CN-121984875-A - Reliability evaluation method and system for power communication network

CN121984875ACN 121984875 ACN121984875 ACN 121984875ACN-121984875-A

Abstract

The invention relates to the technical field of power system communication, and provides a power communication network reliability evaluation method and system, wherein the method comprises the steps of dividing a network state space of an operation state of a power communication network into a plurality of subspaces; the method comprises the steps of extracting space points from each subspace, generating an evaluation space point set based on a preset state evaluation space mapping relation, acquiring original network nodes in a network state space according to key evaluation space points in the evaluation space point set, operating a simulation evaluation flow based on an evolution network state space generated by injecting each original network node into a corresponding preset control logic, reversely calibrating each preset control logic, and injecting each obtained calibration control logic into the evolution network state space to perform reliability evaluation to generate a dynamic reliability evaluation result. The invention can actively and accurately sense the state from the inside of the network, dynamically adjust and optimize according to the feedback of the network, and effectively improve the accuracy and adaptability of the deep reliability state evaluation of the network.

Inventors

FAN MINGXIA
ZHANG LIJUN
ZHANG JIE
HUANG JIANGQIAN
YANG HONGZHEN
HE CHEN
FAN CHAO
QIAN JIN

Assignees

国网浙江省电力有限公司经济技术研究院
国网浙江省电力有限公司信息通信分公司
国网浙江省电力有限公司杭州供电公司

Dates

Publication Date: 20260505
Application Date: 20260407

Claims (10)

1. A method for evaluating reliability of an electric power communication network, the method comprising: Constructing a network state space representing the running state of the power communication network, and performing space division on the network state space to form a plurality of subspaces with association relations; Extracting space points with reliability representation capability from each subspace respectively, mapping each space point to a preset evaluation space based on a preset state evaluation space mapping relation, and generating an evaluation space point set; Acquiring key evaluation space points in the evaluation space point set, and acquiring corresponding original network nodes in the network state space according to each key evaluation space point; Injecting each original network node into corresponding preset control logic, generating an evolution network state space, and running a simulation evaluation flow based on the evolution network state space to obtain a plurality of groups of logic execution records; and reversely calibrating each preset control logic according to all the logic execution records, injecting each obtained calibration control logic into the evolution network state space to execute reliability evaluation, and generating a corresponding dynamic reliability evaluation result.
2. The power communication network reliability evaluation method according to claim 1, wherein the step of performing space division on the network state space to form a plurality of subspaces having an association relationship comprises: Performing state transition analysis according to the historical state transition data of the power communication network to obtain a plurality of state transition modes; Defining a core state area corresponding to the state transition mode in the network state space according to each state transition mode; And taking each core state area as a center, extending outwards according to a preset association degree rule to form a plurality of subspaces covering the network state space, and establishing association relations between adjacent subspaces.
3. The power communication network reliability evaluation method according to claim 1, wherein the constructing step of the preset state evaluation space mapping relation includes: determining the evaluation dimension of the preset evaluation space based on a preset evaluation requirement, wherein the preset evaluation requirement comprises that the number of the evaluation dimensions of the preset evaluation space is larger than the number of the state dimensions of the network state space; Constructing a mapping rule from each state dimension in the network state space to at least one evaluation dimension in the preset evaluation space; and combining to form the preset state evaluation space mapping relation according to all the mapping rules.
4. The power communication network reliability evaluation method according to claim 1, wherein the step of acquiring key evaluation space points in the evaluation space point set comprises: Calculating the evaluation distance between every two evaluation space points in the evaluation space point set; constructing a distance relation network of the evaluation space point set according to all the evaluation distances; Based on the number of the direct connection edges of each evaluation space point in the distance relation network, obtaining the corresponding degree centrality; obtaining corresponding betweenness centrality based on the shortest path passing proportion of each evaluation space point in the distance relation network; Obtaining corresponding proximity centrality based on the inverse value of the sum of the shortest path distances between each evaluation space point and the rest of the evaluation space points in the distance relation network; Analyzing the centrality, the betweenness centrality and the nearness centrality of each evaluation space point according to a preset key point searching condition, and marking the evaluation space points meeting the preset key point searching condition as the key evaluation space points, wherein the preset key point searching condition is that the centrality is larger than a preset connectivity threshold value and the betweenness centrality or the nearness centrality is larger than a preset centrality threshold value.
5. The method of evaluating reliability of a power communication network according to claim 1, wherein the step of injecting each of the original network nodes into a corresponding preset control logic to generate an evolving network state space comprises: Acquiring multi-dimensional state data of each original network node in a preset historical time period, and preprocessing the multi-dimensional state data to obtain corresponding multi-dimensional state data to be analyzed, wherein the multi-dimensional state data comprises a state value sequence, a state change timestamp sequence and an associated event sequence; respectively extracting time domain features and frequency domain features of state value sequences in the multidimensional state data to be analyzed to obtain corresponding state time domain features and state frequency domain features, wherein the state time domain features comprise mean values, variances, skewness and kurtosis; carrying out event interval analysis on the state change time stamp sequences in the multidimensional state data to be analyzed to obtain corresponding event interval characteristics, wherein the event interval characteristics comprise average event interval time and interval time variance; Combining the state time domain features, the state frequency domain features and the event interval features corresponding to the multidimensional state data to be analyzed to obtain node behavior features corresponding to the original network nodes; filling node behavior characteristics of each original network node into a preset control logic template to generate corresponding preset control logic, wherein the preset control logic template comprises a condition judgment rule and a corresponding logic execution path; Injecting each preset control logic into the corresponding original network node to generate a corresponding logic injection node; and recalculating the space topological structure of the network state space according to the positions of the logic injection nodes in the network state space, and generating the evolution network state space.
6. The power communication network reliability evaluation method of claim 5 wherein the step of recalculating the spatial topology of the network state space based on the location of each of the logical injection nodes in the network state space, and generating the evolving network state space comprises: marking each of the logical injection nodes as a particular node in the network state space; Updating the connection weights between each special node and all other nodes in the network state space based on preset weight updating conditions to obtain corresponding logic injection connection weights, wherein the preset weight updating conditions comprise a newly-added data stream interaction mode or a preset inter-node coupling rule generated after the logic injection nodes are introduced; and updating the space connection matrix of the network state space according to the logic injection connection weight of each special node, and generating the evolution network state space according to the updated space connection matrix.
7. The method for evaluating the reliability of a power communication network according to claim 5, wherein the step of obtaining a plurality of sets of logic execution records based on the operation simulation evaluation flow of the evolution network state space comprises: presetting a plurality of simulation operation scenes for the evolution network state space; And under each simulation operation scene, driving the evolution network state space to operate from an initial state to a final state, and continuously collecting control logic operation information of each logic injection node to generate a corresponding logic execution record, wherein the control logic operation information comprises the triggered time of the control logic, the triggering condition of the control logic and the execution result of the control logic.
8. The power communication network reliability evaluation method according to claim 1, wherein the step of reversely calibrating each of the preset control logics based on all the logic execution records comprises: Acquiring execution exception records in all the logic execution records, generating an exception execution record group, and analyzing each exception execution record in the exception execution record group to obtain corresponding control exception information, wherein the control exception information comprises exception triggering time, an exception triggering input condition set and an exception output result; according to the logic execution paths in the corresponding preset control logic of each abnormal execution record, constructing a complete execution path diagram from a logic execution starting point to an abnormal output node; in each complete execution path diagram, starting reverse traversal from the abnormal output node, sequentially backtracking whether the actual output and the expected output of each logic judgment node are consistent, and marking the first logic judgment node with deviation as a target adjustment logic unit; And adjusting the internal parameters of the target adjustment logic unit, and performing verification simulation on the preset control logic after parameter adjustment until the corresponding verification execution record accords with the preset expected execution record, so as to obtain the corresponding calibration control logic.
9. The power communication network reliability evaluation method of claim 1, wherein the step of injecting the obtained respective calibration control logic into the evolving network state space to perform reliability evaluation, and generating the corresponding dynamic reliability evaluation result comprises: Setting a plurality of observation points in the evolution network state space, and starting a preset dynamic evolution flow of the evolution network state space; In the preset dynamic evolution flow, synchronously collecting state evolution flows containing the running states of all logic injection nodes from all observation points; And analyzing all the state evolution flows to generate the dynamic reliability evaluation result in real time.
10. A power communication network reliability evaluation system, the system comprising: the state space division module is used for constructing a network state space representing the running state of the power communication network, and performing space division on the network state space to form a plurality of subspaces with association relations; The evaluation space generation module is used for respectively extracting space points with reliability characterization capability from each subspace, mapping each space point to a preset evaluation space based on a preset state evaluation space mapping relation, and generating an evaluation space point set; The key node extraction module is used for acquiring key evaluation space points in the evaluation space point set and acquiring corresponding original network nodes in the network state space according to each key evaluation space point; the network state simulation module is used for injecting each original network node into corresponding preset control logic, generating an evolution network state space, and running a simulation evaluation flow based on the evolution network state space to obtain a plurality of groups of logic execution records; And the network dynamic evaluation module is used for reversely calibrating each preset control logic according to all the logic execution records, injecting each obtained calibration control logic into the evolution network state space to execute reliability evaluation, and generating a corresponding dynamic reliability evaluation result.

Description

Reliability evaluation method and system for power communication network Technical Field The invention relates to the technical field of power system communication, in particular to a power communication network reliability evaluation method and system. Background Reliability evaluation of power communication networks typically relies on deploying monitoring equipment at critical network nodes for external data acquisition or off-line simulation based on historical operational data and fixed rule models. However, the external monitoring technology can only passively record the performance parameters which are shown by the network, and cannot actively probe the deep response mechanism of the network under the potential fault or extreme working condition, and meanwhile, the evaluation logic based on the simulation of the fixed rule model is statically preset, so that the dynamic change of the network topology and the service flow is difficult to adapt. The two main schemes lead to the disjoint of the evaluation process and the real-time and endogenous state evolution process of the network, the obtained evaluation result has limitations on accuracy and scene adaptability, the evaluation depth and flexibility are insufficient, and the propagation path of the complex fault in the system and the real bearing toughness of the network are difficult to reveal. Disclosure of Invention In order to solve the technical problems, the invention provides a reliability evaluation method and a system for an electric power communication network, which effectively improve the accuracy and adaptability of the evaluation of the deep reliability state of the network by actively and accurately sensing the state from the inside of the network and dynamically adjusting the reliability evaluation mechanism according to the feedback of the network. In a first aspect, an embodiment of the present invention provides a method for evaluating reliability of an electric power communication network, where the method includes: Constructing a network state space representing the running state of the power communication network, and performing space division on the network state space to form a plurality of subspaces with association relations; Extracting space points with reliability representation capability from each subspace respectively, mapping each space point to a preset evaluation space based on a preset state evaluation space mapping relation, and generating an evaluation space point set; Acquiring key evaluation space points in the evaluation space point set, and acquiring corresponding original network nodes in the network state space according to each key evaluation space point; Injecting each original network node into corresponding preset control logic, generating an evolution network state space, and running a simulation evaluation flow based on the evolution network state space to obtain a plurality of groups of logic execution records; and reversely calibrating each preset control logic according to all the logic execution records, injecting each obtained calibration control logic into the evolution network state space to execute reliability evaluation, and generating a corresponding dynamic reliability evaluation result. Further, the step of performing space division on the network state space to form a plurality of subspaces with association relations includes: Performing state transition analysis according to the historical state transition data of the power communication network to obtain a plurality of state transition modes; Defining a core state area corresponding to the state transition mode in the network state space according to each state transition mode; And taking each core state area as a center, extending outwards according to a preset association degree rule to form a plurality of subspaces covering the network state space, and establishing association relations between adjacent subspaces. Further, the step of constructing the preset state evaluation space mapping relation includes: determining the evaluation dimension of the preset evaluation space based on a preset evaluation requirement, wherein the preset evaluation requirement comprises that the number of the evaluation dimensions of the preset evaluation space is larger than the number of the state dimensions of the network state space; Constructing a mapping rule from each state dimension in the network state space to at least one evaluation dimension in the preset evaluation space; and combining to form the preset state evaluation space mapping relation according to all the mapping rules. Further, the step of obtaining the key evaluation spatial point in the evaluation spatial point set includes: Calculating the evaluation distance between every two evaluation space points in the evaluation space point set; constructing a distance relation network of the evaluation space point set according to all the evaluation distances; Based on the number of the di