CN114036699B

CN114036699B - Generalized non-electric power business modeling method for electric power Internet of things platform

Info

Publication number: CN114036699B
Application number: CN202111214509.2A
Authority: CN
Inventors: 宿磊; 沈煜; 杨帆; 杨志淳; 胡伟; 雷杨
Original assignee: Electric Power Research Institute of State Grid Hubei Electric Power Co Ltd
Current assignee: Electric Power Research Institute of State Grid Hubei Electric Power Co Ltd
Priority date: 2021-10-19
Filing date: 2021-10-19
Publication date: 2024-04-02
Anticipated expiration: 2041-10-19
Also published as: CN114036699A

Abstract

The present invention provides a generalized non-power business modeling method for an electric power Internet of Things platform, which includes: using a meta-node model editing module to create a meta-node model, where the meta-node model is a type of node with independent services at the same level; The node generation module implements node instantiation: count the nodes that need to be added in the entire site, add nodes through the node generation module interface, select the new node, enter the node description, select the meta-node model, click Generate, the system adds a node Node in the gallery. During the instantiation process, the system generates a node ID, which is the unique identifier of the node in the gallery; configures the node through the node configuration module; and uses the cross-model traversal algorithm to traverse the entire site model. Aiming at the electric power Internet of Things monitoring platform, the present invention solves the establishment and management problems of various non-electrical business models through a universal modeling method, and realizes the coexistence and integration of multiple models of the platform through a model interaction mechanism.

Description

Generalized non-electric power business modeling method for electric power Internet of things platform

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;

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

1. A generalized non-power business modeling method for a power Internet of Things platform, characterized by comprising the following steps:

S1: Use the meta-node model editing module to create a meta-node model. The meta-node model is a type of node that is independent of the same level of business;

S2: Node instantiation is realized through the node generation module. Count the nodes that need to be added in the whole site. Add nodes through the node generation module interface, select the new node, enter the node description, select the meta node model, click Generate, and the system adds a node Node to the library. During the instantiation process, the system generates a node ID, which is the unique identifier of this node in the library.

S3: Configure nodes through the node configuration module;

S4: Use the cross-model traversal algorithm to traverse the entire station model;

The creation process of the meta-node model includes:

S1.1. Divide business levels according to non-power services and determine meta-nodes at each level. The non-power services include electrical fire analysis. The principles for determining hierarchical meta-nodes are as follows:

1) Meta nodes at the same level have the same business content;

2) The business functions of each node are independent;

3) The hierarchical division is consistent with the human-machine interface logic or business logic;

S1.2. According to the business logic, determine the data elements of each level of meta-node, including data name, data type, and data unit, and edit the above data elements into a template file in XML format;

S1.3. The system imports the template files of each level meta-node model generated by S1.2 to generate the meta-node model;

Step S3 configures the node specifically including:

1) Data element mapping IED model

Perform IED_REF mapping on data elements one by one, filter the signals in the total site data table FCDA according to IEDname and FC type, and select the corresponding DA to map to the node instance table. Each data element can only be mapped to one IED_REF at most. Repeated mapping will Overwrite the original mapped reference;

2) Sibling node configuration

Configure the relationship between sibling nodes at the same level. Query all nodes at this level in the gallery node configuration table. In the sibling node entries associated with this node, multiple sibling node entries can be added. Each entry has a corresponding relationship identifier. The content of the logo is related to the specific business;

3) Parent node configuration

Configure the superior node. Query all superior nodes in the gallery node configuration table and associate them to the sibling node entries of this node. Only one parent node entry can be added;

4) External model association

Associate external model nodes related to this node. The external models include SSD model, IED model, and SPCD model;

By executing steps S1-S3, a many-to-many connectivity relationship is generated between multiple models. Each node association is weighted according to the relationship type to generate a weighted connectivity graph composed of multiple models. Step S4 specifically includes:

Use Prim's algorithm to traverse the weighted connected graph. The specific process is as follows:

1) Take the node as the vertex, the vertex set as V, and the edge set as E;

2) Initialize Vnew = {x}, where x is any node in the set V, Enew = {}, is empty;

3) Repeat the following operations until Vnew = V:

a. Select the edge <u, v> with the smallest weight in the set E, where u is an element in the set Vnew, and v is not in the set Vnew, and v∈V. If there are multiple edges that meet the above conditions, they have the same For the edges with weights, you can choose one of them arbitrarily;

b. Add v to the set Vnew, and add edges <u, v> to the set Enew;

4) Use the sets Vnew and Enew to describe the resulting minimum spanning tree to achieve cross-model traversal.

2. The generalized non-power business modeling method for the power Internet of Things platform according to claim 1, characterized in that: the meta-node model includes data description, parent node, sibling node, model association, and data association.