CN107453786B - Method and device for establishing electric power communication network model - Google Patents

Method and device for establishing electric power communication network model Download PDF

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CN107453786B
CN107453786B CN201710859681.0A CN201710859681A CN107453786B CN 107453786 B CN107453786 B CN 107453786B CN 201710859681 A CN201710859681 A CN 201710859681A CN 107453786 B CN107453786 B CN 107453786B
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communication network
power communication
service
matrix
determining
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CN107453786A (en
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李莉
吴润泽
聂文海
樊冰
宋欣桐
沈卫东
唐良瑞
张海霞
万莹
宋堃
朱正甲
侯喆瑞
吕昕
张雅娜
李环媛
赵旷怡
赵敏
赵芃
孙涛
秦砺寒
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North China Electric Power University
Economic and Technological Research Institute of State Grid Jibei Electric Power Co Ltd
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North China Electric Power University
Economic and Technological Research Institute of State Grid Jibei Electric Power Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B3/00—Line transmission systems
    • H04B3/54—Systems for transmission via power distribution lines

Abstract

The invention provides a method and a device for establishing a power communication network model, and relates to the technical field of power communication systems. The method comprises the following steps: acquiring a network model structure and service distribution condition data of a power communication network to be processed; determining a link capacity matrix and a service connection matrix, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix; determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix; determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow; and correspondingly setting each importance judgment value and each power communication network node in the network model structure of the power communication network to be processed to form a power communication network model with each power communication network node added with the importance judgment value.

Description

Method and device for establishing electric power communication network model
Technical Field
The invention relates to the technical field of power communication systems, in particular to a power communication network model establishing method and device.
Background
Currently, the power communication network is an important support network for ensuring the safe operation of the power system, and the reliability of the power communication network is closely related to the reliability of the power system. Due to the continuous expansion of the scale of the power grid, the grid structure of the power communication network is gradually complicated, the carried traffic is also increased, the safety risk and the handling difficulty are increased, and a reasonable reliability evaluation scheme is necessary for the safe and stable operation of the communication network.
As a private communication network of an electric power system, various services are carried on the electric power communication network, and service flows carried by different nodes are also different. The service importance reflects the influence degree of the power service on the power system and the communication environment requirement of the service, and is an important index for risk assessment of the power communication service. The importance of the node is not very accurate from the perspective of single service, and the importance of low-importance service with large flow and the importance of medium-importance service with small flow cannot be directly compared. Therefore, how to comprehensively determine the importance of the node from two dimensions of transmission flow and bearer service, and construct a power communication network model based on the importance, so as to evaluate the reliability of the power communication network or calculate the risk of the power communication network becomes a problem to be solved urgently.
Disclosure of Invention
Embodiments of the present invention provide a method and an apparatus for establishing a power communication network model, so as to solve the problems that in the prior art, it is not very accurate to measure the importance of a node from a business perspective, it is difficult to comprehensively determine the importance of the node from two dimensions of transmission flow and bearer business, and a power communication network model is established based on the importance to evaluate the reliability of a power communication network or calculate the risk of the power communication network.
In order to achieve the purpose, the invention adopts the following technical scheme:
a power communication network model building method comprises the following steps:
acquiring a network model structure and service distribution condition data of a power communication network to be processed; the network model structure of the electric power communication network to be processed comprises each electric power communication network node, each electric power communication network link and each link capacity; the service distribution condition data comprises service types corresponding to the power communication network nodes and service importance degrees of the service types;
determining a link capacity matrix and a service connection matrix according to a network model structure of the electric power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix;
determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix;
determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow;
and correspondingly setting each importance degree judgment value and each power communication network node in a network model structure of the power communication network to be processed to form a power communication network model with each power communication network node added with the importance degree judgment value.
Specifically, determining a link capacity matrix and a service connection matrix according to a network model structure of the power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix, includes:
determining a link capacity matrix A according to a network model structure of a power communication network to be processed; wherein A ═ aij]N×N(ii) a N is the total number of the nodes of the power communication network; a isijFor the link capacity of the power communication network link between power communication network node i and power communication network node j, if no power communication network link exists between power communication network node i and power communication network node j, then aijIs 0;
determining a service contact matrix L under the service type u according to the service type corresponding to each power communication network nodeu(ii) a Wherein L isu＝[lij]N×N(ii) a If the service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝l ji1 is ═ 1; if no service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝lji＝0；
Determining a maximum flow matrix M of the first power communication network according to the link capacity matrix A; wherein, M ═ fij]N×N；fijThe maximum flow is obtained by taking the power communication network node i as a source node and the power communication network node j as a sink node;
according to the maximum flow matrix M of the power communication network and the service contact matrix L under the service type uuDetermining network traffic flow matrix V under traffic type uu(ii) a Wherein, Vu＝[vij]N×N，vij＝fij×lij。
Specifically, determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix includes:
deleting the kth row and the kth column in the link capacity matrix A to obtain a processed link capacity matrix corresponding to the power communication network node kkA*；
According to the processed link capacity matrixkA*Determining a maximum flow matrix for a second power communication networkkM*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000031
Figure BDA0001414777610000032
according to the processed link capacity matrixkA*Taking the power communication network node i as a source node and the power communication network node j as a sink node to obtain a maximum flow;
the business contact matrix L under the business type uuDeleting the kth row and the kth column to obtain a processed service contact matrix (corresponding to the power communication network node k)kLu)*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000033
maximum flow according to second power communication networkMatrix arraykM*And a processed business contact matrix (kLu)*Determining a network traffic flow matrix (with the power communication network node k removed) under the service type ukVu)*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000034
the network service flow matrix V under the service type u is processeduDeleting the k row and the k column in the network to obtain a processed network service flow matrixkVu；
According to the formula:
Figure BDA0001414777610000035
determining business flow betweenness of power communication network node k under business type u
Figure BDA0001414777610000036
Specifically, determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow includes:
service importance s according to each service typeuDetermining the weight w corresponding to each service typeu(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000037
according to the formula:
Figure BDA0001414777610000038
determining importance judgment value I of power communication network node kk。
A power communication network modeling apparatus comprising:
the data acquisition unit is used for acquiring a network model structure and service distribution condition data of a power communication network to be processed; the network model structure of the electric power communication network to be processed comprises each electric power communication network node, each electric power communication network link and each link capacity; the service distribution condition data comprises service types corresponding to the power communication network nodes and service importance degrees of the service types;
the network service flow matrix determining unit is used for determining a link capacity matrix and a service connection matrix according to a network model structure of the electric power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix;
the service flow betweenness determining unit is used for determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix;
the importance judgment value determining unit is used for determining the importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow;
and the electric power communication network model establishing unit is used for correspondingly setting each importance degree judgment value and each electric power communication network node in a network model structure of the electric power communication network to be processed to form an electric power communication network model with each electric power communication network node added with the importance degree judgment value.
Specifically, the network traffic flow matrix determining unit includes:
the link capacity matrix determining module is used for determining a link capacity matrix A according to a network model structure of the electric power communication network to be processed; wherein A ═ aij]N×N(ii) a N is the total number of the nodes of the power communication network; a isijFor the link capacity of the power communication network link between power communication network node i and power communication network node j, if no power communication network link exists between power communication network node i and power communication network node j, then aijIs 0;
a service contact matrix determining module for determining a service contact matrix L under the service type u according to the service type corresponding to each power communication network nodeu(ii) a Wherein L isu＝[lij]N×N(ii) a If a service exists between the power communication network node i and the power communication network node jThe service of type u is in the service contact matrix LuIn, lij＝l ji1 is ═ 1; if no service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝lji＝0；
The first power communication network maximum flow matrix determining module is used for determining a first power communication network maximum flow matrix M according to the link capacity matrix A; wherein, M ═ fij]N×N；fijThe maximum flow is obtained by taking the power communication network node i as a source node and the power communication network node j as a sink node;
a first network service flow matrix determining module, configured to determine a service contact matrix L according to the maximum flow matrix M of the power communication network and the service type uuDetermining network traffic flow matrix V under traffic type uu(ii) a Wherein, Vu＝[vij]N×N，vij＝fij×lij。
Specifically, the service flow betweenness determining unit includes:
a link capacity matrix processing module, configured to delete the kth row and the kth column in the link capacity matrix a to obtain a processed link capacity matrix corresponding to the power communication network node kkA*；
A second power communication network maximum flow matrix determination module for determining the processed link capacity matrix according to the processed link capacity matrixkA*Determining a maximum flow matrix for a second power communication networkkM*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000041
Figure BDA0001414777610000042
according to the processed link capacity matrixkA*Taking the power communication network node i as a source node and the power communication network node j as a sink node to obtain a maximum flow;
a business contact matrix processing module for processing the business contact matrixService contact matrix L under service type uuDeleting the kth row and the kth column to obtain a processed service contact matrix (corresponding to the power communication network node k)kLu)*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000051
a second network traffic flow matrix determination module for determining a maximum flow matrix according to a second power communication networkkM*And a processed business contact matrix (kLu)*Determining a network traffic flow matrix (with the power communication network node k removed) under the service type ukVu)*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000052
a network service flow matrix processing module for processing the network service flow matrix V under the service type uuDeleting the k row and the k column in the network to obtain a processed network service flow matrixkVu；
A service flow betweenness determining module, configured to:
Figure BDA0001414777610000053
determining business flow betweenness of power communication network node k under business type u
Figure BDA0001414777610000054
Specifically, the importance determination value determining unit includes:
a weight determining module for determining the service importance s according to each service typeuDetermining the weight w corresponding to each service typeu(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000055
the importance judgment value determining module is used for determining the importance judgment value according to a formula:
Figure BDA0001414777610000056
determining importance judgment value I of power communication network node kk。
The embodiment of the invention provides a method and a device for establishing a power communication network model, which comprises the steps of firstly obtaining a network model structure and service distribution condition data of a power communication network to be processed; then, determining a link capacity matrix and a service connection matrix according to a network model structure of the electric power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix; determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix; determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow; and correspondingly setting each importance degree judgment value and each power communication network node in a network model structure of the power communication network to be processed to form a power communication network model with each power communication network node added with the importance degree judgment value. Therefore, the embodiment of the invention can comprehensively judge the importance of the nodes from two dimensions of transmission flow and bearing service, and establish the electric power communication network model with the importance judgment value added to each electric power communication network node based on the importance judgment value, thereby facilitating the subsequent accurate evaluation of the reliability of the electric power communication network or the calculation of the risk of the electric power communication network, and solving the problem of model construction of future heavy load networks in the planning process of the electric power communication network.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a first flowchart of a power communication network model building method according to an embodiment of the present invention;
fig. 2 is a second flowchart of a power communication network model building method according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a power saving network power communication transmission backbone network according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a power communication network model building apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a power communication network model building apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for establishing a power communication network model, including:
step 101, obtaining a network model structure and service distribution data of a power communication network to be processed.
The network model structure of the electric power communication network to be processed comprises each electric power communication network node, each electric power communication network link and each link capacity; the service distribution condition data comprises service types corresponding to the power communication network nodes and service importance of the service types.
Step 102, determining a link capacity matrix and a service connection matrix according to a network model structure of the electric power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix.
And 103, determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix.
And step 104, determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow.
And 105, correspondingly setting each importance degree judgment value and each power communication network node in the network model structure of the power communication network to be processed to form a power communication network model with each power communication network node added with the importance degree judgment value.
The embodiment of the invention provides a power communication network model establishing method, which comprises the steps of firstly, acquiring a network model structure and service distribution condition data of a power communication network to be processed; then, determining a link capacity matrix and a service connection matrix according to a network model structure of the electric power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix; determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix; determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow; and correspondingly setting each importance degree judgment value and each power communication network node in a network model structure of the power communication network to be processed to form a power communication network model with each power communication network node added with the importance degree judgment value. Therefore, the embodiment of the invention can comprehensively judge the importance of the nodes from two dimensions of transmission flow and bearing service, and establish the electric power communication network model with the importance judgment value added to each electric power communication network node based on the importance judgment value, thereby facilitating the subsequent accurate evaluation of the reliability of the electric power communication network or the calculation of the risk of the electric power communication network, and solving the problem of model construction of future heavy load networks in the planning process of the electric power communication network.
In order to make those skilled in the art better understand the present invention, a more detailed embodiment is listed below, and as shown in fig. 2, an embodiment of the present invention provides a power communication network model building method, including:
step 201, obtaining a network model structure and service distribution data of a power communication network to be processed.
The network model structure of the electric power communication network to be processed comprises each electric power communication network node, each electric power communication network link and each link capacity; the service distribution condition data comprises service types corresponding to the power communication network nodes and service importance of the service types. Here, the power communication network nodes may be communication devices in a power communication network, and the power communication network links are typically optical cables between the nodes. Traffic handling various traffic types may be transmitted between the power communication network nodes. In the stage of planning the power communication network, the flow of various services transmitted by the nodes cannot be accurately predicted and can change along with the development of the power system, so that the reliability of the network needs to be improved.
Step 202, determining a link capacity matrix A according to a network model structure of the electric power communication network to be processed.
Wherein A ═ aij]N×N(ii) a N is the total number of the nodes of the power communication network, namely the number of all the nodes in the network model structure of the power communication network; a isijFor the link capacity of the power communication network link between power communication network node i and power communication network node j, if no power communication network link exists between power communication network node i and power communication network node j, then aijIs 0. Generally, the capacity of a communication link connected with a node needs to be defined according to the type of a power communication network node carrying communication service. According to the actual situation of the power communication network, the capacity of a link connected with a provincial dispatching node is the highest; the capacity of a communication link connected with a 500kV transformer substation or a local-city-level dispatching center is not lower than that of a communication link connected with a 220kV transformer substation; the capacity of the communication link connected with the 220kV substation should not be lower than the capacity of the communication link connected with the 110kV substation.
Step 203, determining a service contact matrix L under the service type u according to the service type corresponding to each power communication network nodeu。
Wherein L isu＝[lij]N×N；LuCan be expressed as
Figure BDA0001414777610000081
If the service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝l ji1 is ═ 1; if no service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝lji＝0。
And 204, determining a maximum flow matrix M of the first power communication network according to the link capacity matrix A.
Wherein, M ═ fij]N×N(ii) a M can be represented as
Figure BDA0001414777610000082
fijThe maximum flow is obtained by taking the power communication network node i as a source node and taking the power communication network node j as a sink node.
Step 205, according to the maximum flow matrix M of the power communication network and the business contact matrix L under the business type uuDetermining network traffic flow matrix V under traffic type uu。
Wherein, Vu＝[vij]N×N，vij＝fij×lij. Here VuCan be expressed as
Figure BDA0001414777610000083
Step 206, deleting the k-th row and the k-th column in the link capacity matrix A to obtain a processed link capacity matrix corresponding to the power communication network node kkA*。
Step 207, according to the processed link capacity matrixkA*Determining a maximum flow matrix for a second power communication networkkM*。
Wherein the content of the first and second substances,
Figure BDA0001414777610000091
Figure BDA0001414777610000092
according to the processed link capacity matrixkA*And taking the power communication network node i as a source node and the power communication network node j as a sink node to obtain the maximum flow.
Step 208, the business contact matrix L under the business type uuDeleting the kth row and the kth column to obtain a processed service contact matrix (corresponding to the power communication network node k)kLu)*。
Wherein the content of the first and second substances,
Figure BDA0001414777610000093
step 209, maximum flow matrix according to the second power communication networkkM*And a processed business contact matrix (kLu)*Determining a network traffic flow matrix (with the power communication network node k removed) under the service type ukVu)*。
Wherein the content of the first and second substances,
Figure BDA0001414777610000094
here, akVu)*Can be expressed as:
Figure BDA0001414777610000095
step 210, making the network service flow matrix V under the service type uuDeleting the k row and the k column in the network to obtain a processed network service flow matrixkVu。
Step 211, according to the formula:
Figure BDA0001414777610000096
determining service of power communication network node k under service type uNumber of streams
Figure BDA0001414777610000097
And step 212, determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow.
Here, this step 212 may be implemented as follows:
service importance s according to each service typeuDetermining the weight w corresponding to each service typeu(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000098
according to the formula:
Figure BDA0001414777610000099
determining importance judgment value I of power communication network node kk。
And 213, correspondingly setting each importance judgment value and each power communication network node in the network model structure of the power communication network to be processed to form a power communication network model with each power communication network node added with the importance judgment value.
The above steps 201 to 213 are described in detail with reference to a specific example:
taking a certain power-saving communication transmission backbone network local network as an example, the method provided by the embodiment of the invention is subjected to simulation verification. The simulation network topology structure G (V, E) is shown in fig. 3, and includes 14 nodes and 16 links, where node 1 is a provincial dispatching center (central dispatching), node 13 is a regional dispatching center (local dispatching), node 14 is a 220kV substation, and the rest of the nodes are 500kV substations, where nodes 2, 5, and 8 are aggregation nodes. The capacity of a communication link for carrying service transmission between the central dispatching node and the rest nodes is 12G, the capacity of the rest links is 10G, and no link with the capacity lower than 10G exists in the embodiment because no link from a 220kV transformer substation to a 220kV/110kV transformer substation exists. The service distribution in the network is shown in the following table 1 (1 indicates that the service exists, and 0 indicates that the service does not exist):
table 1:
Figure BDA0001414777610000101
according to the prior art (fan ice, tang liang, power communication network vulnerability analysis [ J ]. china motor engineering report, 2014, (07): 1191-:
table 2:
Figure BDA0001414777610000111
the node importance ranking calculated by the method of the embodiment of the invention is shown in the following table 3:
table 3:
Figure BDA0001414777610000112
Figure BDA0001414777610000121
the node importance calculated by the method of the embodiment of the invention and the existing weighted node shrinkage method and triangular mold fusion method is compared and analyzed, and the results are shown in the following table 4:
table 4:
Figure BDA0001414777610000122
the simulation results show that:
compared with a weighted node contraction method and a triangular model fusion method, the method provided by the embodiment of the invention calculates the node importance of the network by considering the service distribution on the network layer to construct a service connection matrix and combining the maximum flow matrix on the network transmission layer, and the evaluation result not only considers the importance distribution of the service in the network, but also considers the traffic distribution of the service, so that the importance of the node in the network is accurately estimated from two dimensions.
As can be seen from the simulation results of the network shown in FIG. 3, node v1The load bearing traffic is larger than other nodes and has traffic with more nodes, and the node v is considered comprehensively1Should be larger than other nodes, the weighted node contraction method only considers the importance of the nodes on the topological level, and the result shows the node v2Ratio node v1Important, not in line with the fact. The node v obtained by the method of the embodiment of the invention1The importance value is maximum, and the difference between the importance and the second importance node is large, so that the position of the middle adjusting point is reflected. Therefore, the method provided by the embodiment of the invention has more rationality on the evaluation result of the importance of the power communication network node.
Node v2,v5,v13For a sink node, when a node contraction method and a triangular mode fusion method are applied, the importance of the sink node relative to other 500kV nodes cannot be reflected, and the evaluation result obtained by the method provided by the embodiment of the invention is that the node v is2,v5,v13The importance value is large, the characteristics of large service flow of the sink node and high importance in the network can be reflected, and the importance value is consistent with the actual situation.
In summary, embodiments of the present invention provide a method for establishing a power communication network model, which can comprehensively determine the importance of nodes from two dimensions of transmission flow and bearer service, and establish a power communication network model with importance determination values attached to each power communication network node based on the importance determination values, so as to facilitate subsequent accurate evaluation of reliability of a power communication network or calculation of risk of a power communication network, thereby solving a problem of model construction of a future heavy load network in a power communication network planning process.
Corresponding to the method embodiments corresponding to fig. 1 and fig. 2, as shown in fig. 4, an embodiment of the present invention provides an electric power communication network model building apparatus, including:
the data acquisition unit 31 is configured to acquire a network model structure and service distribution data of an electric power communication network to be processed; the network model structure of the electric power communication network to be processed comprises each electric power communication network node, each electric power communication network link and each link capacity; the service distribution condition data comprises service types corresponding to the power communication network nodes and service importance of the service types.
And the network service flow matrix determining unit 32 is configured to determine a link capacity matrix and a service connection matrix according to the network model structure of the power communication network to be processed and the service distribution condition data, and determine a network service flow matrix according to the link capacity matrix and the service connection matrix.
And a service flow betweenness determining unit 33, configured to determine a service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service connection matrix, and the network service flow matrix.
And an importance judgment value determining unit 34, configured to determine an importance judgment value of each power communication network node according to the service importance of each service type and the number of service flows.
And an electric power communication network model establishing unit 35, configured to set each importance degree determination value in correspondence with each electric power communication network node in the network model structure of the electric power communication network to be processed, so as to form an electric power communication network model in which the importance degree determination value is added to each electric power communication network node.
Specifically, as shown in fig. 5, the network traffic flow matrix determining unit 32 includes:
a link capacity matrix determining module 321, configured to determine a link capacity matrix a according to a network model structure of the power communication network to be processed; wherein A ═ aij]N×N(ii) a N is the total number of the nodes of the power communication network; a isijFor the link capacity of the power communication network link between power communication network node i and power communication network node j, if no power communication network link exists between power communication network node i and power communication network node j, then aijIs 0.
A service connection matrix determination module 322 for determining the network connection according to the node pair of the power communication networkDetermining a service contact matrix L under the service type u according to the service typeu(ii) a Wherein L isu＝[lij]N×N(ii) a If the service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝l ji1 is ═ 1; if no service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝lji＝0。
A first power communication network maximum flow matrix determining module 323, configured to determine a first power communication network maximum flow matrix M according to the link capacity matrix a; wherein, M ═ fij]N×N；fijThe maximum flow is obtained by taking the power communication network node i as a source node and taking the power communication network node j as a sink node.
A first network traffic flow matrix determining module 324, configured to determine a traffic contact matrix L according to the maximum flow matrix M and the traffic type u of the power communication networkuDetermining network traffic flow matrix V under traffic type uu(ii) a Wherein, Vu＝[vij]N×N，vij＝fij×lij。
Specifically, as shown in fig. 5, the service flow betweenness determining unit 33 includes:
a link capacity matrix processing module 331, configured to delete the kth row and the kth column in the link capacity matrix a to obtain a processed link capacity matrix corresponding to the power communication network node kkA*。
A second power communication network maximum flow matrix determining module 332, configured to determine a link capacity matrix according to the processed link capacity matrixkA*Determining a maximum flow matrix for a second power communication networkkM*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000141
Figure BDA0001414777610000142
is based onProcessed link capacity matrixkA*And taking the power communication network node i as a source node and the power communication network node j as a sink node to obtain the maximum flow.
A business contact matrix processing module 333, configured to apply the business contact matrix L under the business type uuDeleting the kth row and the kth column to obtain a processed service contact matrix (corresponding to the power communication network node k)kLu)*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000143
a second network traffic flow matrix determination module 334, configured to determine a maximum flow matrix according to a second power communication networkkM*And a processed business contact matrix (kLu)*Determining a network traffic flow matrix (with the power communication network node k removed) under the service type ukVu)*(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000151
a network traffic flow matrix processing module 335, configured to apply the network traffic flow matrix V under the traffic type uuDeleting the k row and the k column in the network to obtain a processed network service flow matrixkVu。
A traffic flow betweenness determining module 336, configured to:
Figure BDA0001414777610000152
determining business flow betweenness of power communication network node k under business type u
Figure BDA0001414777610000153
Specifically, as shown in fig. 5, the importance determination value determining unit 34 includes:
a weight determining module 341, configured to determine the service importance s according to each service typeuDetermining the weight w corresponding to each service typeu(ii) a Wherein the content of the first and second substances,
Figure BDA0001414777610000154
an importance judgment value determining module 342, configured to:
Figure BDA0001414777610000155
determining importance judgment value I of power communication network node kk。
It should be noted that, for a specific implementation manner of the power communication network model establishing apparatus provided in the embodiment of the present invention, reference may be made to the method embodiments corresponding to fig. 1 and fig. 2, and details are not described here again.
The embodiment of the invention provides a power communication network model establishing device, which comprises the following steps of firstly, acquiring a network model structure and service distribution condition data of a power communication network to be processed; then, determining a link capacity matrix and a service connection matrix according to a network model structure of the electric power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix; determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix; determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow; and correspondingly setting each importance degree judgment value and each power communication network node in a network model structure of the power communication network to be processed to form a power communication network model with each power communication network node added with the importance degree judgment value. Therefore, the embodiment of the invention can comprehensively judge the importance of the nodes from two dimensions of transmission flow and bearing service, and establish the electric power communication network model with the importance judgment value added to each electric power communication network node based on the importance judgment value, thereby facilitating the subsequent accurate evaluation of the reliability of the electric power communication network or the calculation of the risk of the electric power communication network, and solving the problem of model construction of future heavy load networks in the planning process of the electric power communication network.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (2)

1. A power communication network model building method is characterized by comprising the following steps:
acquiring a network model structure and service distribution condition data of a power communication network to be processed; the network model structure of the electric power communication network to be processed comprises each electric power communication network node, each electric power communication network link and each link capacity; the service distribution condition data comprises service types corresponding to the power communication network nodes and service importance degrees of the service types;
determining a link capacity matrix and a service connection matrix according to a network model structure of the electric power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix;
determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix;
determining an importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow;
setting each importance degree judgment value and each power communication network node in a network model structure of a power communication network to be processed correspondingly to form a power communication network model with each power communication network node added with the importance degree judgment value;
the method for determining the link capacity matrix and the service connection matrix according to the network model structure of the electric power communication network to be processed and the service distribution condition data and determining the network service flow matrix according to the link capacity matrix and the service connection matrix comprises the following steps:
determining a link capacity matrix A according to a network model structure of a power communication network to be processed; wherein A ═ aij]N×N(ii) a N is the total number of the nodes of the power communication network; a isijFor the link capacity of the power communication network link between power communication network node i and power communication network node j, if no power communication network link exists between power communication network node i and power communication network node j, then aijIs 0;
determining a service contact matrix L under the service type u according to the service type corresponding to each power communication network nodeu(ii) a Wherein L isu＝[lij]N×N(ii) a If the service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝lji1 is ═ 1; if no service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝lji＝0；
Determining a maximum flow matrix M of the first power communication network according to the link capacity matrix A; wherein, M ═ fij]N×N；fijThe maximum flow is obtained by taking the power communication network node i as a source node and the power communication network node j as a sink node;
according to the maximum flow matrix M of the power communication network and the service contact matrix L under the service type uuDetermining network traffic flow matrix V under traffic type uu(ii) a Wherein, Vu＝[vij]N×N，vij＝fij×lij；
The determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix comprises the following steps:
deleting the kth row and the kth column in the link capacity matrix A to obtain a processed link capacity matrix corresponding to the power communication network node kkA*；
According to the processed link capacity matrixkA*Determining a maximum flow matrix for a second power communication networkkM*(ii) a Wherein the content of the first and second substances,
Figure FDA0002745033380000021
Figure FDA0002745033380000022
according to the processed link capacity matrixkA*Taking the power communication network node i as a source node and the power communication network node j as a sink node to obtain a maximum flow;
the business contact matrix L under the business type uuDeleting the kth row and the kth column to obtain a processed service contact matrix (corresponding to the power communication network node k)kLu)*(ii) a Wherein the content of the first and second substances,
Figure FDA0002745033380000023
according to the maximum flow matrix of the second power communication networkkM*And a processed business contact matrix (kLu)*Determining a network traffic flow matrix (with the power communication network node k removed) under the service type ukVu)*(ii) a Wherein the content of the first and second substances,
Figure FDA0002745033380000024
the network service flow matrix V under the service type u is processeduDeleting the k row and the k column in the network to obtain a processed network service flow matrixkVu；
According to the formula:
Figure FDA0002745033380000025
determining business flow betweenness of power communication network node k under business type u
Figure FDA0002745033380000026
The determining the importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow comprises the following steps:
service importance s according to each service typeuDetermining the weight w corresponding to each service typeu(ii) a Wherein the content of the first and second substances,
Figure FDA0002745033380000027
according to the formula:
Figure FDA0002745033380000028
determining importance judgment value I of power communication network node kk。
2. An electric power communication network model building device, characterized by comprising:
the data acquisition unit is used for acquiring a network model structure and service distribution condition data of a power communication network to be processed; the network model structure of the electric power communication network to be processed comprises each electric power communication network node, each electric power communication network link and each link capacity; the service distribution condition data comprises service types corresponding to the power communication network nodes and service importance degrees of the service types;
the network service flow matrix determining unit is used for determining a link capacity matrix and a service connection matrix according to a network model structure of the electric power communication network to be processed and service distribution condition data, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix;
the service flow betweenness determining unit is used for determining the service flow betweenness of each power communication network node under each service type according to the link capacity matrix, the service contact matrix and the network service flow matrix;
the importance judgment value determining unit is used for determining the importance judgment value of each power communication network node according to the service importance of each service type and the betweenness of each service flow;
the electric power communication network model establishing unit is used for correspondingly setting each importance degree judging value and each electric power communication network node in a network model structure of the electric power communication network to be processed to form an electric power communication network model with each electric power communication network node added with the importance degree judging value;
wherein, the network traffic flow matrix determining unit includes:
the link capacity matrix determining module is used for determining a link capacity matrix A according to a network model structure of the electric power communication network to be processed; wherein A ═ aij]N×N(ii) a N is the total number of the nodes of the power communication network; a isijFor the link capacity of the power communication network link between power communication network node i and power communication network node j, if no power communication network link exists between power communication network node i and power communication network node j, then aijIs 0;
a service contact matrix determining module for determining a service contact matrix L under the service type u according to the service type corresponding to each power communication network nodeu(ii) a Wherein L isu＝[lij]N×N(ii) a If the service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝lji1 is ═ 1; if no service of the service type u exists between the power communication network node i and the power communication network node j, the service contact matrix LuIn, lij＝lji＝0；
The first power communication network maximum flow matrix determining module is used for determining a first power communication network maximum flow matrix M according to the link capacity matrix A; wherein, M ═ fij]N×N；fijThe maximum flow is obtained by taking the power communication network node i as a source node and the power communication network node j as a sink node;
a first network service flow matrix determining module, configured to determine a service contact matrix L according to the maximum flow matrix M of the power communication network and the service type uuDetermining network traffic flow matrix V under traffic type uu(ii) a Wherein, Vu＝[vij]N×N，vij＝fij×lij；
The service flow betweenness determining unit includes:
a link capacity matrix processing module, configured to delete the kth row and the kth column in the link capacity matrix a to obtain a processed link capacity matrix corresponding to the power communication network node kkA*；
A second power communication network maximum flow matrix determination module for determining the processed link capacity matrix according to the processed link capacity matrixkA*Determining a maximum flow matrix for a second power communication networkkM*(ii) a Wherein the content of the first and second substances,
Figure FDA0002745033380000041
Figure FDA0002745033380000042
according to the processed link capacity matrixkA*Taking the power communication network node i as a source node and the power communication network node j as a sink node to obtain a maximum flow;
a business contact matrix processing module for processing the business contact matrix L under the business type uuDeleting the kth row and the kth column to obtain a processed service contact matrix (corresponding to the power communication network node k)kLu)*(ii) a Wherein the content of the first and second substances,
Figure FDA0002745033380000043
a second network traffic flow matrix determination module for determining a maximum flow matrix according to a second power communication networkkM*And a processed business contact matrix (kLu)*Determining a network traffic flow matrix (with the power communication network node k removed) under the service type ukVu)*(ii) a Wherein the content of the first and second substances,
Figure FDA0002745033380000044
a network traffic flow matrix processing module forThe network service flow matrix V under the service type u is processeduDeleting the k row and the k column in the network to obtain a processed network service flow matrixkVu；
A service flow betweenness determining module, configured to:
Figure FDA0002745033380000045
determining business flow betweenness of power communication network node k under business type u
Figure FDA0002745033380000046
The importance judgment value determination unit includes:
a weight determining module for determining the service importance s according to each service typeuDetermining the weight w corresponding to each service typeu(ii) a Wherein the content of the first and second substances,
Figure FDA0002745033380000047
the importance judgment value determining module is used for determining the importance judgment value according to a formula:
Figure FDA0002745033380000048
determining importance judgment value I of power communication network node kk。
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