CN111190955B - Management, distribution and dispatching through checking method based on knowledge graph - Google Patents
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Abstract
The invention discloses a marketing, distribution and dispatching through checking method based on a knowledge graph, which comprises the steps of calling a plurality of data based on marketing and distribution data through, and establishing a plurality of net rack topologies for the same type of data; fusing a plurality of network topologies, and displaying any change in the plurality of network topologies in a knowledge graph mode; and sending the updated data to the network topology, and generating a new network frame topology. The invention performs fusion comparison of operation, distribution and dispatching network frame topology, and intelligently identifies cross-professional and cross-system network frame difference, thereby checking operation, distribution and dispatching through result quality and improving matching and through efficiency.
Description
Technical Field
The invention belongs to the technical field of power grids, and particularly relates to a marketing, distribution and dispatching through checking method based on a knowledge graph.
Background
The electric power marketing and distribution data link is a marketing and distribution data integration platform based on a GIS, namely, the data integration management of a marketing business application system, a production management information system and a power grid geographic space information service platform. The comprehensive correspondence and sharing of the production data and the marketing client data can achieve the communication of marketing and distribution data and services by means of application integration and graphical display, and the services such as fault location, power failure range analysis, line loss statistics and business expansion and installation are achieved.
Due to different standards and service attention of marketing, operation and inspection, and scheduling (operation, distribution and dispatching) systems to the grid structure, data are isolated and non-uniform, so that the relation between the grid files and the files in a single system is wrong, the consistency and the relation between the grid files of the cross-system are wrong, each service system lacks the standard of a unified grid topological structure, the data are difficult to share and fuse among the cross-service, and the data value is difficult to effectively improve. The operation and distribution through achievements are crossed across the professional and system service boundaries, the data is not acknowledged, and synchronous updating and effective positioning of network frame differences are lacked. Meanwhile, the original grid structure has the problems of poor expansibility, slow modification response, high maintenance cost and the like.
The existing marketing, distribution and dispatching are mainly carried out by means of manual identification and matching, the matching efficiency is not high, and the accuracy is low. Meanwhile, manpower and material resources are continuously input to check the through achievements, and an intelligent and convenient through checking means is lacked. One of the systems monitors the PMS2.0 system, the data center system, the marketing service application system, the basic data platform system and the data flow transfer process among the systems in real time to generate data of data flow transfer monitoring results; determining the abnormal problem of the data flow monitoring result data according to the data flow monitoring result data, and positioning the abnormal problem of the data flow monitoring result data; performing base quantity data analysis, integrity analysis, consistency analysis and service protocol analysis on the abnormal problems of the data flow monitoring result data, performing problem classification on the abnormal problems of the data flow monitoring result data, and generating abnormal problem attribution classification results; and determining a processing object of the abnormal problems of the data of each data flow monitoring result according to the attribution classification results of the abnormal problems and the preset problem processing corresponding relation. The method is based on monitoring and checking of data flow, and the relevance degree of the method and the actual service is reduced. Because the power grid network frame is not used as a basis, abnormal data or problems cannot be found at the first time, and then consistency and normative verification of marketing, distribution and dispatching through data are not deep enough to support the requirement of current power grid enterprises on marketing, distribution and dispatching through results.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a marketing, distribution and dispatching through checking method based on the knowledge graph aiming at the defects in the prior art, fusion and comparison of marketing, distribution and dispatching network frame topologies are carried out, and cross-professional and cross-system network frame differences are intelligently identified, so that marketing, distribution and dispatching through result quality is checked, and matching and through efficiency is improved.
The invention adopts the following technical scheme:
a marketing, distribution and dispatching through checking method based on a knowledge graph comprises the following steps:
s1, calling a plurality of data based on marketing and distribution data link, combining the relationship between the data and the data, and connecting station-line-change-user files in series according to a physical topological structure mode to establish a plurality of network frame topologies;
s2, fusing the plurality of network topologies, and displaying any change in the plurality of network topologies in a knowledge graph mode;
and S3, sending the updated data to a network topology to generate a new network frame topology.
Specifically, in step S1, the marketing data includes marketing data, operation and inspection data, and scheduling data.
Specifically, in step S1, a power grid network structure topology for marketing, operation and inspection, and scheduling is respectively constructed in a network hierarchical structure form in combination with the station-line-change-user relationship of the power grid network structure topology.
Specifically, in step S1, a plurality of network topologies are managed by the network topology management module, including generation of the network topologies and fusion of the network topologies.
Specifically, in step S2, consistency comparison and difference identification analysis are performed on the grid topology structures of the multiple systems by using a knowledge map and a machine learning technology, and cross-system grid topology node association is identified based on uniqueness and association of a physical grid structure of the power grid, so that grid topology fusion of the multiple systems is realized.
Furthermore, the data of the related service is compared with the data stored in the network topology, and if the data stored in the network topology is abnormal, the network topology is automatically checked and corrected.
Furthermore, automatic verification and correction of the network frame topology are achieved in an auxiliary mode through identification and difference analysis of voltage, line loss and three-phase unbalanced operation data.
Specifically, in step S2, for the information of the newly added node and the abnormal node, the address and the basic attribute of the user information are analyzed and compared in combination with the recorded information of the power grid infrastructure and the business expansion, and the topology of the grid is updated for the approved data according to the business and file association relationship.
Specifically, data combing and data cleaning are performed before the calling in step S1.
Further, the data combing comprises combing out basic archive data of marketing, operation and inspection and dispatching systems; and the data cleaning comprises the step of removing invalid data and repeated data after the data are combed.
Compared with the prior art, the invention at least has the following beneficial effects:
the invention relates to an operation, distribution and dispatching through checking method based on a knowledge graph, which is characterized in that a professional grid topology is constructed based on marketing, operation and inspection and a dispatching system basic file respectively by applying a knowledge graph technology, so that the operation, distribution and dispatching grid topology is constructed; by applying a graph computing technology, marketing, operation and inspection and scheduling grid topology fusion are realized, operation, allocation and scheduling communication are quickly realized, and grid topology fusion is realized; automatically identifying the change of the file information and the topological relation of the net rack, and displaying the changing condition on the net rack topology in a knowledge map mode to realize dynamic intelligent identification of the net rack; by analyzing and mining the big data of the related business, such as analyzing and predicting abnormal electric quantity data, the automatic verification and correction of the net rack topology are realized, and the big data difference analysis is realized.
Furthermore, by combining the service change of the power grid operation and the generated operation data, such as the data analysis results of the change of the basic file, the abnormal electric quantity, the abnormal line loss and the like, the abnormal node and the abnormal reason in the fusion grid are identified and used as the basis for updating the topology structure of the fusion grid.
In conclusion, the invention performs fusion comparison of operation, distribution and dispatching network frame topologies, and intelligently identifies cross-professional and cross-system network frame differences, thereby verifying operation, distribution and dispatching through result quality and improving matching and through efficiency.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 is a functional block diagram of the present invention;
fig. 2 is a schematic diagram of the operation of the embodiment of the present invention.
Detailed Description
Referring to fig. 1, the invention relates to a marketing, distribution and dispatching through checking method based on a knowledge graph, which includes the following steps:
s1, calling a plurality of data based on marketing and distribution data link-up, combining the relationship between the data and the data, and connecting 'station-line-variant-user' files in series according to a physical topological structure mode to form a network frame topology of a single system;
marketing and distribution data link-through includes, but is not limited to, marketing data, shipping and inspection data, and scheduling data; the power grid network structure topology for marketing, operation and inspection and scheduling is respectively constructed in a network hierarchical structure mode by combining the 'station-line-variable-user' relationship of the power grid network structure topology.
The plurality of network topologies are managed through a network topology management module, and the management comprises the generation of the network topologies and the fusion of the network topologies.
And establishing a plurality of net rack topologies aiming at homogeneous data.
In a preferred embodiment of the invention, before calling a plurality of data in the marketing and distribution data through, the method further comprises data combing and data cleaning; the data combing comprises combing out basic archive data of marketing, operation and inspection and dispatching systems; and the data cleaning comprises the step of removing invalid data and repeated data after the data are combed.
S2, fusing the plurality of network topologies, and displaying any change in the plurality of network topologies in a knowledge graph mode;
consistency comparison and difference recognition analysis are carried out on the grid topological structures of the systems by using a knowledge map and a machine learning technology, and cross-system grid topological node association is recognized based on uniqueness and association of a physical grid network structure, so that grid topological fusion of the systems is realized.
Specifically, by combining the service change of the power grid operation and the generated operation data, such as the data analysis results of the change of the basic file, the abnormal electric quantity, the abnormal line loss and the like, the abnormal node and the abnormal reason in the fusion grid are identified and used as the basis for updating the topology structure of the fusion grid.
And for the information of the newly added nodes and the abnormal nodes, the record information of power grid infrastructure, business expansion new installation and the like is combined, the basic attributes such as addresses, user information and the like are analyzed and compared, reference basis is provided for a service manager to determine correct nodes and check, and the network frame topology is updated according to the association relation between services and files for the data passing the check.
In a preferred embodiment of the present invention, the data of the related service is compared with the data stored in the network topology, and if the data stored in the network topology is abnormal, the network topology is automatically checked and corrected.
The automatic verification and correction of the network frame topology are realized by depending on the analysis of relevant service data such as power grid operation data, for example: three users B, C and D are connected to the distribution transformer A in the marketing system; in the operation detection PMS system, two users B and C are connected to the lower portion of a distribution transformer A, and a user D is connected to the lower portion of a transformer E in a hanging mode. In the analysis process, the electricity generated by the distribution transformer A in the marketing and operation and inspection system in the month is 500KW.h, and the total electricity of the three users B, C and D is 500KW.h, so that the fact that the three users B, C and D are actually connected to the distribution transformer A can be judged, and the file data and the topological structure of the operation and inspection PMS system can be corrected by reference.
Similarly, automatic verification and correction of the network frame topology can be assisted through identification and difference analysis of operation data such as voltage, line loss and three-phase imbalance.
And S3, sending the updated data to a network topology to generate a new network frame topology.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
Example 1
As shown in fig. 2, the framework process of the knowledge graph-based marketing, distribution and dispatching through checking method comprises five steps of data acquisition, net rack topology construction, net rack topology fusion, net rack dynamic identification and big data difference analysis.
The specific process is as follows:
(1) Data acquisition
Data combing: and combing a required data list according to the power grid network frame topology construction range and the data requirements, wherein the required data list mainly comprises basic archive data of marketing, operation and inspection and scheduling systems.
Interface development: and according to the data integration frequency requirement, data synchronization replication technologies such as ETL and OGG are selected for data integration acquisition.
Data cleaning: and (4) according to the requirements of the power grid network frame topology construction on the data, carrying out data cleaning, and providing invalid data and repeated data.
(2) Net rack topology construction
And respectively constructing the power grid network structure topology of marketing, operation and inspection and dispatching in a network hierarchical structure form by combining the 'station-line-variable-user' relationship of the power grid network structure topology. And determining knowledge graph display levels (station-line-variable-household relation, parent-child node relation) according to the service logic and the basic archive logic relation, and constructing the power grid network frame topology by specialties.
(3) Net rack topology fusion
The network frame topology of marketing, operation and inspection and scheduling specialities utilizes technologies such as knowledge maps and machine learning to carry out consistency comparison and difference identification analysis on the network frame structure, and cross-system network frame topology node association is identified based on uniqueness and association of a physical network frame structure of a power grid. Directly matching nodes with higher consistency and accuracy; and for the parts with differences, classifying the data according to the difference problems, such as abnormal file association relation, irregular file naming, inconsistent file attributes and the like, and checking and rectifying basic files in a targeted manner, so that the network frame topology fusion of a plurality of systems is realized.
And (4) fusing the topology maps of the marketing, operation and inspection and scheduling professional net racks, and directly matching nodes with higher consistency and accuracy.
And for the parts with the difference, classifying the data according to the difference problem, and checking and correcting the basic file in a targeted manner.
(4) Dynamic identification of net rack
With business expansion and operation maintenance, the grid structure of the power grid is continuously changed, new grid structure topology is periodically generated by acquiring basic file change data of marketing, operation and inspection and scheduling, and the grid structure topology of new and old versions is compared by using map snapshots, so that dynamic grid structure topology difference identification is realized. For the difference part, the accuracy of the map structure is verified through data information such as material purchase, capital construction, new industry expansion and the like, and the normalization and the consistency of the management of each professional basic file are further improved by combining a manual checking mode.
The secondary check of the accuracy of the check map structure further promotes the standardization and consistency of the basic file management of each specialty.
(5) Big data difference analysis
And by combining professional services such as electric quantity data, monitoring and analyzing by using a marketing and distribution network frame topology, alarming for abnormity of the network frame topology according to network frame consistency and normalization problems found in the analysis process, and copying and improving the accuracy of the network frame topology.
In conclusion, by combining professional services such as electric quantity data, marketing, distribution and dispatching are applied to run through the net rack topology for monitoring and analysis, abnormal alarms are given on the net rack topology for the problems of consistency and normalization of the net rack found in the analysis process, and the accuracy of the net rack topology is copied and improved.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. A marketing, distribution and dispatching through checking method based on a knowledge graph is characterized by comprising the following steps:
s1, calling a plurality of data based on marketing and distribution data link, combining the relationship between the data and the data, and connecting station-line-change-user files in series according to a physical topological structure mode to establish a plurality of network frame topologies;
s2, fusing a plurality of network topologies, and displaying any change in the plurality of network topologies in a knowledge graph mode;
and S3, sending the updated data to a network topology to generate a new network frame topology.
2. The method for checking marketing and distribution based on knowledge-graph according to claim 1, wherein in step S1, the marketing and distribution data link comprises marketing data, operation and inspection data and scheduling data.
3. The knowledge-graph-based marketing, distribution and dispatching through checking method according to claim 1, wherein in the step S1, a power grid network structure topology for marketing, operation and dispatching is respectively constructed in a network hierarchical structure form by combining station-line-to-user relations of the power grid network structure topology.
4. The knowledge-graph-based marketing, distribution and dispatching continuity check method according to claim 1, wherein in step S1, a plurality of network topologies are managed by a network topology management module, including generation of the network topologies and fusion of the network topologies.
5. The knowledge-graph-based marketing, distribution and dispatching through checking method according to claim 1, wherein in step S2, a knowledge graph and a machine learning technology are used for performing consistency comparison and difference identification analysis on grid topological structures of a plurality of systems, and cross-system grid topological node association is identified based on uniqueness and association of a physical grid topological structure, so that grid topological fusion of the plurality of systems is realized.
6. The knowledge graph-based marketing, distribution and dispatching through inspection method as claimed in claim 5, wherein the data of the related services are compared with the data stored in the network topology, and if the data stored in the network topology is abnormal, the network topology is automatically checked and corrected.
7. The knowledge-graph-based marketing, distribution and dispatching through checking method according to claim 6, wherein automatic verification and correction of the network frame topology are assisted through identification and difference analysis of voltage, line loss and three-phase unbalanced operation data.
8. The method for verifying operation, distribution and dispatching based on a knowledge graph as claimed in claim 1, wherein in step S2, for the information of newly added nodes and abnormal nodes, the recorded information of power grid infrastructure and business expansion is combined, the address and the basic attribute of user information are analyzed and compared, and the topology of the grid frame is updated according to the association relationship between business and files for the data passing the verification.
9. The knowledge-graph-based marketing, distribution and dispatching breakthrough checking method according to claim 1, characterized in that data combing and data cleaning are performed before calling in step S1.
10. The knowledge-graph-based marketing, distribution and dispatching through-verification method according to claim 9, wherein the data combing comprises combing out basic archive data of marketing, transportation and dispatching systems; and the data cleaning comprises the step of removing invalid data and repeated data after the data are combed.
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| CN112134277B (en) * | 2020-09-22 | 2021-08-24 | 北京科东电力控制系统有限责任公司 | Power grid topology optimization checking method and system based on full-grid marketing and distribution multi-source data |
| CN112732924A (en) * | 2020-12-04 | 2021-04-30 | 国网安徽省电力有限公司 | Power grid data asset management system and method based on knowledge graph |
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