WO2023109142A1

WO2023109142A1 - Method and apparatus for determining critical path of energy internet of things physical and information system

Info

Publication number: WO2023109142A1
Application number: PCT/CN2022/108506
Authority: WO
Inventors: 林国强; 高昆仑; 周飞; 赵保华; 刘思言; 林剑超; 任春卉
Original assignee: 国网智能电网研究院有限公司; 国网江苏省电力有限公司; 国家电网有限公司
Priority date: 2021-12-15
Filing date: 2022-07-28
Publication date: 2023-06-22
Also published as: CN114221983B; CN114221983A

Abstract

The present application discloses a method and apparatus for determining a critical path of an energy Internet of Things physical and information system. The method comprises: creating a target adjacent matrix of the energy Internet of Things physical and information system on the basis of each adjacent matrix constituted of a physical network topology, an information network topology, and an interactive network topology of a target energy device; normalizing each adjacent matrix constituted of the physical network topology, the information network topology, and the interactive network topology in the target adjacent matrix, so as to acquire link edge weights among nodes of the physical network topology, the information network topology, and the interactive network topology; and determining a critical path in the physical network topology, the information network topology, and the interactive network topology according to the link edge weights among the nodes. In this case, on the basis of the topological structure of the energy Internet of Things, the critical degree of a network path constituted of different service attributes in the energy Internet of Things can be quantified by normalizing the link edge weights between different energy media and information media.

Description

A critical path determination method and device for an energy internet of things physical and information system

Cross References to Related Applications

This application is based on a Chinese patent application with application number 202111537635.1 and a filing date of December 15, 2021, and claims the priority of this Chinese patent application. The entire content of this Chinese patent application is hereby incorporated into this application by reference.

technical field

The present application relates to the technical field of energy internet of things, in particular to a method and device for determining a critical path of energy internet of things physical and information systems.

Background technique

With the development and high integration of technologies such as smart grid, big data, Internet of Things, cloud computing, mobile Internet and artificial intelligence, the energy Internet, which uses electric energy as the basic energy medium, has emerged with priority on the use of renewable energy. The so-called Energy Internet completes the high integration of Energy Internet physical space and information space through the state perception of Energy Internet physical space, data transmission in information space, data analysis, processing and control processes.

In related technologies, due to the complexity and variety of network paths and node attribute information in the network topology model, if the specific energy medium status is gradually analyzed for each network path and each node information, not only the analysis efficiency is poor, but also it is impossible to quickly know The criticality of network paths composed of different business attributes in the energy Internet of Things.

Contents of the invention

The technical problem to be solved in this application is to overcome the complexity and variety of network path and node attribute information in the network topology model in the prior art. If the specific energy medium state is gradually analyzed for each network path and each node information, not only is the analysis efficiency relatively high Moreover, it is impossible to quickly know the criticality of the network paths formed by different business attributes in the Energy Internet of Things, so as to provide a method and device for determining the critical path of the physical and information system of the Energy Internet of Things. The technical solutions of the embodiments of the present application can be implemented as follows:

In the first aspect, an embodiment of the present application provides a method for determining a critical path of an energy Internet of Things physical and information system, including the following steps:

Based on the adjacency matrix composed of the physical network topology, information network topology and interactive network topology of the target energy equipment, create the target adjacency matrix of the energy Internet of Things physical and information system;

By performing normalization processing on each adjacency matrix formed by the physical network topology, the information network topology and the interaction network topology in the target adjacency matrix, the physical network topology, the information network topology and the Edge weights between nodes of the interactive network topology;

Determine critical paths in the physical network topology, the information network topology, and the interactive network topology according to the edge weights between the nodes.

In the second aspect, the embodiment of the present application provides a critical path determination device for the physical and information system of the Energy Internet of Things, including the following modules:

The adjacency matrix determination module is configured as each adjacency matrix formed based on the physical network topology, information network topology and interactive network topology of the target energy equipment, and creates the target adjacency matrix of the energy Internet of Things physical and information system;

A normalization processing module configured to perform normalization processing on each adjacency matrix formed by the physical network topology, the information network topology, and the interaction network topology in the target adjacency matrix to obtain the physical network Edge weights between nodes of the topology, the information network topology, and the interactive network topology;

The critical path determination module is configured to determine the critical path in the physical network topology, the information network topology and the interactive network topology according to the edge weights between the nodes.

In the third aspect, the embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores computer instructions, and the computer instructions are configured to make the computer execute the first aspect or any implementation of the first aspect The critical path determination method of the Energy Internet of Things physical and information system described in the method.

In the fourth aspect, the embodiment of this embodiment also provides an electronic device, a memory and a processor, the memory and the processor are connected to each other by communication, the memory stores computer instructions, and the processor executes The computer instructions are used to execute the method for determining the critical path of the physical and information system of the Energy Internet of Things described in the first aspect or any implementation manner of the first aspect.

The embodiment of the present application has the following beneficial technical effects:

The embodiment of the present application provides a method and device for determining the critical path of the physical and information system of the Energy Internet of Things. The adjacency matrix of the physical and information system of the Internet of Things; by normalizing the adjacency matrices composed of the physical network topology, information network topology and interactive network topology, to obtain the nodes of the physical network topology, information network topology and interactive network topology The weight of the connection between each node; according to the weight of the connection between each node, determine the key path in the physical network topology, information network topology and interactive network topology. In this way, based on the topological structure of the Energy Internet of Things, by normalizing the edge weights between different energy media and information media, the criticality of the network path composed of different business attributes in the Energy Internet of Things can be quantified, which is beneficial to the subsequent analysis of the energy network. Internet of things engineering construction.

Description of drawings

In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the accompanying drawings that need to be used in the description of the specific embodiments or prior art. Obviously, the accompanying drawings in the following description The figures show some implementations of the present application, and those skilled in the art can obtain other figures based on these figures without any creative effort.

Fig. 1 is a flowchart of a method for determining a critical path of an energy Internet of Things physical and information system provided by an embodiment of the present application;

Fig. 2 is a schematic diagram of the interaction between the physical side and the information side of an energy Internet of Things physical and information system provided by an embodiment of the present application;

Fig. 3 is a flowchart of another method for determining a critical path of an energy Internet of Things physical and information system provided by an embodiment of the present application;

FIG. 4 is a schematic diagram of a mapping relationship between the physical side and the information side of each network topology provided by the embodiment of the present application;

Fig. 5 is a flow chart of another method for determining the critical path of the energy Internet of Things physical and information system provided by the embodiment of the present application;

Fig. 6 is a flowchart of another method for determining a critical path of an energy Internet of Things physical and information system provided by an embodiment of the present application;

FIG. 7 is a structural block diagram of a critical path determination device for an energy Internet of Things physical and information system provided by an embodiment of the present application;

FIG. 8 is a schematic diagram of hardware of an electronic device provided by an embodiment of the present application.

Detailed ways

The technical solutions of the present application will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are some of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

In the description of the embodiments of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer " and other indicated orientations or positional relationships are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the embodiments of the present application and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, Constructed and operative in a particular orientation and therefore should not be construed as limiting to the embodiments of the present application. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and should not be construed as indicating or implying relative importance.

In the description of the embodiments of this application, it should be noted that unless otherwise specified and limited, the terms "installation", "connection", and "connection" should be understood in a broad sense, for example, it can be a fixed connection or a A detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be a direct connection or an indirect connection through an intermediary; it may also be an internal connection between two components, it may be a wireless connection, or is a wired connection. Those of ordinary skill in the art can understand the specific meanings of the above terms in the embodiments of the present application in specific situations.

In addition, technical features involved in different implementation manners in the embodiments of the present application described below may be combined as long as they do not constitute a conflict with each other.

An embodiment of the present application provides a method for determining a critical path of an energy Internet of Things physical and information system, as shown in FIG. 1 , including the following steps:

Step S11: Based on the adjacency matrices formed by the physical network topology, information network topology and interactive network topology of the target energy equipment, create a target adjacency matrix for the energy Internet of Things physical and information system.

The target energy equipment is the key component equipment for analyzing the physical and information systems of the energy Internet of Things. As shown in Figure 2, it includes production equipment 211, transmission equipment 212, and storage conversion equipment 213 on the physical side 21, and collection equipment 221 on the information side 22. Transmission device 222 and analysis processing device 223 . In FIG. 2 , the production equipment 211 on the physical side 21 includes gas turbines, wind power generators, photovoltaic panels, and oil and gas plants; the transmission equipment 212 on the physical side includes common power transmission networks, gas pipelines, and heating pipe networks; Storage conversion equipment 213 includes daily lighting loads, daily air-conditioning loads, daily refrigerator loads, electric vehicle charging, energy storage, and heat storage. The collection equipment 221 on the information side 22 includes equipment such as status operation and energy collection, the transmission equipment 222 on the information side 22 includes equipment such as power communication networks, optical fiber communication networks, and wireless communication networks, and the analysis and processing equipment 223 on the information side 22 includes Dispatching center, master station and other equipment. Physical network topology, information network topology and interactive network topology are network topology structures formed by nodes and node edges.

In one embodiment, as shown in Figure 3, the above step S11 creates the target adjacency matrix of the physical and information system of the Energy Internet of Things based on the adjacency matrices formed by the physical network topology, information network topology and interactive network topology of the target energy equipment ,include:

Step S111: Divide the energy Internet of Things physical and information system into two parts, the physical side and the information side.

In Fig. 2, the energy Internet of Things physical and information system is divided into two parts: the physical side 21 and the information side 22.

Step S112: Determine the target energy equipment from the physical side and the information side respectively.

The target energy equipment is the key component equipment mentioned above for analyzing the physical and information systems of the energy Internet of Things.

Step S113: Acquiring physical or informational characteristics or physical and informational interaction characteristics of the target energy equipment.

For example: physical characteristics include: cooling characteristics or heating characteristics or power supply characteristics or air supply characteristics, information characteristics include: processing characteristics and/or communication characteristics and/or acquisition characteristics, physical and information interaction characteristics include: from the physical side The characteristics of the transmission from the information side or from the information side to the physical side.

Step S114: Determine the mapping characteristics between the identification information of the target energy equipment and the node numbers of the physical network topology, the information network topology and the interactive network topology.

According to the mapping relationship between the identification information of the target energy device and the node numbers of the physical network topology, information network topology and interactive network topology, determine the attribute information of the target energy device mapped in the physical network topology, information network topology and interactive network topology.

Fig. 4 is a schematic diagram of the mapping relationship between the network topology between the physical side and the information side provided by the embodiment of the present application. As shown in Fig. 4, the schematic diagram of the mapping relationship includes: a gas generator 41 identified as GT01;

As shown in Figure 4, the schematic diagram includes a mapping relationship diagram between the nodes between the physical side and the information side, wherein,

The left side of the schematic diagram is the physical side mapping relationship between the gas generator 41 and the heating pipeline 42, the power transmission network 43 and the gas network 44;

The right side of the schematic diagram is the information side map between the identification GT01 corresponding to the gas generator 41 and the output power n1, cooling form n2 and boiler efficiency n3 of the gas generator 41;

The mapping relationship below the schematic diagram is a one-to-one mapping relationship between the ID (GT01) of the target energy device (gas generator 41) and the node number (neighbor node and attribute), wherein the neighbor node includes at least a heating pipeline 42. The power transmission network 43 and the gas network 44, the attributes at least include output power n1, cooling form n2 and boiler efficiency n3. In this way, based on the one-to-one mapping relationship between the ID of the target energy device and the node number, it has a common, unified and consistent semantics in the context of the physical and information system of the Energy Internet of Things, and the information sharing and exchange interface and services need to be standardized.

Step S115: According to the physical characteristics or information characteristics of the target energy equipment or the interaction characteristics between physics and information, the mapping characteristics between the identification information of the target energy equipment and the node numbers of the physical network topology, information network topology and interactive network topology, Create physical network topologies, information network topologies, and interactive network topologies.

For example: based on the physical information of the cooling or heating characteristics or power supply or gas supply characteristics of the target energy equipment, as well as the information on the processing characteristics and/or communication characteristics and/or collection characteristics of the target energy equipment, combined with the information of the target energy equipment The mapping characteristics between the identification information and the node numbers of the physical network topology, information network topology and interactive network topology are mapped on the physical network topology, information network topology and interactive network topology, so that each network topology has attribute information.

The physical network topology can be expressed by the following formula (1):

G _physical ＝{N _grid ,N _gas ,N _heating ,N _cooling ,E _grid ,E _gas ,E _heating ,E _cooling } (1);

Among them, N _grid is the power supply node, N _gas is the gas supply node, N _heating is the heating node, N _cooling is the cooling node, E _grid is the power supply connection side, E _gas is the gas supply connection side, E _heating is the heating connection side , E _cooling is for cooling side.

The information network topology can be expressed by the following formula (2):

G _cyber = {N _cyber , E _cyber } (2);

Among them, N _cyber is an information node, and E _cyber is an information connection edge.

The interactive network can be expressed by the following formula (3):

G _inter ＝{N _physical , N _cyber , E _{cyber→physical} , E _{physical→cyber} } (3);

Wherein, N _physical is a physical node, N _cyber is an information node, E _{cyber→physical} is an information node pointing to a physical node, and E _{physical→cyber} is a physical node pointing to an information node.

Mapping the target energy equipment in the physical network topology, information network topology and interactive network topology can better understand the status information of different energy media on the physical side and the information side and the interaction information between information media.

In one embodiment, the above step S11, based on the adjacency matrices formed by the physical network topology, information network topology and interactive network topology of the target energy equipment, creates the target adjacency matrix of the energy IoT physical and information system, including:

Step 1: Determine the adjacency matrices formed based on the physical network topology, information network topology, and interactive network topology. Each element of each adjacency matrix is the edge weight between nodes in the physical network topology, information network topology, or interactive network. If there is no connection relationship between each node, each element of each adjacency matrix is zero.

Step 2: Arrange the adjacency matrices to form the target adjacency matrix of the energy Internet of Things physical and information system.

As shown in Table 1 below, it is the target adjacency matrix of the energy Internet of Things physical and information system.

Table 1

In Table 1, A _ecps is the adjacency matrix of the energy Internet of Things physical and information system, A _cyber is the adjacency matrix of the information network topology, A _cyber→grid is the adjacency matrix from information nodes to physical nodes in the interactive network topology, and A _{cyber →gas} is the adjacency matrix from the information node to the gas supply node in the interactive network topology, A _{cyber→heating is} the adjacency matrix from the information node to the heating node in the interactive network topology, A _{cyber→cooling} is the adjacency matrix from the information node to the interactive network topology Pointing to the adjacency matrix of the cooling node, A _{grid → cyber} is the adjacency matrix from the power supply node to the information node in the interactive network topology, A _grid is the adjacency matrix of the power supply node in the physical network topology, A _{grid → gas} is the adjacency matrix of the interactive network topology by The adjacency matrix from power supply nodes to gas supply nodes, A _{grid→heating is} the adjacency matrix from power supply nodes to heating nodes in the interactive network topology, A _{grid→cooling} is the adjacency matrix from power supply nodes to cooling nodes in the interactive network topology, A _gas→cyber is the adjacency matrix from the gas supply node to the information node in the interactive network topology, A _gas→grid is the adjacency matrix from the gas supply node to the power supply node in the interactive network topology, and A _gas is the gas supply in the physical network topology node, A _{gas→heating} is the adjacency matrix from the gas supply node to the heating node in the interactive network topology, A _{gas→cooling} is the adjacency matrix from the gas supply node to the cooling node in the interactive network topology, A _{heating→cyber} is the interactive network topology In the network topology, the adjacency matrix from the heating node to the information node, A _{heating→grid} is the adjacency matrix from the heating node to the power supply node in the interactive network topology, A _{heating→gas} is from the heating node to the gas supply in the interactive network topology The adjacency matrix of nodes, A _heating is the adjacency matrix of heating nodes in the interactive network topology, A _{heating→cooling} is the adjacency matrix from heating nodes to cooling nodes in the interactive network topology, A _{cooling→cyber} is the adjacency matrix of cooling nodes pointing to The adjacency matrix of information nodes, A _{cooling→grid} is the adjacency matrix from the cooling node to the power supply node, A _{cooling→gas} is the adjacency matrix from the cooling node to the gas supply node in the interactive network topology, A _{cooling→heating} is the interactive network topology In the adjacency matrix from the cooling node to the heating node, A _cooling is the adjacency matrix of the cooling node.

Among them, the adjacency matrix A _cyber of the energy Internet of Things physical and information system satisfies the following matrix expression (4):

in,

Represents the connection relationship between information node c1 and information node ci, which satisfies the following formula (5):

in,

The equal diagonal elements represent the self-loop situation of the information node. Generally, there is no self-loop, and the element is set to 0.

The adjacency matrix A _grid of the power supply nodes in the physical network topology satisfies the following matrix formula (6):

in,

Satisfy the following formula (7):

Similarly, the remaining adjacency matrices in Table 1 are arranged in a matrix format similar to A _cyber and A _grid , which will not be repeated here.

The adjacency matrices formed by the physical network topology, the information network topology and the interactive network topology are respectively: A _cyber , A _cyber→grid , A _cyber→gas , A _{cyber→heating} , A _{cyber→cooling} , A _grid→cyber , A _{grid→ gas} , A _{grid→heating} , A _{grid→cooling} , A _gas→cyber , A _gas→grid , A _gas , A gas→ _heating , A _{gas→cooling} , A _{heating→cyber} , A _{heating→grid} , A _{heating→gas} , A _heating , A _{heating→cooling} , A _{cooling→cyber} , A _{cooling→grid} , A _{cooling→gas} , A _{cooling→heating} , A _cooling , that is, the above-mentioned adjacency matrices are arranged according to the adjacency relationship shown in Table 1 above Matrix, in each adjacency matrix in Table 1, if there is no connection relationship between the nodes, the corresponding element is 0, that is, the corresponding adjacency matrix is a zero matrix, for example: there is no connection relationship between the cooling node and the heating node , the adjacency matrix of the interaction between the two is the zero matrix, that is, both A _{heating→cooling} and A _{cooling→heating} are zero matrices. For example, in practical applications, the gas supply network and the cooling network in the physical network topology are usually two independent systems. Therefore, the adjacency matrix A _{gas→cooling} and the adjacency matrix A _{cooling→heating} are also zero matrices. The reverse air supply from the heating system and the reverse power supply from the cooling system have no practical application at present, so A _{heating→cooling} and A _{cooling→heating} are also zero matrices.

Step S12, by normalizing the adjacency matrices formed by the physical network topology, the information network topology and the interactive network topology, to obtain the edge weights between nodes in the physical network topology, the information network topology and the interactive network topology.

The purpose of normalizing the physical network topology, information network topology and interactive network topology is to avoid the heterogeneity of the connection relationship between the physical side and the information side of the energy Internet of Things physical and information systems.

In one embodiment, as shown in FIG. 5, the above step S12 is to obtain the physical network topology, information network topology and and the edge weights between each node of the interactive network topology, including:

Step S121: Determine the adjacency matrix with cooling characteristics, heating characteristics, power supply characteristics, and gas supply characteristics in the physical network topology and the adjacency matrix with information characteristics in the information network topology.

In fact, in Table 1, the adjacency matrix of the physical network topology on the lower diagonal is determined in the adjacency matrix of the energy IoT physical and information system, namely A _cyber , A _grid , A _gas , A _heating , and A _cooling .

Step S122: Determine the largest element from the adjacency matrix with cooling, heating, power supply, and gas supply characteristics in the physical network topology and the adjacency matrix with information characteristics in the information network topology.

From the above-mentioned A _cyber , A _grid , A _gas , A _heating , and A _cooling , determine the largest element of the adjacency matrix. The physical attribute corresponding to the largest element is the edge weight between each node, that is, the largest element is the The maximum edge weight between .

Step S123: Using the remaining elements after removing the largest element from each element to divide by the largest element, update the adjacency matrix with cooling characteristics, heating characteristics, power supply characteristics, and gas supply characteristics in the physical network topology and the information in the information network topology. The adjacency matrix of the characteristics is used to obtain the edge weights between nodes of the physical network topology and information network topology.

For example: from the above-mentioned A _cyber , A _grid , A _gas , A _heating , and A _cooling , determine that the largest element of the adjacency matrix is a _r1r10 , at this time, you can use A _cyber , A _grid , A _gas , A _heating , and A The remaining elements in _cooling except a _r1r10 are divided by a _r1r10 to update A _cyber , A _grid , A _gas , A _heating , and A _cooling .

For example: the normalization of the adjacency matrix A _cyber , A _grid , A _gas , A _heating , and A _cooling is shown in the following pseudocode:

In another implementation, as shown in Figure 6, the above step S12 normalizes the adjacency matrices formed by the physical network topology, information network topology and interactive network topology to obtain the physical network topology, information network topology and the edge weights between each node of the interactive network topology, including:

Step S61 , acquiring uplink adjacency matrices or downlink adjacency matrices in the interactive network topology.

Step S62, obtaining the largest element in each adjacency matrix in the upper row or in each adjacency matrix in the lower row.

Step S63, use the adjacency matrices in the uplink or the adjacency matrices in the downlink to divide the remaining elements after removing the maximum element by the maximum element, and update the adjacency matrices in the uplink or downlink to obtain the relationship between the nodes of the interactive network. Even edge weights.

The adjacency matrix that interacts between the information side and the physical side, because the volume of uplink data and downlink data often differs greatly, therefore, the uplink adjacency matrix and downlink adjacency matrix need to be normalized separately. For example: the uplink adjacency matrix refers to the interaction matrix in which data is collected and transmitted from the physical side to the information side, for example: A _grid→cyber , A _gas→cyber , A _{heating→cyber} and A _{cooling→cyber} , which are normalized Then, use A _grid→cyber , A _gas→cyber , A _{heating→cyber} and A _{cooling→cyber} to divide each element by the maximum element to update The respective normalized values, of course, can also be obtained from the largest elements in the four downlink adjacency matrices, and then, using A _grid→cyber , A _gas→cyber , A _{heating→cyber} and A _{cooling→cyber} , each element is divided by The largest element to update the respective normalized value. For example: A _grid→cyber , A _gas→cyber , A _{heating→cyber} and A _{cooling→cyber} in the interactive network, the pseudocode of the normalization process is as follows.

Step S13, according to the edge weights between nodes, determine the critical path in the physical network topology, information network topology and interactive network topology.

After the normalization processing in step S12 above, the state information of different energy media and the interaction information between information media in the adjacency matrices of the above physical network topology, information network topology and interactive network topology are simpler and more orderly. On this basis, further, it is easier to determine the criticality of the network paths composed of different business attributes in the Energy Internet of Things.

In one embodiment, the above step S13, according to the edge weights between the nodes, determines the critical path in the physical network topology, information network topology and interactive network topology can be performed by the following formula (8):

For example: if the path P _ij with the least number of hops between node i and node j is formed by sequentially connecting nodes {i,n ₁ ,n ₂ ,...,n _k ,j}, the hop number is k+1.

Among them, P _ij is the key path in the physical network topology or information network topology or interactive network topology, a _i1 is the normalized edge weight between node i and node 1, and a _i2 is the link between node i and node 2. The edge weight after inter-normalization processing, a _k-1k is the normalized edge weight between node k-1 and node k, and a _kj is the normalized edge weight between node k and node j The edge weight of k+1 is the number of hops between any two nodes.

Among them, a _i1 and so on are the weights of connected edges after normalization. It can be seen that the criticality of the critical path P _ij is the geometric mean of the normalized weights of the edges that make up the path. If there are two or more paths with the least number of hops between node i and node j, take the path with the highest criticality as the least-hop critical path of the two nodes, that is, this path will be the key to the least number of hops in the physical and information system of the Energy Internet of Things path.

For example: if any two nodes of physical network topology or information network topology or interactive network topology are adjacent nodes, the corresponding hop count is 1, adjacent nodes and the two nodes are not directly connected, then the hop between any two network nodes The number is 2.

Quantifying the critical path in the embodiment of the present application is beneficial to the subsequent engineering construction or engineering analysis of the physical and information system of the Energy Internet of Things.

The method for determining the critical path of the physical and information system of the Energy Internet of Things in the embodiment of the present application can be based on the topological structure of the Energy Internet of Things, and by normalizing the connection weights between different energy media and information media, the energy Internet of Things can be quantified. The criticality of the network path composed of different business attributes is ultimately beneficial to the subsequent construction of the energy Internet of Things.

Based on the same idea, the embodiment of the present application also provides a critical path determination device for the physical and information system of the Energy Internet of Things, as shown in Figure 7, including the following modules:

The adjacency matrix determination module 71 is configured to create a target adjacency matrix of the energy Internet of Things physical and information system based on each adjacency matrix formed by the physical network topology, information network topology and interactive network topology of the target energy equipment;

The normalization processing module 72 is configured to perform normalization processing on each adjacency matrix formed by the physical network topology, the information network topology and the interaction network topology in the target adjacency matrix, so as to obtain the Edge weights between nodes in the physical network topology, the information network topology, and the interactive network topology;

The critical path determination module 73 is configured to determine critical paths in the physical network topology, the information network topology and the interactive network topology according to the weights of the edges between the nodes.

In one embodiment, the physical network topology, information network topology and interactive network topology of the target energy equipment in the adjacency matrix determination module 71 are created through the following modules:

The information division sub-module is configured to divide the energy Internet of Things physical and information system into two parts: the physical side and the information side;

The equipment determination submodule is configured to determine the target energy equipment from the physical side and the information side respectively;

The characteristic acquisition sub-module is configured to acquire the physical characteristics or information characteristics or the interaction characteristics of physics and information possessed by the target energy equipment;

A mapping characteristic determining submodule configured to determine the mapping characteristic between the identification information of the target energy device and the node number of the physical network topology, the information network topology and the interactive network topology;

The network topology creation sub-module is configured to be based on the physical characteristics or information characteristics of the target energy equipment or the interactive characteristics of physics and information, the identification information of the target energy equipment, and the node number of the physical network topology, information network topology, and interactive network topology. Mapping features among them to create physical network topology, information network topology and interactive network topology.

In one embodiment, the physical characteristics include: cooling characteristics or heating characteristics or power supply characteristics or air supply characteristics, information characteristics include: processing characteristics and/or communication characteristics and/or collection characteristics, and physical and information interaction characteristics include : The characteristic transmitted from the physical side to the information side or the characteristic transmitted from the information side to the physical side.

In one embodiment, the adjacency matrix determination module 71 includes:

Each adjacency matrix determination sub-module is configured to determine each adjacency matrix formed based on physical network topology, information network topology and interactive network topology, and each element of each adjacency matrix is between each node of physical network topology or information network topology or interactive network The edge weight of , if there is no connection relationship between the nodes, each element of each adjacency matrix is zero;

The adjacency matrix arrangement submodule is configured to arrange the adjacency matrices to form the target adjacency matrix.

In one embodiment, the normalization processing module 72 includes:

The physical network topology adjacency matrix determination submodule is configured to determine the adjacency matrix with cooling characteristics, heating characteristics, power supply characteristics, and gas supply characteristics in the physical network topology and the adjacency matrix with information characteristics in the information network topology;

The first element determination sub-module is configured to determine the maximum element;

The first matrix update submodule is configured to use the remaining elements removed from each element to divide the maximum element by the maximum element, and update the adjacency matrix with cooling characteristics, heating characteristics, power supply characteristics, and gas supply characteristics in the physical network topology and The adjacency matrix with information characteristics in the information network topology is used to obtain the edge weights between nodes in the physical network topology and information network topology.

In one embodiment, the normalization processing module 72 includes:

Each adjacency matrix acquisition submodule is configured to acquire each uplink adjacency matrix or downlink adjacency matrix in the interactive network topology;

The second element determination submodule is configured to obtain the maximum element in each adjacency matrix of the uplink or each adjacency matrix of the downlink;

The second matrix updating submodule is configured to use the remaining elements in each of the uplink adjacency matrices or downlink adjacency matrices to divide the remaining elements by the maximum element respectively, and update the uplink or downlink adjacency matrices to obtain the interaction network The edge weights between each node of .

In one embodiment, the critical path determination module 73 determines the critical path in the physical network topology, the information network topology and the interactive network topology according to the weight of the connection between the nodes by the following formula:

The embodiment of the present application also provides an electronic device. As shown in FIG. 8, the electronic device may include a processor 81 and a memory 82, wherein the processor 81 and the memory 82 may be connected through a bus or in other ways. In FIG. Take the bus connection as an example.

The processor 81 may be a central processing unit (Central Processing Unit, CPU). Processor 81 can also be other general processors, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-Programmable Gate Array, FPGA) or Other chips such as programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above-mentioned types of chips.

The memory 82, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs and modules. The processor 81 executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory 82, that is, realizes the physical and information system of the energy Internet of Things in the above method embodiments. Critical path determination method.

The memory 82 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application program required by at least one function; the data storage area may store data created by the processor 81 and the like. In addition, the memory 82 may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory 82 may optionally include a memory that is remotely located relative to the processor 81, and these remote memories may be connected to the processor 81 through a network. Examples of the aforementioned networks include, but are not limited to, power grids, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The one or more modules are stored in the memory 82, and when executed by the processor 81, execute the method for determining the critical path of the energy Internet of Things physical and information system in the embodiment shown in the drawings.

Specific details of the above-mentioned electronic device can be understood by referring to corresponding descriptions and effects in the embodiments shown in the accompanying drawings, and details are not repeated here.

Those skilled in the art can understand that all or part of the processes in the methods of the above-mentioned embodiments can be completed by instructing related hardware through computer programs, and the programs can be stored in a computer-readable storage medium. During execution, it may include the processes of the embodiments of the above-mentioned methods. Wherein, the storage medium can be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a flash memory (Flash Memory), a hard disk (Hard Disk) Disk Drive, abbreviation: HDD) or solid-state hard drive (Solid-State Drive, SSD) etc.; The storage medium can also include the combination of above-mentioned types of memory.

Apparently, the above-mentioned embodiments are only examples for clear description, rather than limiting the implementation. For those of ordinary skill in the art, other changes or changes in different forms can be made on the basis of the above description. It is not necessary and impossible to exhaustively list all the implementation manners here. However, the obvious changes or changes derived therefrom are still within the protection scope of the invention of the present application.

Industrial Applicability

In this embodiment, based on the topological structure of the Energy Internet of Things, the criticality of network paths formed by different business attributes in the Energy Internet of Things can be quantified by normalizing the edge weights between different energy media and information media.

Claims

A method for determining a critical path of an energy Internet of Things physical and information system, comprising the following steps:

Based on the adjacency matrix composed of the physical network topology, information network topology and interactive network topology of the target energy equipment, create the target adjacency matrix of the energy Internet of Things physical and information system;

By performing normalization processing on each adjacency matrix formed by the physical network topology, the information network topology and the interaction network topology in the target adjacency matrix, the physical network topology, the information network topology and the Edge weights between nodes of the interactive network topology;

Determine critical paths in the physical network topology, the information network topology, and the interactive network topology according to the edge weights between the nodes.
The critical path determination method according to claim 1, wherein the physical network topology, information network topology and interactive network topology of the target energy equipment are created through the following steps:

Divide the energy Internet of Things physical and information system into two parts, the physical side and the information side;

determining the target energy device from the physical side and the information side respectively;

Obtaining the physical characteristics or information characteristics or the interaction characteristics between physics and information possessed by the target energy equipment;

determining a mapping characteristic between the identification information of the target energy device and the node numbers of the physical network topology, the information network topology, and the interaction network topology;

According to the physical characteristics or information characteristics of the target energy equipment or the interaction characteristics between physics and information, the identification information of the target energy equipment and the nodes of the physical network topology, the information network topology and the interactive network topology Mapping properties between numbers to create the physical network topology, the information network topology and the interactive network topology.
The critical path determination method according to claim 2, wherein the physical characteristics include: cooling characteristics or heating characteristics or power supply characteristics or air supply characteristics, and the information characteristics include: processing characteristics and/or communication characteristics and/or Or collection characteristics, the physical and information interaction characteristics include: characteristics transmitted from the physical side to the information side or characteristics transmitted from the information side to the physical side.
The method for determining the critical path according to claim 1, wherein the target adjacency matrix of the energy Internet of Things physical and information system is created based on the adjacency matrices formed by the physical network topology, information network topology and interactive network topology of the target energy equipment ,include:

determining each adjacency matrix formed based on the physical network topology, the information network topology, and the interaction network topology, each element of each adjacency matrix being the physical network topology or the information network topology or the interaction network The edge weights between each node of , if there is no connection relationship between each node, each element of each adjacency matrix is zero;

Arranging the adjacency matrices to form the target adjacency matrix.
The method for determining a critical path according to claim 1, wherein said normalizing the adjacency matrices formed by said physical network topology, said information network topology and said interactive network topology comprises:

Determine the adjacency matrix with cooling characteristics, heating characteristics, power supply characteristics, and gas supply characteristics in the physical network topology and the adjacency matrix with information characteristics in the information network topology;

determining the largest element from the adjacency matrix with cooling characteristics, heating characteristics, power supply characteristics, and gas supply characteristics in the physical network topology and the adjacency matrix with information characteristics in the information network topology;

Using the remaining elements that remove the maximum element from each element to divide by the maximum element respectively, update the adjacency matrix and all an adjacency matrix with information characteristics in the information network topology to obtain the edge weights between nodes in the physical network topology and the information network topology.
The method for determining a critical path according to claim 1, wherein said normalizing the adjacency matrices formed by said physical network topology, said information network topology and said interactive network topology comprises:

Acquiring the uplink adjacency matrices or the downlink adjacency matrices in the interactive network topology;

Obtaining the largest element in each of the adjacency matrices in the upper row or in the adjacency matrices in the lower row;

Using the adjacency matrices in the up row or the adjacency matrices in the down row, the remaining elements after removing the maximum element are respectively divided by the maximum element to update the adjacency matrices in the up row or down row, so as to obtain the The edge weight between each node of the interaction network.
The method for determining a critical path according to claim 1, wherein the critical path in the physical network topology, the information network topology, and the interactive network topology is determined according to the edge weights between the nodes , through the following formula:

Wherein, P ij is the critical path in the physical network topology or the information network topology or the interactive network topology, a i1 is the normalized edge weight between node i and node 1, a i2 is the normalized edge weight between node i and node 2, a k-1k is the normalized edge weight between node k-1 and node k, and a kj is The normalized edge weight between node k and node j, where k+1 is the number of hops between any two nodes.
A critical path determination device for an energy Internet of Things physical and information system, comprising the following modules:

The adjacency matrix determination module is configured as each adjacency matrix formed based on the physical network topology, information network topology and interactive network topology of the target energy equipment, and creates the target adjacency matrix of the energy Internet of Things physical and information system;

A normalization processing module configured to perform normalization processing on each adjacency matrix formed by the physical network topology, the information network topology, and the interaction network topology in the target adjacency matrix to obtain the physical network Edge weights between nodes of the topology, the information network topology, and the interactive network topology;

The critical path determination module is configured to determine the critical path in the physical network topology, the information network topology and the interactive network topology according to the weights of the edges between the nodes.
The device according to claim 8, wherein the physical network topology, information network topology and interaction network topology of the target energy equipment in the adjacency matrix determination module are created by the following modules:

The information division sub-module is configured to divide the energy Internet of Things physical and information system into two parts: the physical side and the information side;

A device determining submodule configured to determine the target energy device from the physical side and the information side respectively;

The characteristic acquisition submodule is configured to acquire the physical characteristics or information characteristics or the interaction characteristics between physics and information possessed by the target energy equipment;

A mapping characteristic determining submodule configured to determine the mapping characteristic between the identification information of the target energy device and the node numbers of the physical network topology, the information network topology, and the interactive network topology;

The network topology creation submodule is configured to be based on the physical characteristics or information characteristics of the target energy equipment or the interaction characteristics between physics and information, the identification information of the target energy equipment, the physical network topology, and the information network topology and mapping properties between node numbers of the interactive network topology, creating the physical network topology, the information network topology and the interactive network topology.
The device according to claim 9, wherein the physical characteristics include: cooling characteristics or heating characteristics or power supply characteristics or air supply characteristics, and the information characteristics include: processing characteristics and/or communication characteristics and/or collection characteristics , the physical-information interaction characteristic includes: a characteristic transmitted from the physical side to the information side or a characteristic transmitted from the information side to the physical side.
The device according to claim 8, wherein the adjacency matrix determination module includes:

Each adjacency matrix determination submodule is configured to determine each adjacency matrix formed based on the physical network topology, the information network topology, and the interactive network topology, each element of each adjacency matrix is the physical network topology or the The edge weights between the nodes of the information network topology or the interactive network, if there is no connection relationship between the nodes, each element of the adjacency matrix is zero;

The adjacency matrix arrangement submodule is configured to arrange the adjacency matrices to form the target adjacency matrix.
The device according to claim 8, wherein the normalization processing module comprises:

The physical network topology adjacency matrix determination submodule is configured to determine the adjacency matrix with cooling characteristics, heating characteristics, power supply characteristics, and gas supply characteristics in the physical network topology and the adjacency matrix with information characteristics in the information network topology;

The first element determination submodule is configured to select elements from the adjacency matrix with cooling characteristics, heating characteristics, power supply characteristics, and air supply characteristics in the physical network topology and the adjacency matrix with information characteristics in the information network topology , determine the largest element;

The first matrix update submodule is configured to use the remaining elements except the largest element from the elements to divide by the largest element respectively, and update the cooling characteristics, heating characteristics, and power supply characteristics in the physical network topology , an adjacency matrix with gas supply characteristics and an adjacency matrix with information characteristics in the information network topology, so as to obtain the edge weights between nodes in the physical network topology and the information network topology.
The device according to claim 8, wherein the normalization processing module comprises:

Each adjacency matrix acquisition submodule is configured to acquire the uplink adjacency matrices or the downlink adjacency matrices in the interactive network topology;

The second element determination submodule is configured to obtain the largest element in the adjacency matrices in the uplink or in the adjacency matrices in the downlink;

The second matrix updating submodule is configured to use the remaining elements in the adjacency matrices in the uplink or in the adjacency matrices in the downlink to divide the remaining elements by the maximum element respectively, and update all the uplink or downlink adjacency matrices The above adjacency matrices are used to obtain the edge weights between the nodes of the interaction network.
The device according to claim 8, wherein the critical path determination module determines the critical path in the physical network topology, the information network topology and the interactive network topology according to the weight of the connection between each node through the following formula:

Wherein, P ij is the critical path in the physical network topology or the information network topology or the interactive network topology, a i1 is the normalized edge weight between node i and node 1, a i2 is the normalized edge weight between node i and node 2, a k-1k is the normalized edge weight between node k-1 and node k, and a kj is The normalized edge weight between node k and node j, where k+1 is the number of hops between any two nodes.
A computer-readable storage medium, the computer-readable storage medium stores computer instructions, and the computer instructions are configured to cause the computer to execute the energy Internet of Things physical and information system described in any one of claims 1 to 7 method for determining the critical path.
An electronic device, a memory and a processor, the memory and the processor are connected to each other in communication, computer instructions are stored in the memory, and the processor implements claims 1 to 1 by executing the computer instructions. The method for determining the critical path of the energy Internet of Things physical and information system described in any one of 7.
A computer program product, the computer program product includes one or more instructions, the one or more instructions are suitable for being loaded by a processor and executing the energy Internet of Things physical and electronic device according to any one of claims 1 to 7 Critical path determination method of information system.