CN112905726A

CN112905726A - Modeling analysis method and network model updating method for equipment management network

Info

Publication number: CN112905726A
Application number: CN202110174547.3A
Authority: CN
Inventors: 陈龙雨
Original assignee: Individual
Current assignee: Individual
Priority date: 2021-02-08
Filing date: 2021-02-08
Publication date: 2021-06-04
Anticipated expiration: 2041-02-08
Also published as: CN112905726B; WO2022166562A1; CA3207585A1

Abstract

A modeling analysis method, a network model updating method and a working range analysis method for a device management network are provided. The modeling analysis method comprises the following steps: acquiring the position information, the type information and the state information of the physical node through a user terminal, wherein the acquisition is realized through user input, a positioning function of the user terminal or through photographing of the user terminal and automatic identification of the position information, the type information and the state information of the physical node; based on the position information and the type information of the physical nodes, automatically constructing a physical layer model according to a first preset rule so as to automatically connect the physical nodes into a line, and automatically displaying the physical nodes and the line between the physical nodes at corresponding positions by taking an electronic map as a background; and automatically constructing a logic layer model according to a second preset rule based on the type information and the state information of the physical node so as to construct a network model. The method can automatically construct the network model for rapid analysis, so that a user can quickly and automatically view the network graph and the network analysis result in real time.

Description

Modeling analysis method and network model updating method for equipment management network

Technical Field

The embodiment of the disclosure relates to a modeling analysis method, a working range analysis method, a network model updating method, a user terminal and a network server for a device management network.

Background

With the rapid development of information technology, simulating the operation rules of various systems in the existing society by a simulation modeling method becomes an important means for improving the management efficiency. In a device management network operating in real life, whether physical connection between devices or logical connection between devices reflects a rule of operation of the devices. Therefore, through the analysis of various devices in the system, the automatic modeling of the corresponding network model and the analysis based on the network model can be completed.

Disclosure of Invention

At least one embodiment of the present disclosure provides a modeling analysis method for a device management network, which is applied to a user terminal, and the method includes: acquiring the position information, the type information and the state information of a physical node through the user terminal, wherein the acquisition is realized through user input, a positioning function of the user terminal or photographing through the user terminal and automatically identifying the position information, the type information and the state information of the physical node; based on the position information and the type information of the physical nodes, automatically constructing a physical layer model according to a first preset rule so as to automatically connect the physical nodes into a line, and automatically displaying the physical nodes and the line between the physical nodes at corresponding positions by taking an electronic map as a background; and automatically constructing a logic layer model according to a second preset rule based on the type information and the state information of the physical node so as to construct a network model.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, automatically constructing a physical layer model according to a first predetermined rule based on location information and type information of the physical node includes: when the position information and/or the type information of the physical node are/is changed through the user terminal, based on the changed information, the line which does not accord with the first preset rule in the original line is automatically disconnected by taking the electronic map as the background, and the line is automatically connected between the changed physical node and the adjacent physical node thereof according to the first preset rule.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, automatically constructing a physical layer model according to a first predetermined rule based on location information and type information of the physical node includes: and responding to the collected position information and type information of the physical node while the user terminal keeps moving, and displaying the physical node and the automatically generated line between the physical node and the adjacent physical node in real time.

For example, at least one embodiment of the present disclosure provides a modeling analysis method further including: acquiring position information of an additional node, and acquiring type information and state information of the additional node; building an additional layer model for extending the network model based on the location information, type information, and state information of the additional node; and automatically displaying the type information and the state information of the additional node at a corresponding position by taking the electronic map as a background.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, automatically constructing the logical layer model according to the second predetermined rule based on the type information and the state information of the physical node includes: determining, as a logical node, a physical node satisfying a first predetermined condition among the physical nodes displayed on the electronic map based on the type information and the state information of the physical nodes; and identifying the type and the state of the logic nodes, and automatically establishing the topological relation among the logic nodes according to the second preset rule.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, the building of the physical layer model and the logical layer model is performed synchronously.

For example, at least one embodiment of the present disclosure provides a modeling analysis method further including: and automatically displaying the trend of the signals or the fluid in the equipment management network on the electronic map according to the topological relation among the logic nodes in the logic layer model.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, displaying a trend of a signal or a fluid in the device management network on the electronic map includes: on the electronic map, the trend of the signals or fluids in the equipment management network is displayed by using lines with arrows.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, the equipment management network is a power grid management network, and the trend of the signal or fluid in the equipment management network is a power supply direction in the power grid management network.

For example, at least one embodiment of the present disclosure provides a modeling analysis method further including: and displaying the simulation analysis result in response to the analysis function in the scene interface being triggered.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, in response to an analysis function in a scene interface being triggered, a simulation analysis result is displayed, including: and displaying the simulation analysis result through the color change of the control line in response to the fact that the analysis function in the scene interface is triggered.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, the displaying of the simulation analysis result is automatically performed by the user terminal on-line in real time in response to an analysis function in a scene interface being triggered.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, the user terminal acquiring location information, type information, and status information of a physical node is performed online in real time through a mobile internet.

At least one embodiment of the present disclosure further provides a device management network according to the modeling analysis method, where the device management network is a power grid management network, and the method includes: collecting position information, type information and state information of power grid equipment through a user terminal, wherein the collection comprises the steps of photographing through the user input and the positioning function of the user terminal or through the user terminal and automatically identifying the position information, the type information and the state information of the power grid equipment; automatically constructing a physical layer model according to a first preset rule based on the position information and the type information of the power grid equipment so as to automatically connect the power grid equipment into a line, and automatically displaying the power grid equipment and the line between the power grid equipment at a corresponding position by taking an electronic map as a background; based on the type information and the state information of the power grid equipment, automatically constructing a logic layer model according to a second preset rule so as to construct a network model; and responding to the triggering of the power failure analysis function in the scene interface, and displaying the power failure analysis result.

At least one embodiment of the present disclosure further provides a modeling analysis method for a device management network, applied to a simulation analysis server, the method including: receiving position information, type information and state information of a physical node; based on the position information and the type information of the physical nodes, automatically constructing a physical layer model according to a first preset rule so as to automatically connect the physical nodes into a line, wherein the physical layer model is used for automatically displaying the physical nodes and the line between the physical nodes on corresponding positions by taking an electronic map as a background; based on the type information and the state information of the physical nodes, automatically constructing a logic layer model according to a second preset rule so as to construct a network model; in response to receiving the request data, a simulation analysis result is generated.

For example, at least one embodiment of the present disclosure provides a modeling analysis method, further including: receiving the position information, the type information and the state information of the physical node from a user terminal so as to construct the network model at the simulation analysis server side; and sending the simulation analysis result to the user terminal.

For example, in a modeling analysis method provided in at least one embodiment of the present disclosure, receiving location information, type information, and state information of the physical node from a user terminal includes: receiving location information, type information and state information of the physical node from a user terminal through a mobile internet; and sending the simulation analysis result to the user terminal, including: and sending the simulation analysis result to the user terminal through the mobile internet.

At least one embodiment of the present disclosure further provides a working range analysis method according to the modeling analysis method, including: analyzing a working line corresponding to the physical node in the network model based on the network model consisting of the physical node and the line; and automatically connecting each tail end node of the working line, and forming a closed area corresponding to the physical node on the electronic map according to a third preset rule, wherein the closed area is a working range corresponding to the physical node.

For example, a working range analysis method provided in at least one embodiment of the present disclosure further includes: and sending information to a user in a working range corresponding to the physical node, wherein the information at least comprises pictures and characters.

For example, in the working range analysis method provided by at least one embodiment of the present disclosure, sending information to a user in a working range corresponding to the physical node includes sending information to a user in a working range corresponding to the physical node in response to a failure of the physical node, where the information includes a failed line name, a failure range, and estimated failure processing time.

At least one embodiment of the present disclosure further provides a network model updating method, including: dividing the electronic map into a plurality of areas; in the network updating process, when node information of different contents in the same area is received from a plurality of user terminals, a corresponding network model is respectively generated for each of the user terminals to form a plurality of network models; based on a second preset condition, selecting one network model from the multiple network models, and saving the network model in a layer mode to serve as a submission layer corresponding to the current time; and when the number of the saved submitted layers reaches a threshold value or a preset time is set to the first submitted layer, selecting one submitted layer from the plurality of submitted layers as a time layer for updating the network model based on a third preset condition.

For example, in a network model updating method provided by at least one embodiment of the present disclosure, the second predetermined condition and the third predetermined condition include at least one of the following: the network model comprises the maximum number of physical nodes; the area of a map region included in the network model is maximum; the map route included in the network model is longest; the network model includes the most types of physical nodes.

For example, at least one embodiment of the present disclosure provides a network model updating method, in which the network model includes a road network model.

At least one embodiment of the present disclosure further provides a user terminal, including a memory and a processor, where the memory stores instructions, and the processor, when executing the instructions, causes the user terminal to execute the method described above.

At least one embodiment of the present disclosure further provides a network server, including a memory and a processor, where the memory stores instructions, and the processor, when executing the instructions, causes the network server to execute the above method.

Drawings

To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments will be briefly described below, and it should be apparent that the drawings described below only relate to some embodiments of the present disclosure and are not limiting on the present disclosure.

Fig. 1 is a schematic diagram of a system simulation provided in at least one embodiment of the present disclosure;

fig. 2 is an architecture diagram of a device management system according to at least one embodiment of the present disclosure;

fig. 3 is a flow chart of a modeling analysis method for a device management network according to at least one embodiment of the present disclosure;

fig. 4 is a schematic diagram of a physical layer model of a power grid according to at least one embodiment of the present disclosure;

fig. 5 is a flowchart corresponding to step S103 in a modeling analysis method according to at least one embodiment of the disclosure;

fig. 6 is a schematic diagram illustrating a power grid logic layer model according to at least one embodiment of the present disclosure;

fig. 7 is a schematic diagram of an additional layer model of a power grid according to at least one embodiment of the present disclosure;

FIG. 8A illustrates a system architecture hierarchy diagram provided by at least one embodiment of the present disclosure;

FIG. 8B illustrates a simulation system model diagram provided by at least one embodiment of the present disclosure;

fig. 8C illustrates a diagram of a power grid system provided by at least one embodiment of the present disclosure;

fig. 9A is a schematic diagram of a dual power supply provided in at least one embodiment of the present disclosure;

fig. 9B is a schematic diagram of a dual power supply conversion provided in at least one embodiment of the present disclosure;

fig. 10 is a schematic diagram of grid fault location provided by at least one embodiment of the present disclosure;

fig. 11 is a power supply range analysis diagram provided by at least one embodiment of the present disclosure.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described below clearly and completely with reference to the accompanying drawings. It is to be understood that the described embodiments are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the disclosure without any inventive step, are within the scope of protection of the disclosure.

Unless otherwise defined, technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this disclosure belongs. The use of "first," "second," and similar terms in this disclosure is not intended to indicate any order, quantity, or importance, but rather is used to distinguish one element from another. Also, the use of the terms "a," "an," or "the" and similar referents do not denote a limitation of quantity, but rather denote the presence of at least one. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.

In general, a modeling method for a device management network is often limited to devices in the network, and the establishment of a network model is limited to devices directly constituting the network, and cannot consider a relevant factor which has a great influence on the network as a component of the network. In addition, the network model composed of a limited variety of devices is only representative of the physical composition of the network in the information world in the existing life, and the network of the physical world cannot be improved through the analysis of the model. Fig. 1 shows a system simulation diagram, and it can be seen that: firstly, the one-way mapping from the physical world to the information world leads to the fact that the model is only the reflection of the existing equipment type, and great limitation is brought to the analysis of the model, secondly, the real network in the physical world cannot be analyzed and promoted through the change of the simulation model in the information world, the virtual information model is only the one-way mapping of the physical world, and the real network in the physical world cannot be promoted through the change of the virtual model, so that great difficulty is brought to the interaction between the two.

At least one embodiment of the present disclosure provides a modeling analysis method for a device management network, applied to a user terminal, including: acquiring the position information, the type information and the state information of the physical node, wherein the acquisition is realized by user input, a positioning function of a user terminal or photographing through the user terminal and automatically identifying the position information, the type information and the state information of the physical node; based on the position information and the type information of the physical nodes, automatically constructing a physical layer model according to a first preset rule so as to automatically connect the physical nodes into a line, and automatically displaying the physical nodes and the line between the physical nodes at corresponding positions by taking an electronic map as a background; and automatically constructing a logic layer model according to a second preset rule based on the type information and the state information of the physical node so as to construct a network model. At least one embodiment of the present disclosure also provides a working range analysis method, a network model update method, a user terminal, and a network server according to the above modeling analysis method.

At least one embodiment of the present disclosure provides a modeling analysis method for a device management network, which automatically constructs a network model for fast analysis according to a predetermined connection rule based on device information acquired by a user terminal, so that a user can quickly and automatically view a network graph and a network analysis result in real time, so as to promote a real network of a physical world based on the fast analysis of the network model.

In the following, a modeling analysis method provided according to at least one embodiment of the present disclosure is described in a non-limiting manner by using several examples or embodiments, and as described below, different features of these specific examples or embodiments may be combined with each other without mutual conflict, so as to obtain new examples or embodiments, which also belong to the protection scope of the present disclosure.

Fig. 2 is an architecture diagram of a device management system according to at least one embodiment of the present disclosure. For example, in at least one embodiment of the present disclosure, referring to fig. 2, a user terminal 201 is in signal connection with an emulation analysis server 202, and the emulation analysis server 202 is in signal connection with a management terminal 203. The user terminal 201 is associated and communicates with the management terminal 203 through the simulation analysis server 202. According to at least one embodiment of the present disclosure, a plurality of management terminals 203 and a plurality of user terminals 201 may be respectively in signal connection with the simulation analysis server 202 to form an equipment management system.

For example, the user terminal 201, the simulation analysis server 202, and the management terminal 203 may communicate with each other via a wired or wireless network. The wired network is, for example, a wired local area network, a wide area network, a wired telephone communication network. The wireless network is, for example, a wireless local area network, a mobile internet (e.g., 2G/3G/4G/5G), WiFi, etc. It should be noted that the embodiments of the present disclosure do not limit the specific communication manner therebetween.

For example, in at least one embodiment of the present disclosure, the user terminal 201 may be a mobile phone terminal, a tablet computer, or the like having a wireless positioning function. For example, the user terminal 201 may collect the location information using a positioning method such as mobile base station positioning, WiFi positioning, GPS positioning, and the like, which is not limited in this disclosure. For example, in the embodiment of the present disclosure, the management terminal 203 may be a computer, an all-in-one machine, or the like, and the embodiment of the present disclosure is not limited thereto. For example, the simulation analysis server 202 may be a device management network, such as may be deployed on some computer, kiosk, or user terminal. Of course, the simulation analysis server 202 may be a cloud server or a local server, and the embodiment of the disclosure is not limited thereto. For example, the simulation analysis server 202 may interface with one or more user terminals 201, and data collected on the user terminals 201 may be sent to the simulation analysis server 202 for storage or processing.

It should be noted that, in at least one embodiment of the present disclosure, the device management network may include, for example, a utility management system such as a power grid management system, a water pipe network management system, a gas pipe network system, and other similar device management networks such as a cable television network, a communication network, and the like, and the embodiments of the present disclosure are not limited in this respect. For example, in the embodiment of the present disclosure, the device management network in the physical world corresponds to the simulation network, i.e., the network model, in the information world, and the various devices in the device management network correspond to the various nodes in the network model. For example, in one example, taking a power grid management network as an example, the nodes in the power grid model may represent switches, transformers, power poles, telecommunication base station devices, and the like in a power grid, for example, in another example, taking a water pipe network management system as an example, the nodes in the water pipe network model may represent valves, water pumping stations, water treatment plants, and the like in a water pipe network, and for example, in another example, taking a gas pipe network management system as an example, the nodes in the gas pipe network model may represent valve stations, gas valves, compensators, gas storage devices, and the like, which is not particularly limited by the embodiments of the present disclosure and may be set according to actual circumstances.

A modeling analysis method for a device management network according to at least one embodiment of the present disclosure is described in detail below with reference to the accompanying drawings.

Fig. 3 is a flowchart of a modeling analysis method for a device management network according to at least one embodiment of the present disclosure. For example, at least one embodiment of the present disclosure provides a modeling analysis method 10 for a device management network, applied to a user terminal, the method including the following steps S101-S103, as shown in fig. 3.

It should be noted that, in the embodiment of the present disclosure, steps S101 to S103 may be executed sequentially or in other adjusted orders, and some or all operations in steps S101 to S103 may also be executed in parallel, for example, step S102 and step S103 may be executed synchronously, and the execution order of each step is not limited in the embodiment of the present disclosure and may be adjusted according to actual situations. For example, in the example of the present disclosure, the steps S101 to S103 may be performed in a separate user terminal, for example, the user terminal may be automatically networked through a mobile internet, and the above-described steps S101 to S103 are performed by the user terminal online in real time. For example, some operations may also be implemented on a simulation analysis server (e.g., on a cloud server), and embodiments of the present disclosure are not limited in this respect. For example, in some examples, implementing the modeling analysis method 10 for a device management network provided in at least one embodiment of the present disclosure may selectively perform some of steps S101 to S103, or may perform some additional steps other than steps S101 to S103, which is not particularly limited by the embodiments of the present disclosure.

Step S101: the method comprises the steps of collecting position information, type information and state information of a physical node through a user terminal, wherein the collection is realized through user input, a positioning function of the user terminal or through photographing of the user terminal and automatic identification of the position information, the type information and the state information of the physical node.

For example, each type of device in real life is used as a physical node to facilitate display of a network diagram (e.g., a power grid diagram, a water pipe network diagram, a gas pipe network diagram, etc.). The physical nodes are used as basic units of the network physical system, are used for displaying the reflection of various physical equipment in life in a simulation network model and participate in the display of network graphs through basic physical connection rules. For example, in one example, an operator carries a mobile device (e.g., a cell phone) with wireless location capabilities to perform information gathering of physical nodes along a predetermined route (e.g., a street in an area). For example, in one example, the information of the physical node includes location information, type information, state information, image information, and the like, which are not limited by the embodiments of the present disclosure.

For example, in at least one embodiment of the present disclosure, the grid modeling is taken as an example, and various types of physical nodes such as a substation, a ring main unit, a public transformer, a switch, a pole and the like can be included. For example, an operator obtains the location information of the user terminal through a location user terminal (e.g., a mobile phone) at a certain device (e.g., a ring main unit) beside a street as the location information of the physical node. For example, an operator (or user) may select or enter the location and type of the device on the user terminal, e.g., select a device type such as "transformer" on the user terminal, e.g., enter location information such as longitude and latitude of the location where the device is located on the user terminal. For another example, the operator may also select or input the status of the device on the user terminal, such as selecting "on" or "off. For example, the operator may also select or enter the device's number and name, etc., on the user terminal, such as "switch # 1". For example, the operator may also take a picture of the device and its surroundings, etc. through the user terminal, so that the type of device, the location where the device is located, etc. may be automatically identified based on the taken image of the device. In this way, the user terminal may acquire location information, state information, type information, picture information, and the like of the physical node, which is not limited in this embodiment of the disclosure.

Step S102: based on the position information and the type information of the physical nodes, according to a first preset rule, a physical layer model is automatically constructed to automatically connect the physical nodes into a line, and the physical nodes and the line between the physical nodes are automatically displayed at corresponding positions by taking an electronic map as a background.

For example, in one example, for a device management network to be modeled, the types of devices involved in the network are listed first, various devices are defined as various physical nodes, and connection rules between the various types of physical nodes, i.e., first predetermined rules, are defined. For example, taking the grid model as an example, the first predetermined rule may comprise that a pole node is automatically connected to another pole node that is closest thereto, e.g. the first predetermined rule may also comprise that a switch node is automatically connected to a transformer node that is closest thereto. It should be noted that, in the embodiment of the present disclosure, the first predetermined rule may be set based on experience, actual requirements, and the like, and the embodiment of the present disclosure is not particularly limited thereto.

For example, in one example, after defining the types and connection rules of the physical devices for the physical layer model, based on the acquired device information, a graph can be formed that visually displays the types and distribution of various physical devices in the context of an electronic map, which is the basis for the quick display of a network map. For example, in one example, establishing the physical layer model may automatically connect the received point devices into a line according to a first predetermined rule. For example, in one example, when a network is established, only nodes at two ends are collected by the principle that two points determine a straight line, and then a connection line between the two points is automatically drawn according to a predetermined connection rule. In this case, the first point is a certain node, and when the second node is collected, it is judged by a predetermined connection rule (for example, a first predetermined rule) with which node it should be connected, which is the basis for quickly establishing a network model and also the basis for quickly displaying a network map.

For example, in one example, physical nodes and lines between physical nodes are automatically displayed in respective locations in the context of an electronic map. For example, the electronic map may be stored locally or downloaded from a network, and the embodiments of the present disclosure are not limited thereto.

Fig. 4 illustrates a power grid physical layer model diagram provided by at least one embodiment of the present disclosure.

For example, in at least one embodiment of the present disclosure, taking grid modeling as an example, to facilitate fast display of a grid, each type of grid device in real life is taken as a corresponding physical node. For example, in one example, as shown in fig. 4, the physical layer model includes 4 types of devices including a power pole, a substation, a switch, and a transformer, and it should be noted that the embodiments of the present disclosure do not limit the type of the power grid device. For example, in one example, a substation is used as a power source to supply power to a power grid, poles are used for support, wires between poles form the physical line of the power grid, switches are used for segmented control in the line, a transformer is the final consumer, and switches and transformers are all mounted on poles.

For example, in one example, to facilitate a fast establishment of the grid graph, a first predetermined rule may also be defined as follows: the line is composed starting from the power supply (substation) and the serial number of the second device is the first device serial number plus 1. For example, the equipment is added from the No. 1 pole, if the next equipment added is the pole, the equipment is automatically named as the No. 2 pole, the No. 3 pole and the like, and so on. If the next device added after the number 1 pole is a switch, the next device can be manually named as the number 1 switch (for example, through selection or input), if the next switch is found in the devices which are continuously added, the next switch is automatically named as the number 2 switch, and the like. In this way, as the number of electric poles increases, the electric pole as a basic physical unit is automatically connected to the electric pole of the previous serial number. For example, the increase of the serial number is also automatically performed as a switch attached to the electric pole. In this way, the power grid diagram display with the electronic map as the background can be completed quickly, as shown in fig. 4.

For example, in one example, the increasing direction of the number of each type of physical node may indicate the direction of a signal or fluid in the device management network. For example, in one example, the device management network is a grid management network, and the direction of the signal or fluid in the device management network may be a direction of power supply in the grid management network. For example, in another example, the plant management network is a water management network, and the signal or fluid in the plant management network may be directed to a water supply. For another example, in another example, the plant management network is a gas grid management network, and the signal or fluid in the plant management network may be a gas supply direction. It should be noted that the embodiments of the present disclosure are not limited to this specifically.

For example, in the physical layer model of the power grid as shown in fig. 4, taking the electric pole as an example, the increasing direction of the number of the electric pole may indicate the power supply direction of the power grid. For example, in one example, it may be defined that the direction of power supply is from a small number of pole numbers to a large number. In this way, by identifying the number on the pole, the current flow direction, i.e., the power supply direction, can be displayed. For example, the power supply direction may be from number 1 pole to number 2 pole to number 3 pole, and so on. For another example, the direction of power may be from switch No. 1 to switch No. 2 to switch No. 3, and so on. Of course, in the case of adjusting the operation mode of the power grid, the power supply direction may also be from No. 6 to No. 5 to No. 4, and the like.

For example, in at least one embodiment of the present disclosure, for the physical layer model, based on device node (i.e., physical node) information collected by a user terminal (e.g., a mobile phone), and based on a predetermined connection rule (e.g., a first predetermined rule), automatically connecting collected physical nodes into a line, a network graph is quickly constructed without manual drawing.

Step S103: and automatically constructing a logic layer model according to a second preset rule based on the type information and the state information of the physical node so as to construct a network model.

For example, in one example, for the logical layer model, based on different types and operating states (e.g., connected or disconnected) of the physical nodes, the received point devices may be automatically connected into the logical network according to a second predetermined rule to determine a topological relationship between adjacent devices in the network, i.e., a topological structure of the logical layer model, which is a basis for network graph analysis. For example, in one example, exemplified by grid modeling, the second predetermined rule may include: the transformer substation node is automatically connected with a switch node nearest to the transformer substation node, and the switch node is automatically connected with a transformer node nearest to the transformer substation node. It should be noted that the second predetermined rule may be set based on experience, actual requirements, and the like, and the specific content of the second predetermined rule is not limited by the embodiments of the disclosure.

For example, in one example, the logical layer and the physical layer may be one layer. In this case, all the physical nodes are logical nodes, and the search workload in performing the network search analysis is too large.

Fig. 5 is a flowchart corresponding to step S103 in a modeling analysis method according to at least one embodiment of the disclosure. For example, in one example, as shown in fig. 5, in order to improve the retrieval analysis efficiency of the network, step S103 may include the following steps:

step S131: determining physical nodes meeting a first preset condition in the physical nodes as logical nodes based on the type information and the state information of the physical nodes;

step S132: and automatically constructing a logic layer model according to a second preset rule based on the type information and the state information of the logic node.

For example, in one example, the first predetermined condition may be a logical judgment of participation in the network model, i.e., participation in a state analysis of the network model. Therefore, the number of physical devices related to the network model can be greatly reduced, and the retrieval efficiency is improved. The logic layer mentioned hereinafter mainly refers to the logic layer composed of such simplified logic nodes. It should be noted that, the embodiment of the present disclosure does not limit the specific content of the first predetermined condition, and may be set according to actual requirements.

For example, in at least one embodiment of the present disclosure, taking grid modeling as an example, if grid devices of a physical layer are all used as logical nodes, they will all participate in the analysis of the network, and the retrieval amount will be large. In order to improve the retrieval efficiency of the network, equipment participating in logic judgment (state judgment) in the power grid system and electric equipment of a line terminal are used as logic nodes.

Fig. 6 illustrates a schematic diagram of a power grid logic layer model according to at least one embodiment of the present disclosure. For example, in at least one embodiment of the present disclosure, taking grid modeling as an example, the logical nodes include substation, switch, and transformer class 3 devices. For example, as shown in fig. 6, a substation supplies power to a switch, which supplies power to a transformer. The electric pole which only plays a supporting role does not participate in the network analysis of the system, and therefore does not belong to the equipment corresponding to the logic node.

For example, in one example, the second predetermined rule may be defined as follows: the transformer substation is used as an original power supply point, the power supply of the switch is from the transformer substation or a previous-stage switch, and the power supply of the transformer is from the switch. According to the second predetermined rule, the substation position as the power supply point is defined on the electronic map of the physical layer, the nearest substation or switch is automatically searched along with the appearance of the switch, and the upper-level power supply is judged and the connection of the logical relation is carried out according to the number of the electric pole where the substation or switch is located. For example, with the advent of transformers, the nearest switch is automatically searched and the appropriate power supply point is analyzed for connection in a logical relationship. In this way, the establishment of the grid logic layer can be completed quickly, as shown in fig. 6.

For example, in at least one embodiment of the present disclosure, step S102 and step S103 may be executed synchronously, that is, the physical layer model and the logical layer model may be constructed simultaneously, so as to construct the network model quickly and display the network diagram with the analysis function quickly.

Therefore, the modeling analysis method 10 for the device management network according to at least one embodiment of the present disclosure may utilize a mobile user terminal to perform data acquisition, and perform one-time automatic processing on the physical display and the logical relationship of the device according to a predetermined connection rule, and a change of the subsequent rule may automatically change the connection of the logical relationship, so that a user may view a network diagram and a network analysis result in real time, quickly, and automatically, so as to promote a real network of a physical world based on quick analysis of a network model. In addition, by selecting the logical nodes from the physical nodes, the retrieval workload is greatly reduced, and the retrieval efficiency of the network is improved.

For example, in at least one embodiment of the present disclosure, automatically constructing the physical layer model according to the first predetermined rule based on the location information and the type information of the physical node may include, when the location information and/or the type information of the physical node is changed (or updated) by the user terminal, automatically disconnecting a line that does not comply with the first predetermined rule in an existing line based on the changed (or updated) information with the electronic map as a background, and automatically connecting a line between the changed physical node and its neighboring physical node according to the first predetermined rule.

For example, in at least one example of the present disclosure, it is assumed that the existing grid model includes node No. 1, node No. 2, and node No. 3, and node No. 1 is connected to node No. 2 by a line, and node No. 2 is connected to node No. 3 by a line. For example, in an example, in a case where the aforementioned No. 1, No. 2, and No. 3 nodes are all poles, when the user moves the No. 2 pole node through, for example, a mobile phone terminal, that is, when changing the position information of the No. 2 pole node, the connection between the No. 2 pole node before moving and the No. 1 and No. 3 nodes is automatically disconnected, and the connection between the No. 2 pole node after moving and the No. 1 and No. 3 pole nodes is automatically connected according to a first predetermined rule based on the changed node information. It should be noted that, based on the changed node information, according to the first predetermined rule, if the No. 2 pole node is still connected to the No. 1 pole node and the No. 3 pole node, due to the fast update of the model, the user may see that the connection line between the No. 1 node and the No. 2 node and the connection line between the No. 2 node and the No. 3 node move along with the movement of the No. 2 node on the mobile phone interface.

For example, in an example, in a case where the aforementioned No. 1, No. 2, and No. 3 nodes are all poles, when a user adds a new 4-pole node between the No. 2 and No. 3 pole nodes through, for example, a mobile phone terminal, the connection between the No. 2 and No. 3 nodes is automatically disconnected, and the No. 2, No. 3, and No. 4 pole nodes are automatically line-connected according to a first predetermined rule based on the changed node information. If the original line between the node 2 and the node 3 coincides with the updated line between the pole node 2, the pole node 3 and the pole node 4, the user may see the new node 4 added to the line between the node 2 and the pole node 3 on the mobile phone interface due to the fast update of the model.

For example, in another example, in the case where the number 1, the number 2, and the number 3 are all electric poles, when the user deletes the number 2 electric pole node through, for example, a mobile phone terminal, the connection between the number 2 electric pole node and the number 1 and the number 3 electric pole node is automatically disconnected, and if the number 1 electric pole node is automatically connected to the number 3 electric pole node according to a first predetermined rule based on the changed node information, due to the rapid update of the model, the user may see that the number 2 node disappears on the electronic map on the mobile phone interface, and at the same time, the number 1 node and the number 3 node are automatically connected to form a line.

For another example, in an example, when the node 1 is a substation, the node 2 is a switch, and the node 3 is a transformer, when the user deletes the node 2 through the mobile phone terminal, if the node 1 cannot be directly connected to the node 3 according to the first predetermined rule, the user may see on the mobile phone interface that the node 2 disappears on the electronic map, and at the same time, the connection between the node 2 and the nodes 1 and 3 is also automatically disconnected.

Therefore, according to the modeling analysis method 10 provided by the embodiment of the present disclosure, when the physical node information changes, for example, a certain physical node is moved, deleted, added, or the like, the physical layer model automatically changes, that is, the physical layer model is automatically connected based on the changed physical node information, so that a large amount of human resources are not wasted to manually modify the line, and the situation that the physical layer model cannot be connected does not occur.

For example, in at least one embodiment of the present disclosure, for step S102, automatically building the physical layer model according to the first predetermined rule based on the location information and the type information of the physical node may further include: and responding to the collected position information and type information of the physical node while the user terminal keeps moving, and displaying the physical node and the automatically generated line between the physical node and the adjacent physical node in real time.

For example, in at least one embodiment of the present disclosure, when a user collects information of surrounding nodes while walking along a route with a user terminal (e.g., a mobile phone), in response to collecting the information of the nodes, the collected physical nodes and a route between the physical node and an adjacent physical node are automatically displayed on an electronic map in real time on the user terminal. Therefore, the user can quickly and automatically view the network diagram on the user terminal in real time.

In order to extend the existing network model without destroying the original physical layer model and logical layer model, at least one embodiment of the present disclosure further provides a modeling analysis method 20 for a device management network. For example, the modeling analysis method 20 includes, in addition to the above steps S101 to S103, the following steps:

step S201: acquiring position information of an additional node, and acquiring type information and state information of the additional node;

step S202: constructing an additional layer model for extending the network model based on the position information, the type information and the state information of the additional node;

step S203: and automatically displaying the type information and the state information of the additional nodes at corresponding positions by taking the electronic map as a background.

For example, in at least one embodiment of the present disclosure, an additional node corresponds to an additional device that has a significant impact on system analysis as system functionality expands, e.g., the additional device may be a basic component of some kind of attached state. With the increase of system functions, the attached states can be of various types, each state can have a plurality of constituent units, and the additional equipment is born after the network model is built, can be used as a new physical unit for displaying, but does not influence the physical connection of the original network, and can also be used as a new logical unit for participating in analysis, but does not influence the logical connection of the original network. The additional nodes appear in the role of physical or logical network additional state, which brings more influence on the analysis of the network. For additional nodes in the additional layer model, either the physical state or the logical connection state of the additional device, or both, are included. The additional equipment can be equipment with physical state directly added into the equipment type of the physical layer model to display the graph, and the additional equipment is added into the graph later, so that the connection mode of the original equipment is not damaged, and the display of the original physical network is not influenced. The additional device may also be a device having a logical connection state. The connection relation between the devices can be a connection rule or a connection rule-free relation, and the connection relation can participate in the analysis of the network and enrich the content of the system analysis. The additional layer model is the basis of the continuously expanded functions of the network model and is also the basis of the advanced analysis of the network.

Fig. 7 is a schematic diagram of an additional layer model of a power grid according to at least one embodiment of the present disclosure.

For example, in at least one embodiment of the present disclosure, taking power grid modeling as an example, as shown in fig. 7, the additional device in the power grid system may be a power grid monitoring device attached to an electric pole or an electric wire, or may be a device that transmits light or images to the electric pole with a receiving function, such as an image monitoring device, a light monitoring device, and the like, which is not limited in this respect. For example, the additional device may not be a basic component of a physical layer in the grid model, and the composition of the grid is independent of its existence, or may not be a basic component of a logical layer in the grid model, and the basic analysis of the network may not require its support. The additional equipment can monitor the current according to the equipment directly mounted on the electric wire or the electric pole according to different functions, indirectly judge whether the power is cut off through surrounding light sources, and provide early warning of power failure faults and the like by analyzing surrounding fire images. As future system functions are expanded, more additional information sources may be expanded, and embodiments of the present disclosure are not limited in this regard. For example, the additional devices may be physical devices, such as grid monitoring devices, which may be displayed in the composition of the physical network, and which may also participate in network analysis at the logical layer. For another example, the additional device may be non-physical device information such as light and image, and can only participate in network analysis of the logical layer. Because the additional equipment emerges after the basic physical layer model and the logic layer model are built, the connection of the original physical layer and the logic layer is not influenced, but the additional equipment plays a great role in the high-level analysis of the power grid.

For example, in the type of the additional layer of equipment, the grid monitoring equipment is installed on a power pole or a line, monitors whether the power grid is electrified in real time by providing information, and participates in analyzing the power supply state of the power grid, so that the grid monitoring equipment has an existing physical state or a logical connection state. Its installation location may be displayed in the grid map as part of the attributes of the line or equipment on which it is located, to enable the line or equipment to participate in the analysis of the logic, as shown in fig. 7.

Fig. 8A illustrates a system structure hierarchy diagram provided in at least one embodiment of the present disclosure, fig. 8B illustrates a simulation system model diagram provided in at least one embodiment of the present disclosure, and fig. 8C illustrates a power grid system diagram provided in at least one embodiment of the present disclosure.

For example, as shown in fig. 8A and 8B, in at least one embodiment of the present disclosure, the superposition of the above three models, i.e., the physical layer, the logical layer, and the additional layer, may constitute the complete structure of the network model. For example, in one example, different processing is performed on different types of devices based on the acquired location information, type information, status information, and the like of various physical devices, and the construction of a simulation network model, for example, a simulation network model as shown in fig. 8B, is completed quickly.

For example, in an example, taking power grid modeling as an example, as shown in fig. 8C, when a network model is established, the establishment of a power grid physical layer model and a power grid logical layer model can be automatically and synchronously completed according to a predetermined physical and logical connection rule, and an attachment layer is added according to various types of subsequently added monitoring devices. For example, the physical layer model enables a power grid diagram to be normally displayed, the logic layer model enables the power grid diagram to have an analysis function, the additional layer model enables the power grid diagram to be automatically and rapidly analyzed and judged, and the network model capable of displaying the current situation of the power grid in real time and rapidly and automatically giving out a fault analysis result, such as a power failure analysis result and the like, is formed under the combined action of the physical layer model, the logic layer model and the additional layer model.

For example, in at least one embodiment of the present disclosure, taking grid modeling as an example, as shown in fig. 8C, the electric poles and the devices are collected in the order of numbers from the power source as the substation, and the establishment of the physical layer network and the logical layer network is completed synchronously according to different types of the devices. Then, the equipment is displayed on a grid map of the physical layer according to the positions of the monitoring equipment on the electric pole and the electric wire. Meanwhile, the monitoring equipment is added into an additional layer as the attribute of the electric wire and the electric pole, and the electric wire and the electric pole without the logic analysis function are added into the logic analysis through the display of the state information (power on or power off) of the power grid to become a part of the advanced analysis of the power grid, so that the establishment of a network model for displaying the current situation of the power grid in real time is completed.

For example, in at least one embodiment of the present disclosure, the modeling analysis method may further include automatically displaying, on an electronic map, trends of signals or fluids in the device management network according to topological relationships between logical nodes in the logical layer model.

For example, in one example, displaying on an electronic map trends of devices managing signals or fluids in a network, includes: on the electronic map, the direction of the signal or fluid in the device management network is displayed by using a line with an arrow. Of course, other ways (e.g., simulation analysis results, etc.) to display the signal or the fluid trend may be used, and the embodiment of the disclosure is not limited thereto.

For example, in at least one embodiment of the present disclosure, the device management network may be a power grid management network, and the direction of the signal or the fluid in the device management network is a power supply direction in the power grid management network, which is not limited in this respect by the embodiments of the present disclosure.

For example, in at least one embodiment of the present disclosure, the modeling analysis method may further include: and displaying a corresponding simulation analysis result in response to the analysis function button in the scene interface being triggered.

For example, in at least one embodiment of the present disclosure, a network analysis function is provided based on the network model established in step S102 and step S103. For example, in one example, there is an analysis function button in a scene interface displayed by the user terminal, and when a user triggers a certain analysis function button, the user terminal may display a corresponding simulation analysis result in response to the analysis function button in the scene interface being triggered. For example, taking the modeling of the power grid as an example, when a user triggers a power failure analysis button on the user terminal, the user terminal automatically displays the corresponding power failure analysis result.

For example, in at least one embodiment of the present disclosure, in response to an analysis function in the scene interface being triggered, the simulation analysis result is displayed by a color change of the control line. For example, in one example, a switch in a particular grid line opens to cause a power outage, and in response to a power outage analysis function in the scene interface being triggered, the user is notified of the line outage by changing the color of the line controlled by the switch. Of course, the user may also be notified of the line power outage in other ways, for example, sending a message to the user in a specific area, and the embodiment of the disclosure is not limited in this respect.

For example, in at least one embodiment of the present disclosure, the above operations, in response to the analysis function in the scene interface being triggered, may be performed automatically by the user terminal in real time online, for example, through the mobile internet, and the like, which is not limited by the embodiments of the present disclosure.

For example, in at least one embodiment of the present disclosure, the above operation, the user terminal acquiring the location information, the type information, and the state information of the physical node may be performed in real time on-line through a mobile internet, and the user terminal may also be automatically networked in other manners, which is not limited in this respect by the embodiment of the present disclosure.

For example, in at least one embodiment of the present disclosure, after performing a data collection operation (e.g., the above step S101 or step S201), the user terminal may send the acquired node information (e.g., location information, type information, and status information of the physical node or/and the additional node) to the simulation analysis server through a mobile internet (e.g., 5G, 4G, etc.) for building a network model at the simulation analysis server side, and then may also receive a simulation analysis result from the simulation analysis server through the mobile internet for display. Of course, the embodiment of the present disclosure does not limit the specific communication mode between the user terminal and the simulation analysis server. The specific operation at the simulation analysis server side is described in detail below.

For example, in at least one embodiment of the present disclosure, a user terminal (e.g., a mobile phone) may be automatically networked through a mobile internet, and the above modeling analysis methods 10 and 20 may be automatically performed by the user terminal in real time online, which is not limited by the embodiments of the present disclosure.

The modeling analysis method provided by at least one embodiment of the present disclosure quickly completes establishment of a network model by means of classification and layering in combination with predetermined rules (e.g., a first predetermined rule, a second predetermined rule, etc.), and can reserve a space for infinite extension of a network without affecting an original network structure by stacking additional layers. For example, the modeling analysis methods 10 and 20 described above provided by at least one embodiment of the present disclosure include, but are not limited to, the following advantages:

firstly, the method comprises the following steps: the existing network model needs more manual participation, the connection of the logical relationship needs to be manually established after the position and attribute information of the equipment is collected, and the logical connection of the equipment needs to be manually processed along with the change of the logical relationship (for example, the power grid equipment is changed into the connection relationship from the parent-child relationship).

Fig. 9A is a schematic diagram of a dual power supply provided in at least one embodiment of the present disclosure, and fig. 9B is a schematic diagram of a dual power supply conversion provided in at least one embodiment of the present disclosure. For example, as shown in fig. 9A, in the case of dual power supply, in a normal case, the right-side substation is in an open state of a dotted line, the power source is from the left-side substation, the left-side substation supplies power to the transformer through the step-by-step switches, and the direction of power supply can be represented by a logical relationship from parent to child between devices. For example, as shown in fig. 9B, when the left-side substation is in the broken line disconnection state, the network power supply comes from the right-side substation, and the power supply direction of the switch in the figure is changed. In this case, the original parent-child relationship is wrong, and the parent-child relationship between the devices in the model must be changed to the connection relationship. For this situation, the modeling analysis methods 10 and 20 provided by at least one embodiment of the present disclosure can automatically complete the fast adjustment of the logical relationship only by changing the setting of the connection rule of the model without making a large adjustment.

Secondly, the method comprises the following steps: the existing network model is limited in scalability. With the addition of new types of devices, the original model structure must be modified. The modeling analysis method 20 provided by at least one embodiment of the present disclosure provides a chance for infinite extension of a network model through establishment of an additional layer of the third layer, and addition of a new device does not destroy the structure of the existing physical layer for display and logical layer connection, does not cause a large impact on the existing model, and is an additional effect.

Thirdly, the method comprises the following steps: the number of logic devices is simplified, and the efficiency of retrieval analysis is greatly improved. Through the definition of the logic layer and the additional layer device, the number of devices participating in network analysis can be automatically adjusted at any time, the efficiency of retrieval analysis is greatly improved, and the change of a network analysis model is facilitated.

The modeling analysis method performed at the user terminal according to the embodiment of the present disclosure is described above, and the modeling analysis method performed at the management side according to the embodiment of the present disclosure is further described below. The method corresponds to the method in the foregoing embodiment, and for brevity of the description, only brief description will be given below, and specific reference may be made to the modeling analysis method in the foregoing embodiment.

For example, a modeling analysis method for a device management network according to at least one embodiment of the present disclosure is applied to a management terminal, and includes the following operations S301 to S303:

step S301: and acquiring the position information, the type information and the state information of the physical node.

For example, in at least one embodiment of the present disclosure, the acquiring of the information of the physical node by the management terminal may be manually inputting the node information into the management terminal by an operator, may also be reading the node information stored locally, or downloading the node information from the internet, and may also be automatically identifying the node information by scanning a picture, and the like.

Step S302: and automatically constructing a physical layer model according to a first preset rule based on the position information and the type information of the physical nodes so as to automatically connect the physical nodes into a line, and automatically displaying the physical nodes and the line between the physical nodes at corresponding positions by taking the electronic map as a background.

Step S303: and automatically constructing a logic layer model according to a second preset rule based on the type information and the state information of the physical node so as to construct a network model.

For example, in at least one embodiment of the present disclosure, the operations of step S302 and step S303 are similar to step S102 and step S103 described above, and the description about these operations may refer to the above description about step S102-step S103, which is not repeated herein.

For example, in at least one embodiment of the present disclosure, corresponding to the above steps S201-S202 performed by the user terminal, the management terminal may also obtain the location information, the type information, and the state information of the additional node; then constructing an additional layer model for expanding the network model based on the position information, the type information and the state information of the additional node; then, the type information and the state information of the additional nodes are automatically displayed on corresponding positions by taking the electronic map as a background.

In the embodiment of the present disclosure, the management terminal may have a management function in addition to performing operations similar to the above-described modeling analysis method of the user terminal. For example, after the user terminal acquires the node information and generates a corresponding network graph and a network analysis result, an operator can check whether the information is valid or invalid through the management terminal after the operator checks the information in the field. For example, in one example, an operator may maintain system data, manage user accounts, grant user permissions, determine version updates, and the like through a management terminal, which is not particularly limited by the embodiments of the present disclosure.

For example, in at least one embodiment of the present disclosure, similar to the user terminal, after acquiring the node information, the management terminal may transmit the acquired node information (e.g., location information, type information, status information, and the like of the physical node or/and the additional node) to the simulation analysis server through the mobile internet, the wireless local area network, and the like, for building a network model at the simulation analysis server, and then receive a simulation analysis result from the simulation analysis server through the mobile internet, the wireless local area network, and the like, for display. Of course, the embodiment of the disclosure does not limit the specific communication mode between the management terminal and the simulation analysis server.

For example, in at least one embodiment of the present disclosure, the management terminal may be automatically networked through the mobile internet, similar to the user terminal, and the above-described modeling analysis methods 10 and 20 may be automatically performed by the management terminal on-line in real time, which is not limited by the embodiment of the present disclosure.

The modeling analysis method performed at the management terminal according to the embodiment of the present disclosure is described above, and the modeling analysis method performed at the simulation analysis server according to the embodiment of the present disclosure is further described below. The method corresponds to the method in the foregoing embodiment, and for brevity of the description, only brief description will be given below, and specific reference may be made to the modeling analysis method in the foregoing embodiment.

For example, at least one embodiment of the present disclosure provides a modeling analysis method for a device management network, applied to a simulation analysis server, the modeling analysis method including the following operations:

step S401: location information, type information, and status information of the physical node are received.

For example, in one example, the simulation analysis server may receive the location information, the type information, and the status information of the physical node from the user terminal through a mobile internet, a wireless local area network, and the like, and may further include other information, such as image information and the like, which is not limited in this respect by the embodiments of the present disclosure. For example, in one example, the simulation analysis server may receive location information, type information, status information, and the like of the physical node from the management terminal through a mobile internet, a wireless local area network, and the like.

Step S402: and automatically constructing a physical layer model according to a first preset rule based on the position information and the type information of the physical nodes so as to automatically connect the physical nodes into a line, wherein the physical layer model is used for automatically displaying the physical nodes and the line between the physical nodes on corresponding positions by taking an electronic map as a background.

Step S403: automatically constructing a logical layer model according to a second predetermined rule based on the type information and the state information of the physical node to construct a network model,

step S404: in response to receiving the request data, a simulation analysis result is generated.

Steps S402 and S403 are similar to steps S102 and S103, and the description of this operation can refer to the description related to step S102 and step S103, and will not be repeated here.

For example, with respect to step S404, in one example, in response to the simulation analysis server receiving the request data (e.g., power outage analysis, power tracking, etc.) from the user terminal or the management terminal, a simulation analysis result is generated and sent to the user terminal or the management terminal for viewing by the user.

For example, in at least one embodiment of the present disclosure, the simulation analysis server may receive location information, type information, and state information of the physical node from the user terminal, so as to construct a network model at the simulation analysis server, and send a simulation analysis result generated at the simulation analysis server to the user terminal.

For example, in at least one embodiment of the present disclosure, receiving location information, type information, and status information of a physical node from a user terminal may include: location information, type information, and status information of the physical node are received from the user terminal through the mobile internet. For example, sending the simulation analysis result to the user terminal may include: and sending the simulation analysis result to the user terminal through the mobile internet. It should be noted that, the embodiment of the present disclosure does not specifically limit the communication manner between the user terminal and the simulation analysis server.

For example, in at least one embodiment of the present disclosure, the modeling analysis method applied to the simulation analysis server may further include: in response to receiving the information of the additional node, an additional layer model is constructed based on the information of the additional node, the additional layer model being used to extend the network model. For the description of the operation of constructing the additional layer model, reference may be made to the above description related to step S202, and no further description is provided here

For example, at least one embodiment of the present disclosure further provides a modeling analysis method applied to the power grid management system. The method comprises the following steps:

step S601: the method comprises the steps of collecting the position information, the type information and the state information of the power grid equipment through a user terminal, wherein the collection comprises the steps of photographing through user input and a positioning function of the user terminal or through the user terminal and automatically identifying the position information, the type information and the state information of the power grid equipment.

Step S602: based on the position information and the type information of the power grid equipment, a physical layer model is automatically constructed according to a first preset rule so as to automatically connect the power grid equipment into a line, and the power grid equipment and the line between the power grid equipment are automatically displayed at corresponding positions by taking an electronic map as a background.

Step S603: and automatically constructing a logic layer model according to a second preset rule based on the type information and the state information of the power grid equipment so as to construct a network model.

Step S604: and responding to the triggering of the power failure analysis function in the scene interface, and displaying the power failure analysis result.

For example, in at least one embodiment of the present disclosure, the operations of step S601 to step S603 are similar to those of step S101 to step S103 described above, and for the description of these operations, reference may be made to the related description of step S101 to step S103, and details are not repeated here.

For example, in one example, the power grid map obtained by modeling the power grid by using the modeling analysis method may further have functions of fault location, power supply range analysis, power failure information transmission, and the like.

For example, in at least one embodiment of the present disclosure, a user terminal (e.g., a mobile phone) may be automatically networked through a mobile internet, and the above modeling analysis method applied to the power grid management system may be automatically performed by the user terminal on line in real time, which is not limited by the embodiments of the present disclosure.

Fig. 10 is a schematic diagram of grid fault location provided by at least one embodiment of the present disclosure. For example, in one example, after the modeling analysis method is adopted, a user collects information of the power grid equipment along a route through a mobile phone, and then constructs a power grid model based on the collected information of the power grid equipment. For example, the power tracing function may be used to analyze the intersection of the fault points, that is, the fault power point, as shown in fig. 10, after receiving the power failure information sent by the user 1 and the user 2, the intersection of the upper power source is located at the switch 2, and then the switch 2 is the fault power point. In this case, after the grid company disconnects the switch 2, the line from the substation to the switch 2 can be restored to normal power supply. For example, in one example, it may also be determined that the lines in which the user 1 and the user 2 are located have power failure based on an additional device (e.g., a power grid monitoring device, an image monitoring device, etc.), so as to confirm that the superior power source intersection is located at the switch 2, and the switch 2 is a fault power source point.

For example, at least one embodiment of the present disclosure further provides a working range analysis method according to the above modeling analysis method, including: analyzing a working line corresponding to the physical node in the network model based on the network model consisting of the physical node and the line; and automatically connecting each end node of the working line, and forming a closed area corresponding to the physical node on the electronic map according to a third preset rule, wherein the closed area is a working range corresponding to the physical node.

For example, taking a power grid management system as an example, after a power grid model (a network model composed of physical nodes and lines) is constructed by the modeling analysis method, the working range, that is, the power supply range, of a certain power grid device (that is, a physical node) in the power grid model can be analyzed.

Fig. 11 is a power supply range analysis diagram provided by at least one embodiment of the present disclosure. For example, as shown in fig. 11, after the power grid model is established, for the power supply range analysis function, for example, a line supplied with power from a power supply point (e.g., a substation), i.e., a working line, is first analyzed, and nodes at respective ends are connected, i.e., a power supply range of the line. For example, the node at the farthest end is the power supply distance of the line, and the system can automatically complete the accumulation of the lengths of the various sections of the line, that is, the total length of the line. In practice, the connection of end nodes is typically made along roads on an electronic map. For example, in the area between the two lines, the division may be performed by a predetermined rule (for example, a third predetermined rule). For example, the third predetermined rule may be defined as: and connecting intermediate points between adjacent equipment on different working lines respectively to form a connecting line as an area boundary, thereby forming a complete power supply area of each line. It should be noted that the third predetermined rule may be set based on experience, actual requirements, and the like, and the specific content of the third predetermined rule is not limited by the embodiments of the disclosure.

For example, in the example shown in fig. 11, the respective power supply areas are formed by the working lines to which the two substations belong. For example, the working lines corresponding to the two substations are analyzed first, the end nodes of the respective working lines are automatically connected, and according to a third predetermined rule, for example, a common center line of the equipment is used as a boundary in the middle of the two lines, so that two closed areas in which the working lines are independent can be formed, and the two closed areas are power supply ranges corresponding to the two substations respectively.

For example, in at least one embodiment of the present disclosure, the analysis results of the power supply range may be displayed at the client in response to an analysis function in the user interface being triggered.

The working range analysis method further comprises the following steps: and sending information to the user in the working range corresponding to the physical node, wherein the information at least comprises pictures and characters. For example, in one example, when a power supply bureau plans to repair a certain power grid device in the next week, iconic and textual information may be sent to users in the working range corresponding to the power grid device in advance, for example, the information includes, but is not limited to, a name of the device to be repaired, an image of the device, an image of an affected area, an estimated repair time, and the like.

For example, in at least one embodiment of the present disclosure, when a failure of a certain physical node (e.g., a certain grid device) is detected, failure information may be sent to a user within an operating range corresponding to the physical node. For example, the fault information includes, but is not limited to, a fault cause, a fault range (e.g., a map image corresponding to the fault range), and an estimated fault processing time, a fault line name, and the like.

For example, in one example, in the power failure situation of fig. 10, the electronic map within the power supply range of the switch 2 may be configured to send the power failure information of the image and text to the user in the area in a manner of WeChat or the like. For example, the outage information may include the type of failure (e.g., substation, switch failure, etc.), outage line, outage area images, estimated outage time, etc. to alleviate user anxiety.

For example, in an embodiment of the present disclosure, sending information to users within a work scope corresponding to a physical node may include sending information to individual users or enterprise users, etc. within the work scope. For example, in one example, information may be sent to a user terminal, a management terminal, and the like via a mobile internet, a wireless local area network, and the like, and the information may be displayed on a display screen for quick viewing by a user, for example. For example, the information at least includes a picture and a text, and for example, the information may be sent to the user in a multimedia message, a WeChat, an email, and the like, which is not limited in this embodiment of the disclosure.

It should be noted that the above method for analyzing the operating range of the device may be applied to a power grid management system, a water pipe network management system, a gas pipe network management system, and the like, and the embodiment of the disclosure is not particularly limited thereto. For example, in one example, when a water pipe failure (e.g., a water pipe burst) is detected in a certain location, the above-mentioned device operating range analysis method may be used to send pictorially-enhanced water cut-off information, such as water cut-off time, water cut-off reason, water cut-off range, and the like, to the users within the water supply range of the failed water pipe, i.e., the users who cut off water. Therefore, the problem that at present, municipal companies such as power grids, tap water, natural gas and the like can only issue text fault information can be solved.

For example, in at least one embodiment of the present disclosure, a user terminal (e.g., a mobile phone) may be automatically networked through a mobile internet, and the device working range analysis method may be automatically performed by the user terminal in real time online, which is not limited by the embodiment of the present disclosure.

For example, at least one embodiment of the present disclosure further provides a network model updating method, which may support distributed concurrent access and merging of network graphs. It should be further noted that the network model updating method may be applied to a power grid management model, a water pipe network management model, a gas pipe network management model, and the like, and may also be applied to other data management models, such as a road network model (for example, used in a hundred degree map, a google map, and the like), a meteorological data management model, and the like, which is not limited in this respect in this embodiment of the disclosure.

For example, in at least one embodiment of the present disclosure, the network model updating method may include the following steps S701-S704.

Step S701: the electronic map is divided into a plurality of regions.

For example, in one example, to facilitate rapid modeling of a network for a new area, an electronic map is divided into multiple areas in a grid or administrative boundary, or the like.

Step S702: in the network updating process, when node information of different contents in the same area is received from a plurality of user terminals, a corresponding network model is respectively generated for each of the plurality of user terminals to form a plurality of network models.

For example, in one example, multiple registered users may simultaneously perform data collection for the same area (e.g., the same line, the same cell, etc.) and support simultaneous submissions. For example, in one example, the data submitted by each registered user may form an independent submission layer named with an independent version number at the emulation analysis server.

For example, in one example, the modeling analysis method provided by the embodiment of the present disclosure may be adopted to generate a corresponding network model for each user terminal based on data submitted by each user terminal. It should be noted that other conventional modeling methods may also be adopted to generate a corresponding network model for each user terminal based on the data submitted by each user terminal, and the embodiment of the present disclosure does not specifically limit the modeling method.

Step S703: and selecting one network model from the plurality of network models based on a second preset condition, and saving the network model in a layer mode to serve as a submission layer corresponding to the current time.

For example, in one example, the second predetermined condition may include at least one of: the network model may include a maximum number of physical nodes (e.g., a maximum number of devices included), a maximum map area included in the network model, a maximum map route included in the network model, a maximum type of physical nodes included in the network model, and so on. For example, in one example, the second predetermined may be that the map area included in the network model is largest in area and the number of physical nodes is largest. Of course, the second predetermined condition may be set according to actual requirements, and the embodiment of the disclosure is not limited thereto.

Step S704: and when the number of the saved submitted layers reaches a threshold value or a preset time is set to the first submitted layer, selecting one submitted layer from the plurality of submitted layers as a time layer for updating the network model based on a third preset condition.

For example, in one example, similar to the second predetermined condition, the third predetermined condition may include at least one of: the network model may include a maximum number of physical nodes (e.g., a maximum number of devices included), a maximum map area included in the network model, a maximum map route included in the network model, a maximum type of physical nodes included in the network model, and so on. Of course, the third predetermined condition may be set according to actual requirements, and the embodiment of the disclosure is not limited thereto.

For example, taking power grid modeling as an example, the time layer version may be displayed on the power grid diagram, and compared with the existing layer version in a display manner of different colors. For example, the determined time layer version is updated as a formal power grid model version. For example, in one example, any registered user can evaluate the correctness of the existing power grid data by marking or submitting a version layer on a power grid diagram, so that system maintenance personnel can conveniently verify the correctness on site. For the data verified to be valid, the system administrator can update part of the devices at the user terminal or the management end.

It should be noted that the content of the submitted layer is not limited to a certain size, and may be a section of line, or may be a part of equipment, and as long as the confirmation is valid, the submitted layer may be converted into a time layer for formal submission.

For example, in at least one embodiment of the present disclosure, the network model may include a road network model, and the embodiment of the present disclosure is not limited thereto.

For example, in at least one embodiment of the present disclosure, the network model updating method may be performed on the server side. For example, in at least one embodiment of the present disclosure, a user terminal (e.g., a mobile phone) may be automatically networked through a mobile internet, and the above-described network model updating method may be automatically performed by the user terminal online in real time, which is not limited by the embodiments of the present disclosure.

Therefore, the network model updating method based on the modeling analysis method provided by at least one embodiment of the disclosure can effectively deal with the problem of concurrent data acquisition of multiple people, and also provides an updating mode of the network model.

For example, at least one embodiment of the present disclosure further provides a user terminal, which includes a memory and a processor, where the memory stores instructions, and the processor, when executing the instructions, causes the user terminal to execute any modeling analysis method provided by the embodiments of the present disclosure.

For example, at least one embodiment of the present disclosure further provides a network server, which includes a memory and a processor, where the memory stores instructions, and the processor, when executing the instructions, causes the network server to perform any one of the modeling analysis method, the working range analysis method, and the network model update method provided by the embodiments of the present disclosure.

The following points need to be explained:

(1) the drawings of the embodiments of the disclosure only relate to the structures related to the embodiments of the disclosure, and other structures can refer to common designs.

(2) Without conflict, embodiments of the present disclosure and features of the embodiments may be combined with each other to arrive at new embodiments.

The above description is only a specific embodiment of the present disclosure, but the scope of the present disclosure is not limited thereto, and the scope of the present disclosure should be subject to the scope of the claims.

Claims

1. A modeling analysis method for a device management network is applied to a user terminal, and the method comprises the following steps:

acquiring the position information, the type information and the state information of a physical node through the user terminal, wherein the acquisition is realized through user input, a positioning function of the user terminal or photographing through the user terminal and automatically identifying the position information, the type information and the state information of the physical node;

based on the position information and the type information of the physical nodes, automatically constructing a physical layer model according to a first preset rule so as to automatically connect the physical nodes into a line, and automatically displaying the physical nodes and the line between the physical nodes at corresponding positions by taking an electronic map as a background;

and automatically constructing a logic layer model according to a second preset rule based on the type information and the state information of the physical node so as to construct a network model.

2. The method of claim 1, wherein automatically building a physical layer model according to a first predetermined rule based on the location information and the type information of the physical node comprises:

when the position information and/or the type information of the physical node are/is changed through the user terminal, based on the changed information, the line which does not accord with the first preset rule in the original line is automatically disconnected by taking the electronic map as the background, and the line is automatically connected between the changed physical node and the adjacent physical node thereof according to the first preset rule.

3. The method of claim 1, wherein automatically building a physical layer model according to a first predetermined rule based on the location information and the type information of the physical node comprises:

and responding to the collected position information and type information of the physical node while the user terminal keeps moving, and displaying the physical node and the automatically generated line between the physical node and the adjacent physical node in real time.

4. The method of claim 1, further comprising:

acquiring position information of an additional node, and acquiring type information and state information of the additional node;

building an additional layer model for extending the network model based on the location information, type information, and state information of the additional node;

and automatically displaying the type information and the state information of the additional node at a corresponding position by taking the electronic map as a background.

5. The modeling analysis method of claim 1, wherein automatically constructing the logical layer model according to the second predetermined rule based on the type information and the state information of the physical node comprises:

determining, as a logical node, a physical node satisfying a first predetermined condition among the physical nodes displayed on the electronic map based on the type information and the state information of the physical nodes;

and automatically establishing the topological relation among the logic nodes according to the second preset rule based on the type information and the state information of the logic nodes.

6. The modeling analysis method of claim 1, wherein the building of the physical layer model and the logical layer model is performed synchronously.

7. The method of claim 1, further comprising: and automatically displaying the trend of the signals or the fluid in the equipment management network on the electronic map according to the topological relation among the logic nodes in the logic layer model.

8. The method of claim 7, wherein displaying trends of signals or fluids in the device management network on the electronic map comprises:

on the electronic map, the trend of the signals or fluids in the equipment management network is displayed by using lines with arrows.

9. A modeling analysis method according to claim 7, wherein said equipment management network is a grid management network and the trend of signals or fluids in said equipment management network is the direction of power supply in said grid management network.

10. The method of claim 1, further comprising: and displaying the simulation analysis result in response to the analysis function in the scene interface being triggered.

11. The method of claim 10, wherein displaying simulation analysis results in response to an analysis function in the context interface being triggered comprises:

and displaying the simulation analysis result by changing the color of the line in response to the analysis function in the scene interface being triggered.

12. The method of claim 10, wherein the displaying of the simulation analysis results is performed automatically by the user terminal in real-time online in response to an analysis function in the context interface being triggered.

13. The modeling analysis method of claim 1, wherein the user terminal collecting location information, type information and status information of the physical node is performed on-line in real time through a mobile internet.

14. A modeling analysis method according to claim 1, wherein the equipment management network is a grid management network, the method comprising:

collecting position information, type information and state information of power grid equipment through a user terminal, wherein the collection comprises the steps of photographing through the user input and the positioning function of the user terminal or through the user terminal and automatically identifying the position information, the type information and the state information of the power grid equipment;

automatically constructing a physical layer model according to a first preset rule based on the position information and the type information of the power grid equipment so as to automatically connect the power grid equipment into a line, and automatically displaying the power grid equipment and the line between the power grid equipment at a corresponding position by taking an electronic map as a background;

based on the type information and the state information of the power grid equipment, automatically constructing a logic layer model according to a second preset rule so as to construct a network model;

and responding to the triggering of the power failure analysis function in the scene interface, and displaying the power failure analysis result.

15. A modeling analysis method for a device management network is applied to a simulation analysis server, and the method comprises the following steps:

receiving position information, type information and state information of a physical node;

based on the position information and the type information of the physical nodes, automatically constructing a physical layer model according to a first preset rule so as to automatically connect the physical nodes into a line, wherein the physical layer model is used for automatically displaying the physical nodes and the line between the physical nodes on corresponding positions by taking an electronic map as a background;

based on the type information and the state information of the physical nodes, automatically constructing a logic layer model according to a second preset rule so as to construct a network model;

in response to receiving the request data, a simulation analysis result is generated.

16. The modeling analysis method of claim 15, further comprising:

receiving the position information, the type information and the state information of the physical node from a user terminal so as to construct the network model at the simulation analysis server side;

and sending the simulation analysis result to the user terminal.

17. The modeling analysis method of claim 16, wherein receiving location information, type information, and status information of the physical node from a user terminal comprises:

receiving location information, type information and state information of the physical node from a user terminal through a mobile internet; and

sending the simulation analysis result to the user terminal, including:

and sending the simulation analysis result to the user terminal through the mobile internet.

18. A working range analysis method of the modeling analysis method according to claim 15, comprising:

analyzing a working line corresponding to the physical node in the network model based on the network model consisting of the physical node and the line;

and automatically connecting each tail end node of the working line, and forming a closed area corresponding to the physical node on the electronic map according to a third preset rule, wherein the closed area is a working range corresponding to the physical node.

19. The working range analysis method of claim 18, further comprising:

and sending information to a user in a working range corresponding to the physical node, wherein the information at least comprises pictures and characters.

20. The workscope analysis method of claim 19, wherein transmitting information to users within the workscope corresponding to the physical node comprises

In response to the physical node failing, sending information to users within a working range corresponding to the physical node,

the information comprises a fault line name, a fault range and estimated fault processing time.

21. A network model update method, comprising:

dividing the electronic map into a plurality of areas;

in the network updating process, when node information of different contents in the same area is received from a plurality of user terminals, a corresponding network model is respectively generated for each of the user terminals to form a plurality of network models;

based on a second preset condition, selecting one network model from the multiple network models, and saving the network model in a layer mode to serve as a submission layer corresponding to the current time;

and when the number of the saved submitted layers reaches a threshold value or a preset time is set to the first submitted layer, selecting one submitted layer from the plurality of submitted layers as a time layer for updating the network model based on a third preset condition.

22. The network model updating method of claim 21, wherein the second predetermined condition and the third predetermined condition comprise at least one of:

the network model comprises the maximum number of physical nodes;

the area of a map region included in the network model is maximum;

the map route included in the network model is longest;

the network model includes the most types of physical nodes.

23. The network model updating method of claim 21, wherein the network model comprises a road network model.

24. A user terminal comprising a memory and a processor, wherein,

the memory has stored therein instructions that, when executed by the processor, cause the user terminal to perform the method of any of claims 1-14.

25. A network server comprising a memory and a processor, wherein,

the memory has stored therein instructions that, when executed by the processor, cause the network server to perform the method of any of claims 15-23.