CN114205214A - Power communication network fault identification method, device, equipment and storage medium - Google Patents
Power communication network fault identification method, device, equipment and storage medium Download PDFInfo
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- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
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- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
- H04L41/065—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis involving logical or physical relationship, e.g. grouping and hierarchies
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Abstract
The invention discloses a method, a device, equipment and a storage medium for identifying faults of a power communication network, wherein the method comprises the following steps: s1: identifying a key node set in the whole power communication network, and dividing the whole power communication network by adopting the correlation among nodes to form a plurality of communication area subnets; s2: according to network equipment connected with the power equipment, finding out areas divided by the power equipment corresponding to the communication area subnet, and establishing a mapping relation between the power equipment areas and the communication subnet areas; s3: finding out fault power equipment, finding out a power equipment region set containing the most fault equipment and a mapping relation between a power equipment region and a communication subnet region according to the fault power equipment, and finding out all possible fault communication subnet region sets; s4: and for each communication subnet area with possible faults, carrying out fault identification on the communication equipment by utilizing a fault correlation analysis two-layer model. The invention integrates the fault information of the power equipment to improve the accuracy of the fault identification of the communication network.
Description
Technical Field
The invention relates to the technical field of network fault identification, in particular to a method, a device, equipment and a storage medium for identifying a power communication network fault.
Background
The optical transmission network used as the power grid information communication 'highway' mainly bears the information bearing of various services such as power grid production and management, power dispatching, customer service and the like. With the rapid development of energy internet, smart grid and power grid informatization, the service volume borne by the power communication network is larger and larger, the service types are richer, and the service quality requirements are more diversified, so that the changes all put higher requirements on the planning of the optical transmission network.
At present, fault identification methods for a communication network of a power system are mostly based on the fault and alarm of the communication network, and the influence of the network fault of power equipment on the fault identification of the communication network is not considered. This may affect the diagnosis and identification of the power communication network fault in the actual environment, and cause the problems of low identification accuracy and low efficiency of the power communication network fault identification method in the prior art.
Disclosure of Invention
The invention aims to solve the technical problems that in the prior art, the electric power communication network fault identification method is mainly used for detecting faults and alarms of a communication network, and the problems of low identification accuracy and low efficiency caused by the fact that the influence of the network faults of electric power equipment on the fault identification of the communication network is not considered.
Therefore, in the invention, the power equipment network fault is directly reflected by the communication network fault in the actual environment, and the monitoring data analysis of the power equipment network fault node can play a key role in identifying the communication network fault. The invention aims to provide a method, a device, equipment and a storage medium for identifying faults of a power communication network, which fully consider the influence of the network faults of power equipment on the identification of the faults of the communication network and have high identification accuracy and high efficiency.
The invention is realized by the following technical scheme:
in a first aspect, the present invention provides a method for identifying a fault in a power communication network, the method including:
s1: identifying a key node set in the whole power communication network according to the communication network nodes and the communication network topological structure; dividing the whole power communication network by adopting the correlation among the nodes according to the key node set to form a plurality of communication area subnets;
s2: according to network equipment connected with the electric equipment, finding out areas divided by the electric equipment corresponding to the communication area subnet, and establishing a mapping relation between the electric equipment areas and the communication subnet areas;
s3: obtaining fault power equipment according to the network communication state of the power equipment; finding out the power equipment region set containing the most fault equipment according to the fault power equipment, finding out all possible fault communication subnet region sets according to the mapping relation between the power equipment region and the communication subnet region, and arranging the fault equipment regions in a reverse order according to the number of the contained fault equipment;
s4: and for each communication subnet area with possible faults, constructing a fault association analysis two-layer model by using the mapping relation between the power equipment area and the communication subnet area, and identifying the faults of each communication equipment in the communication subnet area.
The method integrates the fault information of the power equipment, improves the accuracy of fault identification of the communication network, simultaneously divides the key area sub-networks of the whole communication network, respectively identifies the faults aiming at the key area sub-networks, and improves the efficiency of fault identification.
Further, step S1 includes the following sub-steps:
s11: according to the communication network node and the communication network topology structure, the whole power communication network can be represented by an undirected graph G ═ V, E, wherein V represents the communication device node, and E represents the connection relation between the communication devices;
s12: identifying k key node sets S in the whole power communication network by adopting a centrality key node identification algorithm, and
minimizing the logarithm f (S) of the connected node after S is removed in the whole undirected graph G;
s13: and dividing the whole communication network into a plurality of communication area subnet sets Gt according to the identified key node set S by adopting a communication network node correlation method.
Further, in step S12, the equation of the pair f (S) of connected nodes after S is removed in the whole undirected graph G is:
in the formula, CiRepresenting G [ V \ S ] after S is removed from the whole undirected graph G]The ith connected component of (a) is,
is the number of nodes in the connected component S.
Further, the calculation formula of the communication network node correlation method in step S13 is as follows:
in the formula, AijRepresenting a communication node TiAnd a communication node TjThe number of failures occurring in the same time period; a represents the total number of faults occurring in the communication network; the larger the ratio, the higher the correlation of the two communication nodes. DijRepresents a node TiAnd node TjThe larger the value of the number of communications therebetween, the communication node T is indicatediAnd a communication node TjThe higher the relevance of (A); d denotes the total number of communications of the nodes in the entire communication sub-network.
When the correlation of the communication network nodes is greater than the set threshold, the two communication nodes belong to the same communication area subnet.
Further, the network communication states of the power devices in step S3 are obtained and then aggregated according to the period dimension.
Further, the two-layer fault correlation analysis model in step S4 is implemented by using a communication network fault node as a root network layer and a power equipment fault node as an association network layer according to the mapping relationship between the power equipment region and the communication subnet region, and implementing identification of each communication equipment fault in the communication subnet through a fault propagation relationship between the communication network fault node and the power equipment fault node.
In a second aspect, the present invention further provides a power communication network fault identification device, which supports the power communication network fault identification method, and the device includes:
the system comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring the network communication state of the power equipment in the power system and aggregating the network communication state of each power equipment according to the periodic dimension;
the communication area subnet constructing unit is used for identifying a key node set in the whole power communication network according to the communication network nodes and the communication network topological structure; dividing the whole power communication network by adopting the correlation among the nodes according to the key node set to form a plurality of communication area subnets;
the mapping relation construction unit of the power equipment region and the communication subnet region is used for finding out the region divided by the power equipment corresponding to the communication region subnet according to the network equipment connected with the power equipment, and establishing the mapping relation between the power equipment region and the communication subnet region;
the possible fault communication subnet area set identification unit is used for obtaining fault power equipment according to the network communication state of the power equipment; finding out the power equipment region set containing the most fault equipment according to the fault power equipment, finding out all possible fault communication subnet region sets according to the mapping relation between the power equipment region and the communication subnet region, and arranging the fault equipment regions in a reverse order according to the number of the contained fault equipment;
and the communication equipment fault identification unit is used for constructing a fault association analysis two-layer model for each communication subnet area with possible faults by utilizing the mapping relation between the power equipment area and the communication subnet area, and identifying the faults of each communication equipment in the communication subnet area.
Further, the communication area subnet constructing unit comprises a key node set subunit and a communication area subnet constructing subunit;
the key node aggregation subunit is configured to represent, according to a communication network node and a communication network topology structure, the entire power communication network by using an undirected graph G ═ V, E, where V represents a communication device node and E represents a connection relationship between communication devices; and identifying k key node sets S in the whole power communication network by adopting a centrality key node identification algorithm, wherein
Minimizing the logarithm f (S) of the connected node after S is removed in the whole undirected graph G;
and the communication area subnet constructing subunit is used for dividing the whole communication network into a plurality of communication area subnet sets Gt according to the identified key node set S and the key nodes by adopting a communication network node correlation method.
In a third aspect, the present invention provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the power communication network fault identification method when executing the computer program.
In a fourth aspect, the present invention further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the power communication network fault identification method.
Compared with the prior art, the invention has the following advantages and beneficial effects:
in the invention, the fact that the network fault of the power equipment is directly reflected by the fault of the communication network in the actual environment is considered, and the monitoring data analysis of the network fault node of the power equipment can play a key role in identifying the fault of the communication network. The invention aims to provide a method, a device, equipment and a storage medium for identifying faults of a power communication network, which fully consider the influence of the network faults of power equipment on the identification of the faults of the communication network and have high identification accuracy and high efficiency.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
fig. 1 is a flowchart of a method for identifying a fault in an electrical power communication network according to the present invention.
Fig. 2 is a structural diagram of a power communication network fault recognition device according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example 1
As shown in fig. 1, the invention relates to a method for identifying a fault of a power communication network, which comprises the following steps:
s1: identifying a key node set in the whole power communication network according to the communication network nodes and the communication network topological structure; dividing the whole power communication network by adopting the correlation among the nodes according to the key node set to form a plurality of communication area subnets; step S1 includes the following substeps:
s11: according to the communication network node and the communication network topology structure, the whole power communication network can be represented by an undirected graph G ═ V, E, wherein V represents the communication device node, and E represents the connection relation between the communication devices;
s12: the identification of the key nodes can be understood as that the connectivity of the nodes in the whole communication network is minimum after the key nodes are removed; then, the whole power communication network is identified by adopting a centrality key node identification algorithmK key node sets S, and
minimizing the logarithm f (S) of the connected node after S is removed in the whole undirected graph G; the formula of (f) is:
in the formula, CiRepresenting G [ V \ S ] after S is removed from the whole undirected graph G]The ith connected component of (a) is,
is the number of nodes in the connected component S.
S13: and according to the identified key node set S, dividing the whole communication network into a plurality of communication area subnet sets Gt { Gt1, Gt2 and … Gtn } according to the key nodes by adopting a communication network node correlation method. The calculation formula of the communication network node correlation method is as follows:
in the formula, AijRepresenting a communication node TiAnd a communication node TjThe number of failures occurring in the same time period; a represents the total number of faults occurring in the communication network; the larger the ratio, the higher the correlation of the two communication nodes. DijRepresents a node TiAnd node TjThe larger the value of the number of communications therebetween, the communication node T is indicatediAnd a communication node TjThe higher the relevance of (A); d denotes the total number of communications of the nodes in the entire communication sub-network.
When the correlation of the communication network nodes is greater than the set threshold, the two communication nodes belong to the same communication area subnet.
S2: all the electric power equipment are connected with the communication equipment nodes in the communication network, so that the communication area subnet to which the electric power equipment belongs can be determined, and therefore, according to the network equipment connected with the electric power equipment, the areas divided by the electric power equipment corresponding to the communication area subnet are found out, and the mapping relation Rtc (Gt, Qc) between the electric power equipment areas and the communication subnet areas is established, wherein Gt represents the communication area subnet set; qc denotes a set of power equipment;
s3: obtaining a fault power equipment set H according to the network communication state of the power equipment; finding out a power equipment region set containing most fault equipment according to fault power equipment, finding out all possibly faulted communication subnet region sets { < Gt, Qc > } according to a mapping relation Rtc between the power equipment region and the communication subnet region, and arranging the possibly faulted communication subnet region sets in a reverse order according to the contained fault equipment number; wherein:
the network communication state of the power equipment is obtained and then aggregated according to the cycle dimension. Specifically, in the whole power system, network monitoring devices are randomly arranged in the power equipment, the distribution of the network monitoring devices is uniform on the whole, the network monitoring devices are used for collecting network delay data of a current point and equipment communication conditions, and the network monitoring devices can include routers, switches, CDNs, information systems or network monitoring clients. The network monitoring device uploads the network state of each power device every second, and the data acquisition module aggregates the acquired original data according to the periodic dimensional data so as to reduce the data volume. The communication State of each equipment period dimension takes 0 or 1, 1 represents that the communication State of the equipment is normal, and 0 represents that the communication State of the equipment is abnormal.
S4: and for each communication subnet area with possible faults, constructing a fault association analysis two-layer model by using the mapping relation between the power equipment area and the communication subnet area, and identifying the faults of each communication equipment in the communication subnet area. Wherein:
and the two-layer fault correlation analysis model is used for identifying faults of each communication device in the communication area sub-network by taking the communication network fault node as a root network layer and taking the power device fault node as a correlation network layer according to the mapping relation between the power device area and the communication sub-network area and by taking the communication network fault node as the correlation network layer and the fault propagation relation between the communication network fault node and the power device fault node.
Specifically, the set of communication subnet areas for all possible failures identified in step S3<Gt,Qc>For each set, establishing a two-layer model G (T, E, C) of the power equipment and communication network fault association analysis, wherein T belongs to a node in a communication area subnet, a communication network fault node is used as a fault root network layer, C belongs to a node in a power equipment area, a power equipment fault node is used as a fault association network layer, E is an edge of the communication network subnet node pointing to the power equipment layer, and the specific meaning represents the influence of the communication network node fault on the power equipment; definition of wijIs an edge (T)i,Cj) And the weight represents the propagation probability of the communication network node fault to the power equipment node fault.
Identification of a set of failed nodes of a communication network can be converted into a set of communication devices X that find a failure in a communication area subnet, wherein
Enabling the actual occurrence of observable sets of faults of electrical equipment
Then the probability of this failure occurring is the greatest.
Further, the problem of probability of occurrence of the fault can be converted into the following minimization problem:
in the formula, K represents a K-dimensional vector xi，xi∈{0，1}，
The probability of failure for the ith communication device.
And solving the 0-1 planning problem by adopting a genetic algorithm, calculating the fault probability of each communication device, and selecting the communication device exceeding a threshold value as a fault communication device. Therefore, the method can find out the fault communication equipment node set X, and the purpose of identifying the fault of the power communication network is achieved.
The method integrates the fault information of the power equipment, improves the accuracy of fault identification of the communication network, simultaneously divides the key area sub-networks of the whole communication network, respectively identifies the faults aiming at the key area sub-networks, and improves the efficiency of fault identification.
Example 2
As shown in fig. 2, the present embodiment is different from embodiment 1 in that the present embodiment provides a power communication network fault identification device which supports a power communication network fault identification method described in embodiment 1, and the device includes:
the system comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring the network communication state of the power equipment in the power system and aggregating the network communication state of each power equipment according to the periodic dimension;
the communication area subnet constructing unit is used for identifying a key node set in the whole power communication network according to the communication network nodes and the communication network topological structure; dividing the whole power communication network by adopting the correlation among the nodes according to the key node set to form a plurality of communication area subnets;
the mapping relation construction unit of the power equipment region and the communication subnet region is used for finding out the region divided by the power equipment corresponding to the communication region subnet according to the network equipment connected with the power equipment, and establishing the mapping relation between the power equipment region and the communication subnet region;
the possible fault communication subnet area set identification unit is used for obtaining fault power equipment according to the network communication state of the power equipment; finding out the power equipment region set containing the most fault equipment according to the fault power equipment, finding out all possible fault communication subnet region sets according to the mapping relation between the power equipment region and the communication subnet region, and arranging the fault equipment regions in a reverse order according to the number of the contained fault equipment;
and the communication equipment fault identification unit is used for constructing a fault association analysis two-layer model for each communication subnet area with possible faults by utilizing the mapping relation between the power equipment area and the communication subnet area, and identifying the faults of each communication equipment in the communication subnet area.
The execution process of each unit may be executed according to the flow steps of the method for identifying a fault in an electric power communication network described in embodiment 1, and details are not repeated in this embodiment.
Meanwhile, the invention also provides a computer device which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the computer program to realize the power communication network fault identification method.
Meanwhile, the invention also provides a computer readable storage medium, which stores a computer program, and the computer program realizes the power communication network fault identification method when being executed by a processor.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A power communication network fault identification method is characterized by comprising the following steps:
s1: identifying a key node set in the whole power communication network according to the communication network nodes and the communication network topological structure; dividing the whole power communication network by adopting the correlation among the nodes according to the key node set to form a plurality of communication area subnets;
s2: according to network equipment connected with the electric equipment, finding out areas divided by the electric equipment corresponding to the communication area subnet, and establishing a mapping relation between the electric equipment areas and the communication subnet areas;
s3: obtaining fault power equipment according to the network communication state of the power equipment; finding out a power equipment region set containing most fault equipment according to fault power equipment, and finding out all communication subnet region sets with possible faults according to the mapping relation between the power equipment region and the communication subnet region;
s4: and identifying the fault of each communication device in the communication area subnet by utilizing a fault association analysis two-layer model for each communication subnet area with possible faults.
2. The power communication network fault identification method according to claim 1, wherein the step S1 includes the following sub-steps:
s11: according to the communication network node and the communication network topology structure, the whole power communication network is represented by an undirected graph G which is (V, E), wherein V represents the communication equipment node, and E represents the connection relation between the communication equipment;
s12: identifying k key node sets S in the whole power communication network by adopting a centrality key node identification algorithm, and
minimizing the logarithm f (S) of the connected node after S is removed in the whole undirected graph G;
s13: and dividing the whole communication network into a plurality of communication area subnet sets according to the identified key node set S by adopting a communication network node correlation method.
3. The method according to claim 2, wherein the equation of the pair f (S) of connected nodes with S removed in the whole undirected graph G in step S12 is as follows:
in the formula, CiRepresenting G [ V \ S ] after S is removed from the whole undirected graph G]The ith connected component of (a) is,
is the number of nodes in the connected component S.
4. The method for identifying the fault in the power communication network according to claim 2, wherein the calculation formula of the correlation method of the communication network nodes in the step S13 is as follows:
in the formula, AijRepresenting a communication node TiAnd a communication node TjThe number of failures occurring in the same time period; a represents the total number of faults occurring in the communication network; dijRepresenting a communication node TiAnd a communication node TjThe number of communications therebetween; d denotes the total number of communications of the nodes in the entire communication sub-network.
5. The method for identifying the fault in the power communication network as claimed in claim 1, wherein the network communication states of the power devices in the step S3 are obtained and then aggregated according to the periodic dimension.
6. The method according to claim 1, wherein the two-layer fault correlation analysis model in step S4 is implemented by using a communication network fault node as a root network layer and a power equipment fault node as a correlation network layer according to a mapping relationship between the power equipment region and the communication subnet region, and implementing identification of each communication equipment fault in the communication region subnet through a fault propagation relationship between the communication network fault node and the power equipment fault node.
7. An electric power communication network fault identification device, characterized in that the device supports an electric power communication network fault identification method according to any one of claims 1 to 6, and the device comprises:
the acquisition unit is used for acquiring the network communication state of the power equipment in the power system and aggregating the network communication state of the power equipment according to the periodic dimension;
the communication area subnet constructing unit is used for identifying a key node set in the whole power communication network according to the communication network nodes and the communication network topological structure; dividing the whole power communication network by adopting the correlation among the nodes according to the key node set to form a plurality of communication area subnets;
the mapping relation construction unit of the power equipment region and the communication subnet region is used for finding out the region divided by the power equipment corresponding to the communication region subnet according to the network equipment connected with the power equipment, and establishing the mapping relation between the power equipment region and the communication subnet region;
the possible fault communication subnet area set identification unit is used for obtaining fault power equipment according to the network communication state of the power equipment; finding out a power equipment region set containing most fault equipment according to fault power equipment, and finding out all communication subnet region sets with possible faults according to the mapping relation between the power equipment region and the communication subnet region;
and the communication equipment fault identification unit is used for identifying the fault of each communication equipment in the communication area subnet by utilizing a fault correlation analysis two-layer model for each communication subnet area with possible faults.
8. The power communication network fault identification device of claim 7, wherein the communication area subnet constructing unit comprises a key node set subunit and a communication area subnet constructing subunit;
the key node aggregation subunit is configured to represent, according to a communication network node and a communication network topology structure, the entire power communication network by using an undirected graph G ═ V, E, where V represents a communication device node and E represents a connection relationship between communication devices; and identifying k key node sets S in the whole power communication network by adopting a centrality key node identification algorithm, wherein
Minimizing the logarithm f (S) of the connected node after S is removed in the whole undirected graph G;
and the communication area subnet constructing subunit is used for dividing the whole communication network into a plurality of communication area subnet sets according to the key nodes by adopting a communication network node correlation method according to the identified key node set S.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements a power communication network failure identification method according to any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, implements a power communication network fault identification method according to any one of claims 1 to 6.
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| CN109743215A (en) * | 2019-03-05 | 2019-05-10 | 重庆邮电大学 | A kind of ant group optimization mapping method of virtual network based on disaster prediction under multizone failure |
| CN111835537A (en) * | 2019-04-17 | 2020-10-27 | 中国移动通信集团山西有限公司 | Method, device and equipment for identifying nodes in communication network cascade fault |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117093952A (en) * | 2023-10-19 | 2023-11-21 | 北京松岛菱电电力工程有限公司 | Intelligent control method and system based on operation state of power equipment |
| CN117093952B (en) * | 2023-10-19 | 2024-01-02 | 北京松岛菱电电力工程有限公司 | Intelligent control method and system based on operation state of power equipment |
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