CN104579868B - Powerline network construction method based on pitch point importance - Google Patents

Abstract

The present invention provides a kind of powerline network construction method based on pitch point importance, comprises the steps: to obtain the network model of power telecom network；Wherein, described network model includes that node and link, described node are the communication equipment in power communication system, and described link is each bar optical cable connecting node；The business calculating described node adds measures and weights；Business according to described node adds measures and weights, calculates the importance degree of described node；Obtain the network model of the importance degree being attached with correspondence on each node, the network model obtained is carried out the reliability determination of Network topology and power communication system.The powerline network that the inventive method builds, can significantly improve the accuracy of the reliability determination of power communication system.

Description

Electric power communication network construction method based on node importance

Technical Field

The invention relates to the technical field of power communication systems, in particular to a power communication network construction method based on node importance.

Background

The power communication system is an important component of the power system, and the reliability of the power communication system directly influences the safe production and the reliable operation of the power system. The reliability of the power communication system is determined, the operation condition of the current network can be known on the whole, and weak links and faults can be found in time, so that direct basis is provided for troubleshooting and network reconstruction, the stability of the power communication network is further guaranteed, and the communication quality is improved.

As a communication private network of a power system, various services are carried on the power communication network, different types of services have different guarantee functions on a primary power system, and the importance of the power services refers to the degree of harm to the safety and stability of the power system after service interruption or failure. 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. However, most of the existing power communication network models only represent nodes and links, and the accuracy is low when the reliability of the power communication system is measured.

Disclosure of Invention

Based on the above, the invention provides a power communication network construction method based on node importance, and the power communication network constructed by the method can obviously improve the accuracy of reliability measurement of a power communication system.

A power communication network construction method based on node importance degree comprises the following steps:

acquiring a network model of the power communication network; the network model comprises nodes and links, wherein the nodes are communication equipment in the power communication system, and the links are all optical cables for connecting the nodes;

calculating the traffic weighting degree of the node by the following formula:

$s_i=\underset{j\∈N_i}{\mathrm{\Σ}}{w}_{\mathrm{ij}};$

wherein s is_iIs a node v_iThe degree of the service weighting of (a),m_ijrepresents a link e_ijTotal number of classes of service running on, n_ijkRepresents a link e_ijNumber of class k services run on, v_ijkRepresenting the service importance value, N, of class k services_iIs node v_iA neighbor set of (a);

calculating the importance of the node according to the service weighting degree of the node by the following formula:

$\mathrm{IMC}\left(v_i\right)=\sqrt[3]{W_i\×s_i\×\stackrel{\‾}{L_i}}$

wherein, IMC (v)_i) Is a node v_iImportance of, W_iFor a preset node v_iThe node weight value of (a) is,for a preset node v_iThe polymerization coefficient of (a);

and acquiring a network model with corresponding importance attached to each node, and performing network topology analysis and reliability measurement of the power communication system on the acquired network model.

According to the electric power communication network construction method based on the node importance, the network model of the electric power communication network is obtained, for each node in the network model, the node service weighting degree is calculated firstly by combining the electric power service, then the importance of each node is calculated by combining the node weight and the node aggregation coefficient, the network model with the corresponding importance added to each node is obtained, and the reliability determination accuracy of the electric power communication system can be remarkably improved.

Drawings

Fig. 1 is a schematic flow chart of a method for constructing a power communication network based on node importance according to an embodiment of the present invention.

Fig. 2 is a schematic diagram of a power communication transmission backbone network of a power saving network in an embodiment of a method for constructing a power communication network based on node importance according to the present invention.

FIG. 3 is a schematic diagram of a node importance variation curve calculated by the method of the present invention and the existing weighted node shrinkage method and triangular mold fusion method.

Detailed Description

The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.

As shown in fig. 1, the method is a schematic flow chart of a method for constructing a power communication network based on node importance, and includes the following steps:

s11, acquiring a network model of the power communication network; the network model comprises nodes and links, wherein the nodes are communication equipment in the power communication system, and the links are all optical cables for connecting the nodes;

s12, calculating the service weighting degree of the node according to the following formula:

$s_i=\underset{j\∈N_i}{\mathrm{\Σ}}{w}_{\mathrm{ij}};$

wherein s is_iIs a node v_iThe degree of the service weighting of (a),m_ijrepresents a link e_ijTotal number of classes of service running on, n_ijkRepresents a link e_ijNumber of class k services run on, v_ijkRepresenting the service importance value, N, of class k services_iIs node v_iA neighbor set of (a);

s13, according to the service weighting degree of the node, calculating the importance degree of the node by the following formula:

$\mathrm{IMC}\left(v_i\right)=\sqrt[3]{W_i\×s_i\×\stackrel{\‾}{L_i}}$

wherein, IMC (v)_i) Is a node v_iImportance of, W_iFor a preset node v_iThe node weight value of (a) is,for a preset node v_iThe polymerization coefficient of (a);

and S14, acquiring a network model with corresponding importance attached to each node, and performing network topology analysis and reliability measurement of the power communication system on the acquired network model.

Various services are carried on the power communication network, different types of services have different guarantee functions on a power primary system, and the importance of the power services refers to the degree of harm to the safety and stability of the power system after service interruption or failure. 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. Analyzing the importance of the service in terms of the influence of the service on a power grid and the service quality requirement, establishing an importance level analysis index system of the service by utilizing a level analysis method, and calculating the service importance.

The influence indexes of the power grid reflect the influence degree of the service on the operation of the power system, and are divided into a safety area, a bearing mode, a service channel and three secondary indexes for analyzing the importance degree of the service; the service quality requirement reflects the requirement of the service on the communication service quality provided by the network, and generally, the service related to the safe operation of the power system has very high requirement on the communication service quality, and correspondingly, the influence degree on the operation of the power system is relatively high, so the service quality requirement can reflect the important degree of the service from the side.

And according to relevant regulations of production and operation in the technical field of electric power, the service importance of the typical service is evaluated by using an analytic hierarchy process and the proposed service importance model. After normalization, the service importance values of 10 typical power communication services are obtained, as shown in the following table:

according to the calculation result of the service importance degree in the table, the importance degree of the circuit relay protection service is the maximum, and then a stability system and a dispatching automation service are provided, and the services directly realize real-time monitoring on the primary power system and are all key services for ensuring the safe operation of the power system; the protection management information system aims at secondary equipment, is a service for fault diagnosis and post-processing of the power system, and has relatively low importance. In the operation management of the power enterprise, it is also very important to ensure that important conferences are safely and smoothly carried out, the corresponding video conference system service is higher than the common management service, in conclusion, the service importance evaluation method is feasible and effective, and the calculation result accords with the actual situation.

A large number of power services are operated in a power communication network, and some important services such as a line relay protection service have extremely high requirements on service quality, particularly time delay. The traditional weighting network adopts the link length as the edge weight, but for the electric power communication network which generally adopts the optical transmission technology, the distance is not the main influence factor of information transmission, the link is used as the carrier of service transmission, and the service is the important factor influencing the network operation, so the network edge weight is considered to be evaluated from the service perspective.

A weighted network may be described by the set G ═ V, E, comprising n nodes, and a set of edges E with weights, which may be generally represented by a weighted adjacency matrix w in which the elements w are_ijRepresenting edge weights between two adjacent points, w, taking into account traffic_ij∈ [0, ∞)) indicating that the corresponding link considers the class of service_ij0 means no connection between two points.

$w_{\mathrm{ij}}=\underset{k=1}{\overset{m_{\mathrm{ij}}}{\mathrm{\Σ}}}{n}_{\mathrm{ijk}}\×v_{\mathrm{ijk}}$

Wherein m is_ijRepresents a link e_ijTotal number of classes of service running on, n_ijkRepresents a link e_ijNumber of class k services run on, v_ijkRepresenting the traffic importance value of the kth class of traffic.

After the service is taken as the consideration factor of considering the edge weight, the node weighting degree s is obtained_iIt is defined as:

$s_i=\underset{j\∈N_i}{\mathrm{\Σ}}{w}_{\mathrm{ij}}$

wherein N is_iIs a neighbor set of node i.

Node weighting degree s considering traffic_iThe method not only considers the neighbor number of the node, but also considers the importance and the quantity of the service passing through the node, is the comprehensive embodiment of the local service information of the node, and reflects the relative importance degree of the node from the service perspective.

The three indexes of node service weighting degree, power grid influence factor and aggregation coefficient describe the relative importance degree of the node in the whole network from three different angles of service, function and topology, and the three aspects of information of the node operation service, the weight of the node and the position of the node in the topology are integrated to obtain the importance degree of the node i:

$\mathrm{IMC}\left(v_i\right)=\sqrt[3]{W_i\×s_i\×\stackrel{\‾}{L_i}}$

wherein, W_iNodal grid influence factor, s, for a node_iIn order to weight the degree of the node,is the aggregate coefficient of the nodes.

The node importance degree comprises three layers of information of the node service, status and topology, the importance degree of the node comprehensiveness is reflected more comprehensively, and the method has practical significance for the evaluation of the power communication network nodes.

As shown in fig. 2, the calculation method is simulated and verified by taking a certain power-saving communication transmission backbone network as an example. The simulation network topology structure G (V, E) is shown in fig. 2, 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, and the node grid influence factors are shown in the following table:

the service distribution in the network is shown in the following table:

comparing and analyzing the node importance degrees calculated by the method of the embodiment and the existing weighted node shrinkage method and the existing triangular model fusion method, wherein the results are shown in the following table, in order to conveniently compare different methods, the calculation results are processed in a unitization way, and a node importance degree change curve is drawn and is shown in fig. 3;

the simulation result shows that:

compared with a weighted node contraction method and a triangular model fusion method, the method comprehensively evaluates the importance of the nodes by combining the network aggregation coefficient and the importance and the number of the node bearing services, and the evaluation result can reflect the influence degree of the nodes on the connectivity of a network topology layer and also reflect the importance degree of the nodes in the network service layer.

The network and simulation results according to the example of FIG. 2 can be seenGo out, node v₁As a middle regulation point, the node has the maximum power grid influence factor value and the bearing traffic is far larger than that of other nodes, and the node v is considered comprehensively₁The importance degree of the node v is far higher than that of other nodes, and the weighted node contraction method only considers the topological factor to obtain the node v₂Ratio node v₁Important results, which do not correspond to the fact, are obtained for the node v by the method of the present embodiment₁The importance value is maximum, the difference of the importance values is large, the status of the medium adjusting point is reflected, and the evaluation result of the method for the power communication network is more reasonable.

Node v₆And node v₇The importance degrees of the two nodes are similar in network topology, the evaluation results of the weighted node contraction method and the triangular mode fusion method are similar, but the node v is₇Carried traffic is compared with node v₆The evaluation result obtained by the calculation method is also the node v₇Ratio node v₆The importance value is large, and is the same as the actual situation.

The method comprehensively considers three aspects of topology, service and node influence of the power communication network, can more comprehensively reflect the comprehensive importance degree of the network nodes, and the obtained node importance value has more rationality and practicability, and has wide application prospect in power communication network node evaluation and reliability or risk management.

In a preferred embodiment, the aggregate coefficient of the nodes is calculated by:

$\stackrel{\‾}{L_k}=\underset{z\≠k\∈V}{\mathrm{\Σ}}(\frac{W_z}{\underset{i\≠k\∈V}{\mathrm{\Σ}}{W}_i}\×\frac{1}{d(k,z)})$

wherein, W_iIs a node v_iNode weight value of W_zIs a node v_zD (k, z) is a node v_kAnd v_zThe shortest path value in between;is a node v_kThe polymerization coefficient of (a);

in the embodiment, in consideration of the obvious difference in the status and the action of each node in the power communication network, the status and the action of important nodes in the provincial power communication backbone network, such as a provincial dispatching center and a 500KV substation, are greater than those of other nodes, and the compactness between the important nodes contributes more to the overall reliability of the network. Therefore, a node aggregation coefficient concept is introduced, and the node weight and the node compactness are combined to comprehensively analyze the position of the network node in the network topology;

the node weight considers the position and the action of the node, and the power communication network node weight can be considered from two aspects, namely the position and the action of a site where the power communication network node is located in a power grid; the second is the position and role of the power communication network nodes in the communication network, such as evaluating the node weight from the aspects of node types (including aggregation nodes and common nodes) and node devices (processing capability and forwarding capability).

In the power communication network, the more closely the important nodes are connected with other important nodes in the network, the more reasonable the network topology is, and the more reliable the network is. The node aggregation coefficient in this embodiment represents a weighted average shortest distance between one node and another node, and takes the weight of the node into consideration. The node aggregation coefficient can be used for measuring the average distance between the node and the important node, and the smaller the distance between the node and the important node is, the denser the distribution of the important node around the node is, and the higher the aggregation coefficient of the node is. The property of the aggregation coefficient has practical application value in the power communication network, for example, the dispatching center undertakes the monitoring and control tasks of the power system, needs to process a large amount of power service information, the denser the distribution of the important nodes around the dispatching center is, the more reasonable the power communication network topology is, and the higher the network reliability is.

Suppose v_kIf the network graph G is a node in (V, E), the node V is a node in (V, E)_kThe polymerization coefficient of (a) is calculated as follows:

$\stackrel{\‾}{L_k}=\underset{z\≠k\∈V}{\mathrm{\Σ}}(\frac{W_z}{\underset{i\≠k\∈V}{\mathrm{\Σ}}{W}_i}\×\frac{1}{d(k,z)})$

wherein, W_iIs a node v_iD (k, z) is a node v_kAnd v_zThe shortest path value in between;is node v_kAnd v_zThe reciprocal of the shortest path between the nodes represents the compactness between the two nodes, and the shorter the distance between the nodes is, the larger the value is, the higher the compactness between the nodes is. The value range of the node tightness is (0,1)]When the compactness value is 1, the two nodes are directly connected, and the two nodes are connected most closely at the moment.

By node v_kFor the center, calculating the compactness between other nodes in the network and the node, and simultaneously consideringThe weight of the node itself obtains an index capable of reflecting the average degree of tightness of the distribution of the nodes around the nodeNamely the node aggregation coefficient. The larger the node aggregation coefficient is, the denser the distribution of important nodes around the node is, and the distance between the center of gravity of the network and the node v_kThe more recent, the more important the position of the corresponding node on the network topology.

Node aggregate coefficientThe importance of the nodes and the connection status of the nodes with the important nodes are described, the position of the nodes in the network can be reflected, the distribution status of the network important nodes is analyzed by utilizing the node aggregation coefficient indexes, the higher the connection tightness between the important nodes is, the closer the center of gravity of the network is to the important nodes, the more reasonable the network structure is, the higher the overall connection reliability is, the lower the risk of the corresponding network structure is, and the accuracy of network reliability determination can be obviously improved.

In a preferred embodiment, the node weight value can be obtained by:

acquiring the site type and the site scale of the node, and determining the site grade value, the site grade influence value, the site scale value and the site scale value influence value of the node according to a preset site factor influence rule;

acquiring a power supply load of the node, and determining a load grade value, a load grade influence value, a load size and a load size influence value of the node according to a preset load factor influence rule;

determining the influence score value of each node according to the factor index set, and calculating a node relative influence matrix under each factor index; wherein the factor index set comprises a plurality of factor indexes, and the factor indexes comprise the site grade, the site scale, the load grade and the load size;

adding and summing the relative influence according to the node relative influence matrix under each factor index to obtain a node comprehensive relative influence matrix;

normalizing the node comprehensive relative influence matrix to obtain a power grid influence factor value of each node;

in a preferred embodiment, the site type includes a dispatch center, a substation, or a power plant;

the power communication network node is located at a site which comprises a dispatching center, a transformer substation, a power plant and the like, the similar sites also distinguish voltage classes or management classes, if a 500KV transformer substation is higher in grade than a 220KV transformer substation, the influence is large, the 500KV transformer substation belongs to the jurisdiction of a network dispatching center (a regional power grid dispatching center), the 220KV transformer substation is governed by a central dispatching center (a provincial power grid dispatching center), and the site class is directly reflected by the status of the site in a power grid; in addition, the site scale also affects the node status, for example, the transformer substation is divided into a hub station, a regional station and a terminal station according to the scale, the transformer substations of different scales have different functions and actions and different corresponding statuses, and meanwhile, the influence degree of the scheduling center can be distinguished according to the scale of the site governed by the scheduling center. Therefore, the site category factor of the node is evaluated from two factors of site level and site scale.

For objectively evaluating site category factors, three factor evaluation criteria of node grade and node scale are established according to relevant regulations of power enterprise production management, and are shown in the following table:

in summary, the site level includes a special level, a first level or a second level, and each level may correspond to a different numerical value; the station scales comprise a hub station, a regional station and a terminal station, and each scale can correspond to different values; according to the category factor of the site where the node is located, according to the preset site factor influence rule and according to the information of the site where each node is located, the corresponding site type influence value and the corresponding site scale value influence value are given to the node. The specific influence values of the site types and the site scale values corresponding to different site types and site scales can be set according to actual needs.

For the transformer substation directly serving the power consumer or the dispatching node indirectly serving the power consumer, the provincial production unit, the provincial power dispatching plant and other nodes, the importance degree of the served users has a great influence on the influence of the nodes, and therefore the station load grades are distinguished according to the power consumer grades served by the power loads.

According to the relevant national regulations, power consumers are divided into important power consumers and other power consumers, the important power consumers are important in social, political and economic lives of a country or a region (city), and power interruption to the important power consumers can cause personal casualties, large environmental pollution, large political influences, large economic losses, and serious social and public order disorder power utilization units or power utilization places with special requirements on power supply reliability. The important power user list is provided by a power supply enterprise according to the industry range and the power consumption load characteristics of the important power users determined by the relevant departments of the local people's governments, and is approved by the relevant departments of the local people's governments above the county level and then reported to the power supervision organization for record. According to the requirement of power supply reliability and the degree of power supply interruption hazard, important users can be classified into special-level, first-level and second-level important power users and temporary important power users.

The special level important users are power users which have a particularly important role in managing national affairs and can possibly harm national safety when power supply is interrupted; the primary important users refer to power users which may be affected by the interruption of power supply; secondary important users, which are power users that may have great influence and loss when power supply is interrupted; the temporary important power consumers refer to power consumers (large-scale hydro hubs, tunnel construction and heavy-duty temporary power conservation consumers) needing temporary special power supply guarantee.

The size of the site load is an important reference index of the influence degree of the site. The load size of the station in the power grid is not a fixed value and changes along with the change of the load of the power grid, but the relative size of the load of the station in the power grid is relatively stable, so that the load size of the station is evaluated by utilizing the load proportion of the station in the power grid. A complete failure of a site or its jurisdiction and an outages will result in a grid derating load, i.e. the maximum reduction in the actual load of the grid during the occurrence of an accident.

The accident grade caused by the reduction of the supply load of the power grid is distinguished as shown in the following table:

according to the fact that the station where the node is located or the jurisdiction range of the station completely fails and the level difference of the power grid power reduction load accidents caused by external power failure serves as an evaluation standard for evaluating the node load size factor, the load level factor is synthesized, and the node load factor evaluation criterion is obtained and is shown in the following table.

In summary, the load grades include special grade, first grade or second grade, and each grade can correspond to different numerical values; presetting a corresponding influence force value according to the load grade; the load is the power grid load of the node, the load is determined according to the power grid supply reduction load accident level, and a corresponding influence value is preset; and according to a preset load factor influence rule and the load information of the site where each node is located, giving a load grade influence value and a load size influence value corresponding to the node. The specific load grade influence values and the load size influence values corresponding to different load grades and load sizes can be set according to actual needs.

In a preferred embodiment, the set of factor indicators is: k ═ K_nN is 1,2, ·, N; this exampleWherein N is equal to 4, namely 4 factor indexes, site level, site size, load level and load size are included, wherein N is equal to 4, k₁、k₂、k₃、k₄Respectively refer to the four indexes.

The step of determining the influence score value of each node according to the factor index set and calculating the relative influence matrix of the nodes under each factor index comprises the following steps:

and calculating to obtain the relative influence matrix of the nodes according to the following formula:

wherein each node constitutes a node set B ═ v_i1,2, ·, I; the influence score of each node in the node set is { s }_i(k_n)}，s_i(k_n) Is a node v_iAt factor index k_nThe lower influence value;

representing a node v_iAnd v_jAt factor index k_nRelative impact value of; when the value of i is equal to j,when i ≠ j, $a_{\mathrm{ij}}^{\left(k_n\right)}=\left\{\begin{array}{cc}1& s_i\left(k_n\right)/s_j\left(k_n\right)>1\\ 0.5& s_i\left(k_n\right)/s_j\left(k_n\right)=1\\ 0& s_i\left(k_n\right)/s_j\left(k_n\right)<1\end{array}\right.;$

for the same factor index k_nSumming the row vector elements of the lower node relative influence matrix to obtain a factor index k_nLower node relative influence moment array

Wherein the node comprehensive relative influence matrix is

In a preferred embodiment, when the node comprehensive relative influence matrix is normalized, the node comprehensive relative influence moment matrix is normalized by adopting a normalization method based on membership.

The step of normalizing the node comprehensive relative influence moment array by adopting a normalization method based on membership comprises the following steps:

normalizing the node comprehensive relative influence moment array through the following formula; obtaining the power grid influence factor value of each node:

$F\left(v_i\right)=e^{\frac{-{(a_i^{\mathrm{sum}}-c)}^2}{2{\mathrm{\&sigma;}}^2}}$

wherein,F(v_i) Is a node v_iThe value of the grid impact factor of (c), $a_{\max }^{\mathrm{sum}}=\mathrm{MAX}(a_1^{\mathrm{sum}},a_2^{\mathrm{sum}},...,a_i^{\mathrm{sum}},...a_I^{\mathrm{sum}}),a_{\min }^{\mathrm{sum}}=\mathrm{MIN}(a_1^{\mathrm{sum}},a_2^{\mathrm{sum}},...,a_i^{\mathrm{sum}},...a_I^{\mathrm{sum}}),$ the value range is ∈ (0,1) for the preset normalization parameter.

The invention relates to a power communication network construction method based on node importance, which is used for acquiring a network model of a power communication network, calculating the node service weight degree of each node in the network model by combining power service, calculating the importance of each node by combining node weight and node aggregation coefficient, analyzing the three aspects of service, topology and node self status and action, and acquiring the node importance by using an information fusion method. The invention comprehensively considers three aspects of topology, service and node influence of the power communication network, can more comprehensively reflect the comprehensive importance degree of network nodes, obtains more reasonable and practical node importance value, and finally obtains a network model with corresponding importance degree added on each node, thereby obviously improving the accuracy of reliability determination of the power communication system.

The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (8)

1. A power communication network construction method based on node importance is characterized by comprising the following steps:

acquiring a network model of the power communication network; the network model comprises nodes and links, wherein the nodes are communication equipment in the power communication system, and the links are all optical cables for connecting the nodes;

calculating the traffic weighting degree of the node by the following formula:

$s_i=\underset{j\&Element;N_i}{\&Sigma;}{w}_{ij};$

wherein s is_iIs a node v_iThe degree of the service weighting of (a),m_ijrepresents a link e_ijTotal number of classes of service running on, n_ijkRepresents a link e_ijNumber of class k services run on, v_ijkRepresenting the service importance value, N, of class k services_iIs node v_iA neighbor set of (a);

calculating the importance of the node according to the service weighting degree of the node by the following formula:

$IMC\left(v_i\right)=\sqrt[3]{W_i\&times;s_i\&times;\stackrel{\&OverBar;}{L_i}}$

wherein, IMC (v)_i) Is a node v_iImportance of, W_iFor a preset node v_iThe node weight value of (a) is,for a preset node v_iThe polymerization coefficient of (a);

and acquiring a network model with corresponding importance attached to each node, and performing network topology analysis and reliability measurement of the power communication system on the acquired network model.

2. The node importance-based power communication network construction method according to claim 1, wherein the aggregation coefficient is calculated by the following formula:

$\stackrel{\&OverBar;}{L_k}=\underset{z\&NotEqual;k\&Element;V}{\&Sigma;}(\frac{W_z}{\underset{i\&NotEqual;k\&Element;V}{\&Sigma;}{W}_i}\&times;\frac{1}{d(k,z)})$

wherein, W_iIs a node v_iD (k, z) is a node v_kAnd v_zThe shortest path value in between;is a node v_kV is a node set.

3. The method for constructing the power communication network based on the node importance degree according to claim 2, wherein the node weight value is obtained by:

acquiring the site type and the site scale of the node, and determining the site level, the site level influence value, the site scale and the site scale value influence value of the node according to a preset site factor influence rule;

acquiring the power supply load of the node, and determining the load grade, the load grade influence value, the load size and the load size influence value of the node according to a preset load factor influence rule;

determining the influence score value of each node according to the factor index set, and calculating a node relative influence matrix under each factor index; wherein the factor index set comprises a plurality of factor indexes, and the factor indexes comprise the site grade, the site scale, the load grade and the load size;

adding and summing the relative influence according to the node relative influence matrix under each factor index to obtain a node comprehensive relative influence matrix;

and normalizing the node comprehensive relative influence matrix to obtain a power grid influence factor value of each node as the node weight value.

4. The node importance-based power communication network construction method according to claim 3, wherein the site type includes a dispatch center, a substation, or a power plant.

5. The method of constructing a power communication network of node importance according to claim 3, characterized in that:

the factor index set is: k ═ K_n},n＝1,2,...,N；N＝4；

The step of determining the influence score value of each node according to the factor index set and calculating the relative influence matrix of the nodes under each factor index comprises the following steps:

and calculating to obtain the relative influence matrix of the nodes according to the following formula:

wherein each node v_iConstituting node set V ═ V_i1,2, ·, I; the influence score of each node in the node set is { s }_i(k_n)}，s_i(k_n) Is a node v_iAt factor index k_nThe lower influence value;

representing a node v_iAnd v_jAt factor index k_nRelative impact value of; when the value of i is equal to j,when i ≠ j,

for the same factor index k_nSumming the row vector elements of the lower node relative influence matrix to obtain a factor index k_nLower node relative influence moment array

6. The method according to claim 5, wherein the node comprehensive relative influence matrix is

7. The method for constructing the power communication network of the node importance degree according to claim 6, wherein when the node comprehensive relative influence matrix is normalized, a normalization method based on the membership degree is adopted to normalize the node comprehensive relative influence moment matrix.

8. The method for constructing a power communication network of node importance according to claim 7, wherein the step of normalizing the node comprehensive relative influence moment array by using a membership-based normalization method comprises:

normalizing the node comprehensive relative influence matrix through the following formula to obtain a power grid influence factor value of each node:

$F\left(v_i\right)=e^{\frac{-{(a_i^{sum}-c)}^2}{2{\mathrm{\&sigma;}}^2}}$

wherein, F(v_i) Is a node v_iThe value of the grid impact factor of (c), for the normalization parameter, the value range is ∈ (0, 1).