, and is called as 1:1 graph modulo no difference check. Meanwhile, the power grid generally has thematic maps with various abstraction levels, the model with the finest granularity is abstracted correspondingly according to the abstraction level of the graph, and then forward verification from the model to the graph and reverse verification from the graph to the model are carried out, which are called as N: 1 graph modulo no difference check. The graph model is verified by the verification method, the graph model data can be verified and compared from multiple angles and multiple sides, and the consistency of the graph model data is better ensured. The flow of graph-modulo two-way verification is shown in fig. 1.
Performing 1:1, verifying differential data (namely common differential data of the graph model) in common data of the model and the graph and differential data (namely differential data of the graph model) which does not exist in the model and exists in the graph by taking model data as a reference; the common differential data of the graph model is data with difference in common equipment, common containers and common asset data in the model and the graph; the graphs and the models share the same data, namely the data of the device data, the container data or the asset data existing in the models and the graphs are verified to be the same, as shown in FIG. 2.
Model data is processed by graph data by 1:1, checking differential data (namely common differential data of the graph and the model) in common data of the graph and the model and differential data (namely differential data of the model) which does not exist in the graph but exists in the model by taking the graph data as a reference; the graph differentiated data is equipment, container and asset data which exist in the graph but do not exist in the model; the common differential data of the graph model is data which is common equipment in the graph and the model but has difference, and the data and the common differential data in the forward graph model no-difference check have overlapped data and need to be combined with the same data; the graph model shares the same data as the data of the model and the verification in the graph; as shown in fig. 3.
Compared with SVG (scalable vector graphics) graphic description information, XML model description is more comprehensive and more detailed and is the model with the finest granularity. Because the graphic file is often simplified aiming at different application scenes and is an abstracted coarse granularity view, the two-way verification of the graphic file and the abstract coarse granularity view needs a unified model description view angle. When the graph model is subjected to bidirectional error-free verification, model data can be compressed or abstracted according to a user-defined rule to form a model view matched with the graph, and then the graph model is subjected to bidirectional verification on the basis. N: 1 the core of forward and backward graph model error-free check is to compress or abstract the model data according to the defined check rule.
The model data compression method is that according to the model data compression rules defined in the rule base, the topological connection relation is compressed according to the equipment type, the unimportant or unappreciated detail data is removed, and the reasonable model data backbone is extracted for verification.
The model data abstraction method is to abstract all the connection devices into general nodes according to the model data abstraction rules defined in the rule base, form an internal topological connection relation, simplify or perform other special processing on the topological connection relation, and compare and verify the topological connection relation of the whole network after the processing is completed.
Processing the model data according to a defined compression or abstraction rule, and then carrying out forward or reverse graph model error-free verification, wherein the verification method and the process are as follows: 1 positive and negative graphs are identical in modulo no difference check.
Checking the design of a rule base, considering that the drawing model has various sources and different detailed degrees, on one hand, checking the semantic grammar and the data of the model through different rules, and checking the correctness of the SVG format, the drawing layer, the symbol and the topology description of the drawing file; on the other hand, data normalization needs to be performed on different graph models, the models are mapped into different views through different rules, and homodyne verification is performed on the models and the matched graph views. These rules support customization and extensibility.
As shown in fig. 4, a graph-model bidirectional indifferent verification view under different scales from macro to micro at various viewing angles can be formed by rule base configuration, and one verification view can contain various different types of verification rules:
firstly, the model is not increased when viewed from the graph;
viewing the graph from the model without increment;
measuring semantic consistent with the object.
A distribution network graph-model bidirectional error-free verification method is combined with IEC61970/CIM standards to verify model data and graph data, and verification details and contents are defined by verification rules. The specific verification steps and flow are as follows:
step 1: graph-model two-way error-free check rule definition
In the graph-model bidirectional error-free check rule, firstly, a model check rule is defined, which comprises: the method comprises the following steps of model file format verification, model attribute value verification, model topology connection relation verification, model power supply point verification, model island verification and the like. The graph verification rule comprises the following steps: graphic file format verification, graphic attribute value verification, graphic connection relation verification and the like. N: in the graph mode two-way error-free check, a graph compression rule is defined, and the graph compression rule is as follows: feeder section compression, disconnecting link compression, ground knife compression and the like.
For example, based on the graphics application requirements of the tone, a two-way consistency check verification of the graphics model is performed. The model used for the allotment is a graph obtained after the feeder section is compressed, the model provides a model for the PMS, and fig. 5 is a graph obtained after the feeder section compression rule is based. Thus, the verification view is defined as:
rule one, keeping the attributes of all the on-column switches consistent (model attribute checking);
rule two, graph model no island (graph connection relation check);
rule three, the feeder segments need to be compressed (compression rule).
Correspondingly, the verification views of different description angles can be obtained by compressing the data compression rules based on other data such as the disconnecting link, and equipment, containers or assets needing to be verified and attribute values thereof under the verification views compressed based on the disconnecting link are correspondingly selected as the verification rules.
Step 2: forward graph-modulo-error-free verification from model data to graph data
And performing forward graph mode differential checking from the model data to the graph data, determining whether to compress or abstract the model data according to a selected graph mode bidirectional differential checking rule, and searching and checking the graph data on the basis of the model data.
Classifying and processing the equipment data which does not exist in the model and exists in the graph according to the graph differentiation data class; defining and checking equipment data, container data and asset data which are all present in the model and the graph according to a checking rule, and classifying and processing partial data with different attributes or attribute values according to the graph model and common differential data; and defining and checking the equipment data, the container data and the asset data which are all present in the model and the graph according to a checking rule, wherein the equipment data, the container data and the asset data with the same attribute values can pass the checking and are classified into the graph model and share the same data.
The model topology is analyzed and simplified into internal topology structure data according to a Terminal-connectivity node connection mode in the CIM model, and then is compared and checked with the graph topology to form a topology differentiation data checking result. The graph topology is verified after being converted into internal topological structure data by adopting a GLink _ Ref topological connection relation on the graph data according to a defined graph rule, or verified after being analyzed by adopting a graph geometric connection relation and converted into the internal topological structure data. As shown in FIG. 6 below, forward modulo non-differential data verification verifies that the "# 12-4 feed line segment" and the "# 12-5 feed line segment" are not present in the model data but are present in the graphics data. Meanwhile, the existence of differential data of the two devices of station 921 and Baihong time 901 can be verified.
And step 3: inverse graph-model-error-free verification from graph data to model data
And searching and checking the model data based on the graph data according to the selected graph-mode bidirectional error-free checking rule from the graph data to the model data.
Classifying equipment which does not exist in the graph but exists in the model according to the differentiated data class of the model; defining and checking equipment data existing in both the graph and the model according to a check rule, and classifying and processing partial data with different attributes or attribute values according to differential data shared by the graph and the model; and the equipment data in both the graph and the model are checked according to the definition of the check rule, and the completely same equipment data can pass the check and are classified into the graph and the model which share the same data. As shown in fig. 6 below, the inverse graph model verifies that the "# 13 tie switch" is not present in the graph data but is present in the model data without differential data verification. Meanwhile, the existence of differential data of the two devices of station 921 and Baihong time 901 can be verified.
And after the reverse graph model is verified completely without difference, comparing the graph models of the two times to obtain common differential data, combining the same verification results, and finally forming a uniform graph model common differential data verification result.
And 4, step 4: graph-model bidirectional error-free check result output
In conclusion of the forward and reverse graphic mode checking steps, the forward checking result and the reverse checking result are integrated to form graphic differential data, model differential data, graphic mode common differential data and topology differential data, and the graphic mode common differential data and the topology differential data are classified according to the checking results and output to form an error report file. The error report file contents are as follows:
Claims (9)
1. a power distribution network graph-model bidirectional error-free verification method is characterized by comprising the steps of obtaining a model file and an image file, abstracting or compressing the model file with the minimum fine granularity according to different abstraction levels of the image file to obtain model data with N levels, carrying out image compression on the model data with N levels to obtain a verification view of appointed level model data, selecting a verification rule of the appointed level model data according to the verification view of the appointed level model data, and carrying out bidirectional N on the verification view of the appointed level model data and the model data corresponding to the verification view according to the verification rule of the appointed level model data: 1 consistency check, and N is an appointed level.
2. The method according to claim 1, wherein the rules for compressing the model data including N layers to obtain the verification view of the model data at the designated layer include, but are not limited to, a feeder segment compression rule, a disconnecting link compression rule, and a ground knife compression rule.
3. The power distribution network graph-model two-way error-free verification method according to claim 1, wherein the verification rules include model verification rules and graph verification rules, and the model verification rules include but are not limited to: the method comprises the following steps of model file format verification, model attribute value verification, model topology connection relation verification, model power supply point verification and model island verification, wherein a graph verification rule comprises but is not limited to: the method comprises the steps of graphic file format verification, graphic attribute value verification and graphic connection relation verification.
4. The distribution network graph-model bidirectional indifference verification method according to claim 1, wherein bidirectional N is performed on the verification view of the specified hierarchical model data and the model data corresponding to the verification view according to the verification rule of the specified hierarchical model data: 1, the consistency checking method comprises the following steps: and with the equipment in the model data of the Nth layer as a unit, searching the equipment in the verification view of the model data of the Nth layer, and according to the following steps of 1:1, comparing the equipment data one by a consistency check method.
5. The power distribution network graph-model two-way error-free verification method according to claim 4, wherein the 1: the consistency checking method specifically comprises the following steps:
the method comprises the steps of performing forward graph model verification from model topology to graph topology by taking model data as a reference, classifying equipment data which does not exist in the model and exists in the graph into graph differential data, classifying equipment data, container data and asset data which exist in the model and the graph but have differences in part of attributes or attribute values into graph model common differential data, and classifying the equipment data, the container data and the asset data which exist in the model and the graph and have the same attribute values into graph model common same data;
the method comprises the steps of carrying out reverse graph-mode verification from graph topology to model topology by taking graph data as a reference, classifying equipment which does not exist in a graph and exists in a model into model differential data, classifying equipment data which exists in the graph and the model but has difference in partial attributes or attribute values into graph-mode common differential data, and classifying equipment data which exists in the graph and the model but has the same attribute values into graph-mode common same data.
6. The distribution network graph-model two-way difference-free verification method according to claim 5, characterized in that after forward graph-model verification from model topology to graph topology is performed with model data as a reference, the model topology data and graph topology data of a verification view are compared to obtain a topology differentiation data verification result.
7. The distribution network graph-model two-way difference-free verification method according to claim 5, wherein the same verification result in the graph-model common differential data obtained by the forward graph-model verification and the reverse graph-model verification is combined to obtain a final graph-model common differential data verification result.
8. The graph-model bidirectional error-free verification method for the power distribution network according to claim 6, wherein the method for comparing the model topology data with the graph topology data of the verification view to obtain the verification result of the topology differentiation data comprises the following steps: the method comprises the steps of analyzing model topology according to a Terminal-connectivity node connection mode in a CIM model, then simplifying the model topology into internal topology structure data, converting the graph topology into the internal topology structure data according to graph rules and by adopting a GLink _ Ref topology connection relation on the graph data, and comparing the internal topology structure data obtained by simplifying the model topology with the internal topology structure data obtained by converting the graph topology.
9. The distribution network graph-model bidirectional error-free verification method according to any one of claims 1 to 8, wherein model data including N layers are subjected to graph compression according to different image compression rules to obtain verification views of different description angles of specified layer model data, a verification rule is selected according to the verification view of each description angle, and the verification view of each description angle and the model data corresponding to the verification view of each description angle are subjected to bidirectional N: 1 consistency check.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111134926.6A CN113870051A (en) | 2021-09-27 | 2021-09-27 | Graph-model bidirectional error-free calibration method for power distribution network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111134926.6A CN113870051A (en) | 2021-09-27 | 2021-09-27 | Graph-model bidirectional error-free calibration method for power distribution network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113870051A true CN113870051A (en) | 2021-12-31 |
Family
ID=78991116
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111134926.6A Pending CN113870051A (en) | 2021-09-27 | 2021-09-27 | Graph-model bidirectional error-free calibration method for power distribution network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113870051A (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012155494A1 (en) * | 2011-05-16 | 2012-11-22 | 河北省电力研究院 | Verifying method of optimal control parameter in whole network for automatic voltage control system |
| CN104951997A (en) * | 2015-05-21 | 2015-09-30 | 北京科东电力控制***有限责任公司 | Multidimensional graphic and model quality analysis method facing power distribution network |
| 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 |
| CN106951556A (en) * | 2017-03-30 | 2017-07-14 | 广东电网有限责任公司中山供电局 | The consistency desired result method and system of power distribution network artwork under offline environment |
| CN107591802A (en) * | 2017-09-15 | 2018-01-16 | 云南电网有限责任公司 | A kind of abstract method of calibration of distribution network model |
| CN107730123A (en) * | 2017-10-20 | 2018-02-23 | 国网江苏省电力公司南京供电公司 | A kind of consistent property check method of dispatching automation artwork |
| CN109165824A (en) * | 2018-08-07 | 2019-01-08 | 国网江苏省电力有限公司 | A kind of appraisal procedure and system for critical workflow |
| CN112580178A (en) * | 2020-12-26 | 2021-03-30 | 广东电网有限责任公司电力调度控制中心 | Graph-model bidirectional verification method and device for energy management system |
-
2021
- 2021-09-27 CN CN202111134926.6A patent/CN113870051A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012155494A1 (en) * | 2011-05-16 | 2012-11-22 | 河北省电力研究院 | Verifying method of optimal control parameter in whole network for automatic voltage control system |
| CN104951997A (en) * | 2015-05-21 | 2015-09-30 | 北京科东电力控制***有限责任公司 | Multidimensional graphic and model quality analysis method facing power distribution network |
| 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 |
| CN106951556A (en) * | 2017-03-30 | 2017-07-14 | 广东电网有限责任公司中山供电局 | The consistency desired result method and system of power distribution network artwork under offline environment |
| CN107591802A (en) * | 2017-09-15 | 2018-01-16 | 云南电网有限责任公司 | A kind of abstract method of calibration of distribution network model |
| CN107730123A (en) * | 2017-10-20 | 2018-02-23 | 国网江苏省电力公司南京供电公司 | A kind of consistent property check method of dispatching automation artwork |
| CN109165824A (en) * | 2018-08-07 | 2019-01-08 | 国网江苏省电力有限公司 | A kind of appraisal procedure and system for critical workflow |
| CN112580178A (en) * | 2020-12-26 | 2021-03-30 | 广东电网有限责任公司电力调度控制中心 | Graph-model bidirectional verification method and device for energy management system |
Non-Patent Citations (2)
| Title |
|---|
| 张帝;朱吉然;唐海国;张志丹;齐飞;冷华;: "基于配电网统一信息模型的全网一张图建设", 湖南电力, no. 02, 25 April 2020 (2020-04-25), pages 58 - 62 * |
| 陈连杰;韩冰;赵家庆;杜红卫;钱科军;欧阳文;: "利用自动成图的配电网模型拓扑校核技术及实现", 电力***自动化, no. 02, 25 January 2017 (2017-01-25), pages 166 - 170 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105787089B (en) | A kind of distribution network planning basic data integrated approach | |
| CN102521398B (en) | Modeling method for substation-dispatching center two-level distributed type power grid | |
| CN102622463B (en) | Drawing-model uniformity based method for automatic check of design drawings | |
| CN102750406B (en) | Multi-version management method for model set and difference model-based power grid model | |
| US10331156B2 (en) | System and method for big data geographic information system discovery | |
| CN109765447A (en) | A kind of intelligent substation relay protection automatic test approach | |
| CN107357970B (en) | Data mining-based building information model abnormal element detection device and method | |
| CN108270640B (en) | Information interoperation consistency test method for intelligent marketing and distribution information integration system | |
| CN112580178B (en) | Graph-model bidirectional verification method and device for energy management system | |
| CN111625964B (en) | Method, system and equipment for constructing transformer substation graph model based on logical relationship | |
| Kim et al. | QVT-based model transformation to support unification of IEC 61850 and IEC 61970 | |
| CN107591802A (en) | A kind of abstract method of calibration of distribution network model | |
| KR101397381B1 (en) | Method for integrating meta-modeling | |
| CN115329556A (en) | Transformer substation CAD drawing auditing method and device | |
| CN113870051A (en) | Graph-model bidirectional error-free calibration method for power distribution network | |
| CN111597166B (en) | Power database model construction method, device, computer equipment and storage medium | |
| CN108564261A (en) | Method, apparatus and computer equipment are determined based on the power information of work ticket | |
| CN109271350B (en) | Database and information point table automatic comparison and synchronization method based on telecontrol communication | |
| CN109710669A (en) | The method of raising full electric network model data accuracy based on verification rule base | |
| CN109933588A (en) | A kind of dwg data turn the method and system of gdb data | |
| Wang et al. | Research and implementation of virtual circuit test tool for smart substations | |
| CN112328538A (en) | PMS2.0 graph model file importing method | |
| Wu et al. | Distribution network topology modelling and automatic mapping based on CIM and GIS | |
| Ji et al. | A geospatial analysis framework for fine scale urban infrastructure networks | |
| CN109947867A (en) | Electric Power Network Planning data fusion method based on function support dimension |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |