CN-122027640-A - Network edge optimization method applied to urban power communication network

CN122027640ACN 122027640 ACN122027640 ACN 122027640ACN-122027640-A

Abstract

A network edge optimization method applied to urban power communication networks relates to the technical field of power communication networks and solves the problems that network edge optimization of the existing power communication networks cannot achieve multi-objective, lacks multi-scene robustness and is insufficient in consideration of fragile areas. The method comprises the steps of constructing an urban power communication network model, determining a key area, defining an annular area, constructing a multi-fault scene damage set, setting weights, generating a candidate edge set under the multi-fault scene, evaluating indexes of each candidate edge under each fault scene, summarizing according to the weights, adjusting the weights of the candidate edges located in the key area, calculating scores of the candidate edges, selecting the most balanced edge adding strategy according to the pareto front edge and maxmin, and finally outputting a newly added link and an evaluation index value. The invention avoids the defect that the traditional method is optimal only under a single hypothesis and fails in actual combat.

Inventors

JIANG WANCHANG
Zhai Xueru
ZHANG MINGHUI
LI XINMENG
WANG SHENGDA
LIU DANNI

Assignees

东北电力大学

Dates

Publication Date: 20260512
Application Date: 20251024

Claims (8)

1. The network edge optimization method applied to the urban power communication network is characterized by comprising the following steps of: Constructing an urban power communication network model, and simultaneously analyzing vulnerability of the urban power network to determine a key area; Step two, defining an annular zone according to the key zone determined in the step one; Step three, constructing a multi-fault scene damage set, and setting weights for all scenes; Comprehensively adopting cross-component bridging, cut point neighbor closure, community bridging and girdle closure and surrounding area bridging strategies to generate a candidate edge set under a multi-fault scene; step five, evaluating indexes of each candidate edge under each fault scene respectively, summarizing according to weights, adjusting weights of the candidate edges in the key areas at the same time, and calculating scores of the candidate edges; And step six, selecting the most balanced edge adding strategy according to the pareto front edge and maxmin, selecting candidate edges until the upper limit is reached or no forward gain is generated, and finally outputting a newly added link and an evaluation index value.
2. The network edge optimization method applied to an urban power communication network as set forth in claim 1, wherein in step one, the urban power communication network model is , wherein, For a collection of sites, i.e , Represent the first Individual sites, number of sites is E is the set of the corresponding sides of the communication links in the power communication network, namely , Representing a power communication network model Middle station With the site Edge between, in the collection Middle if =1, Then say at site With the site There is an edge connection, if =0, Then say at site With the site There is no edge connection.
3. The network edge optimization method applied to urban power communication network of claim 1, wherein in the second step, a key area is defined as D= { | , wherein, And (3) with For a station Longitude and latitude coordinates of (a); the circle center coordinates of the key area are shown, and r is the damage radius; Setting the annular zone as a preferential edge buffer zone which is close to the key zone but not in the zone; the ring belt region is defined as R= { (x, y) R < d ((x, y), c) < 1+gamma) R }, wherein (x, y) is the position of a certain node in the network model G, c is the central position of a key region, d ((x, y), c) represents the geometric distance between the position of the node and the center of a circle, and gamma is the thickness coefficient of the ring belt region.
4. The network edge optimization method for urban power communication network as set forth in claim 1, wherein the adopted damage method comprises obtaining a power communication network model The position information of each site is traversed, the Euclidean distance between the site and the center of the key area is calculated V, if Traversing all the sites in the key area, deleting the sites and the related edges thereof, traversing each edge, and calculating Euclidean distance between the edges and the center of the key area If (3) The edge is considered to cross the critical area.
5. The network edge optimization method applied to the urban power communication network according to claim 1, wherein in the third step, a key area weight beta is set, multiple times of network model optimization and damage are respectively carried out on a plurality of weight values of beta epsilon {1,2,3,4,5}, integral optimization indexes M (G) after edge addition and after damage are recorded, M (G) epsilon { E (G), C (G) and R (G) }, wherein E (G) is network efficiency, C (G) is connectivity and R (G) is robustness, the average value and standard error of indexes after damage are summarized for each beta, and beta with the maximum index average value is used as the weight value.
6. The network edge optimization method applied to the urban power communication network according to claim 5, wherein in the third step, the formula of the network efficiency E (G) is as follows: ; Wherein, the For the shortest path length between node v i and node v j , n is the total number of nodes in network model G; The formula of connectivity C (G) is as follows: ; Wherein is # The number of the maximum connected subgraphs of the network model G is, |V| is the total number of nodes in the current network; The formula of the robustness R (G) is as follows: ; Wherein, S (p) is the maximum connected sub-graph scale duty ratio after removing the p proportion of nodes before removing; is the maximum removal ratio.
7. The network edge optimization method applied to the urban power communication network according to claim 1, wherein the specific process of the fifth step is as follows: Step five, adding a candidate edge e to the network model G, and calculating a gain set { of scene indexes on each fault scene S i epsilon S , } ; ; In the formula, , Respectively adding the candidate edges e and then adding the candidate edges e into the network model G to obtain the network efficiency, connectivity and robustness index gain values; For the first index value set of network, { E } ),C( ),R( )}∈M( ),M( ) To add candidate edges based on the network model G under the scene s i The network efficiency, connectivity and robustness index value set of the network model G; Step five, scene index gain set for each scene Calculating expected gain value, wherein each scene s i corresponds to one scene weight vector The desired gain value is expressed as: ; Wherein, the Wherein, the method comprises the steps of, , , Respectively add candidate edges The network efficiency, connectivity and robustness of the rear network model G are improved; Step five, if the candidate edge The geometric position of (a) falls into a critical region D, then for the desired gain value And (3) adjusting, wherein an adjusting formula is as follows: If not, the first part of the first part is connected with the second part, =1; Candidate edge scoring:
8. The network edge optimization method applied to the urban power communication network according to claim 1, wherein in the sixth step, the improvement amplitude of each candidate edge on the scene indexes of network efficiency, connectivity and robustness is compared, and finally the candidate edge with the most balanced improvement of the network index is selected as the optimal edge, and the optimal edge is added into a network model G to update a network structure; And when the number of the candidate edges reaches an upper limit h or no positive gain edge exists in the candidate set, outputting a newly added link and an evaluation index value.

Description

Network edge optimization method applied to urban power communication network Technical Field The invention relates to the technical field of power communication networks, in particular to a network edge optimization method applied to an urban power communication network. Background With the acceleration of urban processes, urban power demands are increasing, and the role of power communication networks in urban power systems is also becoming increasingly important. The urban power communication network is taken as an important component of the intelligent power grid and bears key tasks such as real-time monitoring, scheduling, load management and fault diagnosis of urban power equipment. With the rapid development of smart grids, urban power communication networks are no longer simple information transmission channels, but are core platforms for supporting efficient operation and stable power supply of power systems. However, with the increase of urban power communication network loads, the complexity of network structures, and the threat of natural disasters and external malicious attacks, the vulnerability problem of the urban power communication network is gradually revealed, and especially in the aspect of reliability of key nodes and key areas, the robustness of the power communication network becomes an important factor affecting the stability of the urban power system. Indeed, the vulnerability of urban power communication networks has historically been exposed many times. The accidents are caused by the failure or deliberate damage of the information communication system in the power grid. Therefore, the network optimization of the power communication network is a necessary measure for ensuring the normal operation of the smart grid. The experiment aims at more comprehensively and accurately evaluating and improving the survivability of the urban power communication network by constructing a complex network model comprising tower nodes and real nodes and applying an innovative algorithm. Disclosure of Invention The invention provides a network edge optimization method applied to an urban power communication network, which aims to solve the problems that the network edge optimization of the existing power communication network cannot achieve multi-objective, lacks multi-scene robustness and is insufficient in consideration of fragile areas. The network edge optimization method applied to the urban power communication network is realized by the following steps: Constructing an urban power communication network model, and simultaneously analyzing vulnerability of the urban power network to determine a key area; Step two, defining an annular zone according to the key zone determined in the step one; Step three, constructing a multi-fault scene damage set, and setting weights for all scenes; Comprehensively adopting cross-component bridging, cut point neighbor closure, community bridging and girdle closure and surrounding area bridging strategies to generate a candidate edge set under a multi-fault scene; step five, evaluating indexes of each candidate edge under each fault scene respectively, summarizing according to weights, adjusting weights of the candidate edges in the key areas at the same time, and calculating scores of the candidate edges; And step six, selecting the most balanced edge adding strategy according to the pareto front edge and maxmin, selecting candidate edges until the upper limit is reached or no forward gain is generated, and finally outputting a newly added link and an evaluation index value. The invention has the beneficial effects that: According to the invention, the local circular damage area is modeled and is incorporated into an edge decision, the weaving ring and the winding bridging are preferably implemented in the annular zone area at the outer edge of the damage area, so that the network can still keep the main network communication when the key area fails, the risk that the topology is segmented into a plurality of islands is remarkably reduced, meanwhile, the scene weight vector is introduced to carry out weighted evaluation on multiple faults such as directional striking, random failure, fragile area damage and the like, and the self-adaptive balance between the expected optimal performance and the worst case bottom protection can be avoided, and the defect that the traditional method is optimal only under a single hypothesis and fails in actual combat is avoided. The method not only supplements the critical topological fragile links, but also effectively controls the newly added link length and the construction cost by integrating structural candidates such as cross component bridging, cut point neighbor closure, community bridging and the like and geographical distance constraints, and is more balanced and feasible compared with a degree/medium number single index or a pure geographical neighbor method, and the method applies position punishment to candidate edge