CN114036699B - Generalized non-electric power business modeling method for electric power Internet of things platform - Google Patents
Generalized non-electric power business modeling method for electric power Internet of things platform Download PDFInfo
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- G—PHYSICS
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- G06F30/00—Computer-aided design [CAD]
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- G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
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Abstract
The invention provides a generalized non-power business modeling method for an electric power internet of things platform, which comprises the following steps: creating a meta-node model by using a meta-node model editing module, wherein the meta-node model is a type of node with the same level and independent service; node instantiation is realized through a node generation module: counting nodes needing to be added in the total station, adding the nodes through a Node generation module interface, selecting newly added nodes, inputting Node description, selecting a meta Node model, clicking to generate, adding a Node in a gallery by a system, generating a Node ID by the system in an instantiation process, and uniquely identifying the Node ID in the gallery; configuring the nodes through a node configuration module; traversing the total station model using a cross-model traversal algorithm. Aiming at the electric power internet of things monitoring platform, the invention solves the problems of building and managing various non-electric service models through a general modeling method, and realizes coexistence and fusion among multiple models of the platform through a model interaction mechanism.
Description
Technical Field
The invention relates to the technical field of electric power Internet of things, in particular to a generalized non-electric power business modeling method for an electric power Internet of things platform.
Background
The power supply system has close relation with social production life, and for a monitoring platform combining power business with non-power business, a pure power monitoring platform lacks display of real business, and a common Internet of things platform lacks support of a power model.
The traditional power monitoring platform is based on standard modeling of IEC61850, IEC61970 and the like, focuses on the model description of an electrical principle, such as a primary part and a secondary part of a power system are respectively modeled through a substation and an IED part in an SCD model file of IEC61850, and secondary correlation is carried out in the substation part. The standard only models the service logic, and does not consider the physical model of the actual equipment, so that the corresponding relation between the physical optical fiber loop and the logic link of the process layer is lost, and great trouble is brought to the management and maintenance of the power equipment.
In order to solve the modeling problem, the electric power enterprises in China put forward an SPCD model for describing the physical characteristics of secondary equipment, network cables and optical fibers. However, the SPCD file can only be used as a supplement to the IED part of the SCD file, which is based on the description of the power model structure. The SPCD model is also frustrating when non-electrical services (e.g., electrical fire management, building structures) are required.
Modeling specific business for each project is a relatively reliable method, but the platform is too customized, so that a large amount of development resources are consumed, and the limitation of products is increased.
Disclosure of Invention
The invention provides a generalized non-electric service modeling method for an electric power Internet of things platform, which can be used for rapidly generating a plurality of non-electric service models according to project requirements and solving coexistence and interaction problems under a plurality of model systems, wherein the platform can select different model systems according to service requirements, so that the difficulty in processing the non-electric service caused by the fact that the platform is attached to a single electric model is avoided.
In order to solve the technical problems, the invention adopts the following technical scheme:
a generalized non-power business modeling method for an electric power Internet of things platform comprises the following steps:
s1: creating a meta-node model by using a meta-node model editing module, wherein the meta-node model is a type of node with the same level and independent service;
s2: implementing node instantiation through a node generation module
Counting nodes needing to be added in the total station, adding the nodes through a Node generation module interface, selecting newly added nodes, inputting Node description, selecting a meta Node model, clicking to generate, adding a Node in a gallery by a system, generating a Node ID by the system in an instantiation process, and uniquely identifying the Node ID in the gallery;
s3: configuring the nodes through a node configuration module;
s4: traversing the total station model using a cross-model traversal algorithm.
Further, the meta-node model comprises a data description, a father node, a brother node, a model association and a data association.
Further, the meta-node model creation process includes:
s1.1, dividing service levels according to services, and determining metanodes of each level, wherein the principle of determining hierarchical metanodes is as follows:
1) The metanodes of the same hierarchy have the same service content;
2) The service functions of all nodes are independent;
3) The hierarchy division is consistent with human-machine interface logic or business logic;
s1.2, determining data elements comprising data names, data types and data units of each level of meta-nodes according to business logic, editing the data elements into a template file, wherein the template file is in an xml format;
s1.3, the system imports the template file of each level meta-node model generated in the S1.2 to generate a meta-node model.
Further, the step S3 of configuring the node specifically includes:
1) Data element mapping IED model
Performing IED_REF mapping on the data elements one by one, screening signals in the total station data table FCDA according to IEDname and FC types, selecting corresponding DA to map to a node instance table, wherein each data element can only map one IED_REF at most, and repeating mapping to cover references of the original mapping;
2) Sibling node configuration
Configuring the relation between brother nodes of the same hierarchy, inquiring all nodes of the hierarchy in a gallery node configuration table, and adding a plurality of brother node entries in the brother node entries associated with the nodes, wherein each entry has a corresponding relation identifier, and the identifier content is related to a specific service;
3) Parent node configuration
Configuring upper nodes, inquiring all upper nodes in a gallery node configuration table, and adding only 1 father node item in the brother node item associated with the node;
4) External model association
An external model node is associated with the node, wherein the external model comprises an SSD model, an IED model and an SPCD model.
Further, by executing the step 1-3, a many-to-many communication relationship is generated between the multiple models, and each node association relationship is weighted according to the relationship type, so as to generate a weighted communication graph composed of multiple models, and the step S4 specifically includes:
traversing the weighted connected graph by using a Prim algorithm, wherein the specific process is as follows:
1) Taking nodes as vertexes, wherein a vertex set is V, and an edge set is E;
2) Initializing vnew= { x }, wherein x is any node in set V, and enew= { }, is null;
3) The following operations are repeated until vnew=v:
a. selecting an edge < u, V > with the smallest weight value from the set E, wherein u is an element in the set Vnew, V is not in the Vnew set, V is V, and if a plurality of edges meeting the conditions, namely having the same weight value exist, one of the edges can be selected at will;
b. adding v to the set Vnew, and adding < u, v > edges to the set engw;
4) The resulting minimum spanning tree is described using the sets Vnew and engw, enabling traversal across models.
According to the invention, the electric power Internet of things platform is allowed to establish a non-electric service model through an engineering means, so that the problem that the platform is too specialized and single in function is solved, and the platform can be widely used for projects related to electric power but with core services being dominant by the non-electric model; meanwhile, the invention uses standardized general engineering configuration means to replace the conventional developer modeling, realizes the standardization of the model structure, and greatly reduces the development workload of model design and modeling.
Drawings
FIG. 1 is a flow chart of one embodiment of a generalized non-power business modeling method for an electric networking platform of the present invention;
FIG. 2 is a schematic diagram of a metanode model generated in step S1 of the present invention;
FIG. 3 is a schematic diagram of a meta-node model generated by the present invention using room nodes as an example.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-3, an embodiment of the present invention provides a generalized non-power service modeling method for an electric power internet of things platform, taking building modeling for electric fire analysis as an example, specifically comprising the following steps:
s1: the method comprises the steps of creating a meta-node model by using a meta-node model editing module, wherein the meta-node model is a class of nodes with independent service at the same level, and comprises data description, father nodes, brother nodes, model association, data association and the like, and the creation flow is as follows:
s1.1, dividing service layers according to the service, and determining meta-nodes of each layer.
According to project requirements, a building model needs to be built to describe the spatial relationship in the building. The man-machine interface interactive design level is sequentially building-floor-room, and the fire algorithm is also related to the space taking the room as a unit. So the business hierarchy is divided and each hierarchy node is determined to be a building-floor-room in turn.
S1.2, determining data elements of each level of meta-nodes according to service logic, editing a template file, wherein the template file is in an xml format.
Taking a room meta-model as an example, as the business requirement can know, the required data elements of the room model are as follows: the switching position of the electrical equipment, the current, the voltage, the protection signal, the temperature and the smoke concentration of the room, and the fire monitoring area where the room belongs. The above signals are integrated into a template file named "room node. Xml".
S1.3, the system imports the template file generated in S1.2 to generate a meta-node model structure as shown in figure 3.
The room meta-node model infrastructure, as shown in FIG. 2, includes ID, description, model data, sibling, parent, external model associations. Wherein the data elements in the model data are generated by XML file importation and the values of the other content items are completed by later steps.
S2: node instantiation through a node generation module
Taking room node instantiation as an example, counting rooms needing to be added in the whole building, adding nodes through a node generation module interface, selecting newly added nodes, inputting node description as room numbers, and selecting a meta-node model as room meta-nodes. Clicking generation, the system adds a Node in the gallery, and in the process of instantiation, the system generates a Node ID, and the Node ID is the unique identification of the Node in the gallery.
S3: node configuration
The following configuration of the node is completed through the node configuration module:
1) Data element mapping IED model
The switch positions, currents, voltages, protection signals and temperatures of the room, smoke concentration signals, fire monitoring areas of the electrical equipment are taken from the IED model, the data elements under each node are selected in the interface, and IED references are added. Specifically, signals in the FCDA of the total station data table are filtered according to IEDname and FC types, the corresponding DA is selected to be mapped to the node instance table, each data element can only be mapped with one ied_ref at most, and repeated mapping covers the reference of the original mapping.
2) Sibling node configuration
Sibling nodes, here spatially adjacent, communicating rooms, are used for fire development process analysis. The relationship identifier 1 indicates that the spaces are adjacent and communicated, and the relationship identifier 2 indicates that the spaces are adjacent but not communicated.
And selecting room nodes to be configured, inquiring all the room nodes of the floor in a gallery node configuration table, manually selecting adjacent communicated room nodes, and setting a relation identifier for each brother node room according to the actual position condition in brother node entries associated with the nodes.
3) Parent node configuration
The parent node of the room node is the corresponding floor node, and the parent node of the floor node is the building node.
4) External model association
An external model association associates external model nodes associated with the node. In this example, the external model nodes that need to be associated are: an electrical device node in the SSD model, a portion of the IED nodes in the IED model; cable nodes in SPCD model.
S4: traversing a total station model using a cross-model traversal algorithm
And (3) generating a multi-to-many communication relation among the models by executing the steps (1-3), weighting the node association relation according to the relation type, and generating a weighted communication diagram consisting of multiple models.
According to a cross-model traversal algorithm, the spatial positions influenced by arc abnormality alarms of two LTU devices can be rapidly positioned, and then the fire position is positioned. The association relations are needed to be judged by combining the topological relation of the SSD model, the LTU equipment coordinates and signals of the IED model, the cable information of the SPCD model and the space position information of the building model.
Step S4, traversing the weighted connected graph by using a Prim algorithm, wherein the detailed method is as follows:
1) Taking nodes as vertexes, wherein a vertex set is V, and an edge set is E;
2) Initializing vnew= { x }, where x is any node (starting point) in set V, and engw= { }, is null;
3) The following operations are repeated until vnew=v:
a. selecting an edge < u, V > with the smallest weight value from the set E, wherein u is an element in the set Vnew, V is not in the Vnew set, and V epsilon V (if a plurality of edges meeting the condition, namely having the same weight value exist, one of the edges can be selected at will);
b. adding v to the set Vnew, and adding < u, v > edges to the set engw;
4) The resulting minimum spanning tree is described using the sets Vnew and engw, enabling traversal across models.
According to the invention, the electric power Internet of things platform is allowed to establish a non-electric service model through an engineering means, so that the problem that the platform is too specialized and single in function is solved, and the platform can be widely used for projects related to electric power but with core services being dominant by the non-electric model; meanwhile, the invention uses standardized general engineering configuration means to replace the conventional developer modeling, realizes the standardization of the model structure, and greatly reduces the development workload of model design and modeling.
The foregoing is merely illustrative embodiments of the present invention, and the present invention is not limited thereto, and any changes or substitutions that may be easily contemplated by those skilled in the art within the scope of the present invention should be included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (2)
1. A generalized non-electric power business modeling method for an electric power Internet of things platform is characterized by comprising the following steps of: the method comprises the following steps:
s1: creating a meta-node model by using a meta-node model editing module, wherein the meta-node model is a type of node with the same level and independent service;
s2: the method comprises the steps of realizing Node instantiation and counting nodes needing to be added in a total station through a Node generation module, adding the nodes through a Node generation module interface, selecting newly added nodes, inputting Node description, selecting a meta Node model, clicking to generate, adding a Node in a gallery by a system, generating a Node ID by the system in the instantiation process, wherein the Node ID is the unique identifier of the Node in the gallery;
s3: configuring the nodes through a node configuration module;
s4: traversing the total station model by using a cross-model traversal algorithm;
the meta-node model creation flow includes:
s1.1, dividing service levels according to non-electric service, and determining metanodes of each level, wherein the non-electric service comprises electric fire analysis, and the principle of determining the hierarchical metanodes is as follows:
1) The metanodes of the same hierarchy have the same service content;
2) The service functions of all nodes are independent;
3) The hierarchy division is consistent with human-machine interface logic or business logic;
s1.2, determining data elements comprising data names, data types and data units of each level of meta-nodes according to business logic, editing the data elements into a template file, wherein the template file is in an xml format;
s1.3, the system imports the template file of each level meta-node model generated in the S1.2 to generate a meta-node model;
the step S3 of configuring the node specifically includes:
1) Data element mapping IED model
Performing IED_REF mapping on the data elements one by one, screening signals in the total station data table FCDA according to IEDname and FC types, selecting corresponding DA to map to a node instance table, wherein each data element can only map one IED_REF at most, and repeating mapping to cover references of the original mapping;
2) Sibling node configuration
Configuring the relation between brother nodes of the same hierarchy, inquiring all nodes of the hierarchy in a gallery node configuration table, and adding a plurality of brother node entries in the brother node entries associated with the nodes, wherein each entry has a corresponding relation identifier, and the identifier content is related to a specific service;
3) Parent node configuration
Configuring upper nodes, inquiring all upper nodes in a gallery node configuration table, and adding only 1 father node item in the brother node item associated with the node;
4) External model association
Associating external model nodes related to the node, wherein the external model comprises an SSD model, an IED model and an SPCD model;
by executing the steps S1-S3, a many-to-many communication relation is generated among the models, the association relation of each node is weighted according to the relation type, and a weighted communication diagram composed of multiple models is generated, and the step S4 specifically comprises the following steps:
traversing the weighted connected graph by using a Prim algorithm, wherein the specific process is as follows:
1) Taking nodes as vertexes, wherein a vertex set is V, and an edge set is E;
2) Initializing vnew= { x }, wherein x is any node in set V, and enew= { }, is null;
3) The following operations are repeated until vnew=v:
a. selecting an edge < u, V > with the smallest weight value from the set E, wherein u is an element in the set Vnew, V is not in the Vnew set, V is V, and if a plurality of edges meeting the conditions, namely having the same weight value exist, one of the edges can be selected at will;
b. adding v to the set Vnew, and adding < u, v > edges to the set engw;
4) The resulting minimum spanning tree is described using the sets Vnew and engw, enabling traversal across models.
2. The generalized non-power business modeling method for an electric power internet of things platform of claim 1, wherein: the meta-node model comprises a data description, a father node, a brother node, a model association and a data association.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106530114A (en) * | 2016-09-22 | 2017-03-22 | 厦门亿力吉奥信息科技有限公司 | Power grid equipment monitoring method and system |
| CN110190984A (en) * | 2019-04-29 | 2019-08-30 | 中国电力科学研究院有限公司 | A kind of efficient power communication system large scale emulation scene modeling method and system |
| CN112765134A (en) * | 2020-12-29 | 2021-05-07 | 广东电网有限责任公司电力科学研究院 | Generation method and system of electric power internet of things level object model |
| CN113488996A (en) * | 2021-07-02 | 2021-10-08 | 国网湖北省电力有限公司电力科学研究院 | Power distribution network protogram modeling method based on distributed parallel graph computing framework |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7392258B2 (en) * | 2005-02-25 | 2008-06-24 | International Business Machines Corporation | Method and computer program product for dynamic weighting of an ontological data model |
-
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- 2021-10-19 CN CN202111214509.2A patent/CN114036699B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106530114A (en) * | 2016-09-22 | 2017-03-22 | 厦门亿力吉奥信息科技有限公司 | Power grid equipment monitoring method and system |
| CN110190984A (en) * | 2019-04-29 | 2019-08-30 | 中国电力科学研究院有限公司 | A kind of efficient power communication system large scale emulation scene modeling method and system |
| CN112765134A (en) * | 2020-12-29 | 2021-05-07 | 广东电网有限责任公司电力科学研究院 | Generation method and system of electric power internet of things level object model |
| CN113488996A (en) * | 2021-07-02 | 2021-10-08 | 国网湖北省电力有限公司电力科学研究院 | Power distribution network protogram modeling method based on distributed parallel graph computing framework |
Non-Patent Citations (3)
| Title |
|---|
| 基于图数据库的TDM系统设计与实现;钱俊松等;软件导刊;20180930;第196-199页 * |
| 基于物联网技术的电气火灾监控系统的设计与实现;牛瑞丽;中国优秀博硕士学位论文全文数据库(硕士);20210515;第1-75页 * |
| 面向物联网的电气火灾监控系统;张征峰;中国优秀博硕士学位论文全文数据库(硕士);20210115;第1-76页 * |
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