169 results about "Cascading failure" patented technology

The invention provides an electric power technology service guarantee supervision method, which comprises the steps of determining a matching degree evaluation criterion of an operation tool specification and a protection measure grade according to a real-time operation data set, and meanwhile, integrating a compliance deviation reason according to an out-of-plan repair judgment result to determine an operation rationality evaluation criterion; performing electric power risk grading analysis on the cascading failure prediction set, judging the existence condition of a high risk grade, and extracting transformer abnormal sign data to obtain a risk grade classification result; according to the flow difference degree of the optimized repair path and the initial repair operation step, the optimized path is integrated back to the real-time operation data set, and meanwhile, in combination with transformer abnormal sign data, an update operation guidance set is obtained; and generating a power operation visualization report according to the updated operation guidance set, verifying the applicable condition that the alarm is not directly started when the service standard process is deviated, and obtaining a final compliance judgment conclusion.

The invention discloses a fault diagnosis method and system for an electric power centralized communication control device, which are used for accurately identifying cascade faults so as to improve the safety and stability of an electric power system. The method comprises the following steps: acquiring operation data of the power centralized communication control device, and extracting a frequency feature set from the operation data; calculating association strength among variables in the frequency feature set by using a conditional probability table, and screening out a key feature vector set to generate an interactive topology among different devices in the power system; calculating propagation paths and propagation speeds of the key feature vectors in the interactive topology according to a path reasoning algorithm, and screening out a candidate fault propagation path set based on the propagation paths and the propagation speeds; calculating fault propagation probabilities of the candidate fault propagation paths to determine a cascade fault propagation feature set; and constructing a high-dimensional space classification boundary according to the cascade fault propagation feature set so as to perform fault mode classification and obtain a fault diagnosis result.

The invention relates to a charging pile AC / DC power dynamic cooperative regulation and control system, which belongs to the technical field of charging piles and comprises a power grid parameter acquisition module, a charging load characteristic analysis module, a coupling effect calculation module, a power distribution optimization module and a cooperative control execution module. The system can accurately distribute power to vehicles which really need and can be efficiently utilized, mutual interference between modules can be effectively restrained, power oscillation and cascading failures are avoided, the stability and reliability of the whole charging station under high-density operation are guaranteed, the robustness of the system is enhanced, and the service life of the charging station is prolonged. A dynamic and globally optimal balance point is found and maintained among three mutually restricted targets, namely, power deviation, coupling power and power grid constraint, by establishing and solving a multi-target optimization model containing power deviation, coupling power and power grid constraint, the stability of the multi-target optimization model is guaranteed, and the power grid safety is maintained, which cannot be achieved by any single-target or static-weight control strategy.

The invention discloses a supply chain network toughness dynamic evaluation method. According to the method, an improved cascade failure model is constructed, normal operation, damage and interruption states of nodes are defined, interruption propagation is simulated, and node state changes are tracked; counting the number of normal operation nodes at each moment to generate a structural performance curve, constructing a maximum flow model with the maximization of the total delivery amount as a target, and solving the total delivery amount at each moment to generate an operation performance curve; according to the structure performance curve and the operation performance curve, the maximum performance decreasing amplitude, the recovery duration and the average performance maintenance rate are calculated respectively, and the supply chain network toughness is quantified from the three dimensions of absorption force, recovery force and adaptability. The invention further discloses a supply chain network toughness dynamic evaluation device, electronic equipment, a storage medium and a computer program product. The method can dynamically evaluate the toughness of the supply chain network facing the interruption risk, provides a stable and reliable basis, and is suitable for toughness evaluation and optimization of the supply chain network.

The invention discloses a multi-network cascading failure propagation prediction method based on a heterogeneous graph neural network under a disaster. The method comprises the following steps: acquiring multi-source data of disaster, electric power, communication and traffic networks; constructing a four-layer heterogeneous graph model, and defining multi-type interlayer edges; establishing a mapping relation between disaster physical quantities and physical node health states, and predicting an initial fault state at a disaster impact moment; defining a multi-scale and multi-mechanism propagation rule based on interlayer edges, and simulating a cascading failure process; a space-time heterogeneous graph neural network model is constructed, a heterogeneous graph neural network module and a gating circulation unit module are stacked in the model, and a double-end prediction layer is adopted to predict the continuous operation state and the discrete function state of nodes in an autoregression mode; and post-processing a state time sequence output by the model, and reconstructing a cross-domain cascading failure propagation path through a causal attribution algorithm. According to the method, the whole evolution process from disaster occurrence to multi-network cascading failure can be accurately simulated, and multi-scale failure prediction and causal analysis are realized.

The invention discloses a cascade fault diagnosis method based on a root cause intensity power set belief rule base. According to the technical scheme, the method comprises the steps of 1, constructing a power set belief rule base; the conclusion hypothesis unit can clearly describe a single-point fault state, a composite fault state and a causal chain fault state. And 2, introducing a root cause strength parameter: introducing the root cause strength parameter into the conclusion hypothesis unit constructed in the step 1 for quantifying the causal influence capability of the fault state as the root cause. And step 3, reasoning fusion: calculating the matching degree and the activation degree of each rule, and applying an evidence theory-based reasoning fusion algorithm to an output result to obtain power set confidence distribution of each fault hypothesis. And step 4, fault diagnosis and fault root cause positioning are carried out, and a main fault root cause is output, and the main fault root cause is the root cause with the maximum root cause strength. The method is mainly used for realizing accurate diagnosis of cascade faults in a complex system by popularizing a traditional BRB model to power set reasoning and introducing a root cause strength concept.

The invention relates to the field of traffic engineering, and discloses an urban road network toughness management platform and evaluation method based on dynamic cascade failure, and the platform comprises a disturbance scene simulation and random capacity degradation module, a dynamic cascade failure process simulation module, and a multi-dimensional toughness index calculation and uncertainty evaluation module. A toughness three-dimensional vector is formed by integrating system robustness, restorability and performance accumulated loss, and a time-varying dynamic traffic distribution model considering road network structure change is used for depicting a cascade failure dynamic process; a random variable is introduced into a damaged road section capacity index, and a new evaluation method is provided for solving the defect that the existing toughness evaluation method is difficult to comprehensively quantify the robustness and the restorability of a road network. A failure diffusion mechanism in an abnormal scene is truly restored, and an effective method is provided for overcoming the double defects that a traditional model is insufficient in quantification of travel behavior dynamics and a system recovery process.

Disclosed is a power-limited network protection system designed to enhance the reliability and stability of networks with multiple remote nodes. This system employs a combination of power supplies and communication transceivers to modulate energy and data transmission, ensuring efficient operation across extensive distances. Each remote node is equipped with an advanced protection device featuring a controllable disconnect switch and monitoring capabilities for current and voltage. This configuration enables independent operation of nodes while preventing cascading failures. By dynamically managing power distribution and implementing fail-safe mechanisms, the system mitigates risks associated with overloads and shorts, ultimately enhancing network resilience. This invention is particularly beneficial in environments prone to electrical disruptions, ensuring continued functionality and minimizing operational downtime.

The invention discloses a cross-modal causal coupling water supply network cascade failure deduction method and system, and relates to the field of safety prevention and control of urban water supply networks. The method comprises the following steps: firstly, constructing a water supply network heterogeneous graph, abstracting physical pipe sections as core nodes, associating the pipe sections as heterogeneous edges, and obtaining static and dynamic attributes of the heterogeneous edges; multi-source heterogeneous data space-time alignment is completed through an exclusive scale adaptive coding layer, and a standardized feature matrix is generated; taking the cross-modal causal directed acyclic graph as a hard constraint, and generating a dynamic coupling adjacency matrix through a cross-modal graph attention layer; dynamic weighted coupling of multi-modal characteristics is realized through a space-time dynamic gating unit; finally, cascade failure evolution is simulated based on the coupling characteristics and the adjacent matrix, critical inflection points are recognized, and graded early warning signals are output. The method solves the problems of modeling distortion, false correlation and inflection-point-free pre-judgment in the traditional technology, greatly improves the deduction precision and the engineering credibility, and is suitable for safety prevention and control and emergency early warning of the urban water supply pipe network.

The invention discloses a risk assessment method for power grid cascading failures, and the method comprises the steps: firstly determining an assessment range and a target, and carrying out the data collection after the assessment range and the target are determined; establishing a system model, and constructing a digital model capable of accurately reflecting physical characteristics, operation states and control behaviors of a real power grid in a computer; constructing an initial fault scene; analyzing a cascading failure propagation path; quantifying risk indexes; and evaluating the cross-domain association influence, supplementing and evaluating the linkage influence on the association system in combination with the cross-domain association characteristics, and proposing a risk prevention and control and optimization strategy. According to the method, potential cascading failure inducements in a power grid can be actively mined through risk assessment of power grid cascading failures, a traditional passive mode of failure reprocessing is broken through, weak links are positioned, key equipment which easily triggers the cascading failures is found out through initial failure scene screening and propagation path simulation, and long-term latent hidden dangers are avoided.

The invention discloses a power system cascading failure chain modeling and blocking method, device and system considering source-load double-end uncertainty, and a medium. The method comprises the steps of constructing source-load uncertainty input distribution (wind power introduces Weibull distribution based on a wind speed segmented power model, photovoltaic introduces Beta distribution based on an irradiance output model, and a load side introduces a normal distribution fluctuation model); an MSFF method is adopted to construct a unified source-load stochastic power flow model, and a multi-scene power flow state set is obtained; introducing a power flow out-of-limit criterion and a hidden fault probability function, building a cascading fault propagation model fusing wind-solar load uncertainty, and dynamically simulating fault chain evolution; and formulating a staged collaborative blocking strategy (cutting off non-critical load emergency control, quickly responding a battery energy storage system and dynamically adjusting a critical line protection constant value) to realize real-time fault suppression. Simulation shows that the method is suitable for power system security defense in a high-proportion new energy penetration scene, and has good engineering adaptability and dynamic control performance.

The invention provides a causal relationship and time sequence characteristic-considered cascading failure rapid screening method and system, and relates to the technical field of power grid cascading failures, and the method comprises the steps of obtaining cascading failure scene data; based on cascading failure scene data, extracting a causal relationship between an initial short-circuit fault and a subsequent fault by using logistic regression and a neural network model; different states of the fault event are converted into graph structures, time delays between the different states of the fault event are obtained based on cascading fault scene data statistics, and time sequence features in the transient evolution process of the cascading fault event are extracted; the probability that the initial fault causes a subsequent fault event is obtained based on a causal relationship, the duration of different states of the fault event is generated by adopting a Monte Carlo sampling method based on time sequence characteristics, and a cascading fault scene is generated; and carrying out risk assessment and probability assessment on the cascading failure scene generated based on the causal relationship and the time sequence characteristics, and finally screening to obtain a high-risk cascading failure scene.

The invention discloses an electrical integrated energy system toughness index evaluation method, which comprises the following steps: firstly, considering disaster-causing uncertainty of extreme disasters, and establishing a typical fault scene set of an electrical integrated energy system; secondly, considering dynamic and static characteristics and coupling constraints of an electric and gas heterogeneous energy flow system, constructing a numerical simulation model of the electrical integrated energy system under a fault condition, and simulating a cascade fault and energy supply recovery process of the system under a typical fault scene set; and finally, based on a simulation result, drawing a multi-stage toughness curve of the system, and constructing a multi-dimensional comprehensive evaluation index system of the electricity-gas dependency under a toughness perspective. The invention further discloses an electrical integrated energy system toughness index evaluation system, full-dimension quantitative analysis of the multi-energy dependency relationship under the fault working condition can be achieved, and weak links caused by multi-energy flow strong coupling can be effectively screened out.

The present disclosure provides a method and system for quickly screening cascading failures that consider causal relationships and timing characteristics, and relates to the technical field of cascading failures in power grids. The method comprises the following steps: obtaining cascading failure scenario data; extracting the causal relationship between an initial short-circuit fault and subsequent faults using logistic regression and a neural network model based on the cascading failure scenario data; converting different states of a fault event into a graph structure, and obtaining time delays between different states of the fault event based on statistics of the cascading failure scenario data, and extracting timing characteristics during the transient evolution of the cascading failure event; obtaining the probability of an initial fault triggering a subsequent fault event based on the causal relationship, and generating a cascading failure scenario using a Monte Carlo sampling method based on the timing characteristics; and performing risk assessment and probability assessment on the cascading failure scenarios generated based on the causal relationship and timing characteristics, and ultimately screening out high-risk cascading failure scenarios.

The invention belongs to the field of underground transportation, and particularly relates to a cascade failure-based subway freight network operation robustness evaluation method. Making a subway freight network cascade failure redistribution strategy; constructing a subway freight network cascade failure load redistribution model; constructing a subway freight network robustness evaluation index; and designing an evaluation algorithm for the robustness of the metro freight network based on the established cascade failure redistribution strategy of the metro freight network in combination with the constructed cascade failure load redistribution model and the proposed robustness evaluation index system, thereby realizing quantitative evaluation of the operation robustness of the network in the cascade failure situation. According to the invention, a scientific basis can be provided for planning and operation management of a subway freight system, and the reliability and safety of an urban comprehensive transportation system are effectively improved.

The invention discloses a cascade failure-based double-layer international railway freight network toughness evaluation method, which belongs to the technical field of road traffic network evaluation, and comprises the following steps: constructing topology models of a basic line network and a transportation service network; constructing a network evaluation system and an importance evaluation system of each node in the network; constructing a network vulnerability evaluation model based on cascade failure, wherein the model adopts an improved CML node state model and a cargo redistribution strategy; and in combination with each network and the evaluation model, a cascade failure condition is simulated through a simulation experiment, and the network is evaluated in combination with an evaluation system. The characteristics of international railway freight are considered, a double-layer coupling network of a basic line network and a transportation service network is constructed, a multi-dimensional toughness evaluation index system and a cargo distribution mechanism are set up, and the cascade failure condition in the international railway freight network can be simulated.

The invention relates to the technical field of power system operation and control, in particular to a power system recovery capability evaluation method, device and equipment considering unconventional risks and a medium, and the method comprises the steps: determining parameters for calculating the occurrence probability of earthquake disasters of different earthquake magnitudes; calculating intensity distribution by using an earthquake intensity diffusion model; calculating transmission tower and transmission line fault probabilities to obtain a fault line set; according to the operation power flow and the maximum allowable power flow, the cascading failure situation is divided into high risk and low risk; aiming at the two conditions, respectively enumerating a first-order fault state set and a second-order fault state set to obtain a system recovery capability initial value; the value serves as input, a convergence threshold value is set, a ULBI-IISE algorithm is adopted for iterative calculation, when the difference value of the upper cut set and the lower complementary set is smaller than the threshold value, the recovery capacity and the interval are output, and the method reduces high-order fault complete enumeration and the calculation amount while guaranteeing the precision, and is suitable for rapid evaluation of emergency scenes such as earthquakes.

The invention discloses a method and device for determining an initial fault line combination of a power system considering cascading failure propagation, electronic equipment and a storage medium, and belongs to the technical field of power system fault recognition. The method comprises the following steps: constructing an attack and defense double-layer optimization model comprising an upper-layer attack model and a lower-layer defense model, wherein the upper-layer attack model aims at maximizing the load loss value, and the lower-layer defense model aims at minimizing the load loss value; the method comprises the following steps of: randomly generating a plurality of candidate fault line combinations containing a preset number of fault lines, respectively simulating a cascading fault propagation process caused by the candidate fault line combinations, obtaining a power grid working condition after a fault is ended, and calculating a load loss value of each candidate combination by utilizing a lower-layer defense model; and selecting the candidate fault line combination with the maximum load loss value as an initial fault line combination of the power system. By implementing the method, the problem that the initial fault line combination of the power system is not accurately determined in the prior art can be solved.

The invention discloses a power distribution communication network fault positioning method, device and equipment and a medium, and the method comprises the steps: obtaining an alarm data flow of a power distribution communication network, and carrying out the recognition based on the alarm data flow, and obtaining a cascading fault cluster; constructing a time sequence causal reasoning model according to the cascading failure cluster, and determining a source alarm and a secondary alarm in the cascading failure; fault position identification is carried out according to alarm data corresponding to the root alarm, and a fault positioning point candidate set is obtained; and based on the fault positioning point candidate set, determining a final fault positioning point according to the matching confidence of the alarm data corresponding to the positioning point and the historical alarm data. According to the invention, the efficiency and accuracy of fault positioning can be improved.

The invention discloses an electric power system cascading failure risk assessment method, system and device based on machine learning and a medium. The method comprises the steps that an electric power system cascading failure probability model is constructed, and an accident chain of an initial failure conduction path is generated; a multi-scene initial fault data set is dynamically generated, and cascading fault risk labels are marked; classifying the multi-scene initial fault data set, storing a risk sub-data set, and outputting a corresponding fault probability; predicting a loss consequence of cascading failures of the risk sub-data set through a machine learning regression model, and quantifying a risk level; and fusing the fault probability and the loss consequence to generate a comprehensive risk assessment index. Through collaborative innovation of accurate modeling, efficient calculation, dynamic optimization and real-time control, triple breakthrough of accuracy, timeliness and operability of cascading failure risk assessment of the high-proportion new energy power system is realized, and a full-chain technical support from risk early warning to active blocking is provided for safe and stable operation of a power grid.

The invention discloses a reinforcement learning-based virtual power plant enhanced recovery strategy method and system. According to the method, information-physical fusion modeling is adopted, and a power layer, an information layer and a coupling layer of a virtual power plant are constructed, so that the influence of key nodes and key lines is accurately evaluated, and a fault recovery sequence is optimized. Firstly, node efficiency, load importance and information-power coupling strength are calculated through a complex network theory, key nodes and lines are identified, and the prevention capability of a system is improved. And secondly, after a fault occurs, an intelligent load redistribution strategy is adopted, power flow adjustment of an overload line is optimized, and cascade failure diffusion is prevented. And finally, optimizing and recovering scheduling by utilizing a reinforcement learning method, and realizing dynamic scheduling optimization. According to the invention, the recovery capability of the virtual power plant under the cascade fault condition is improved, and the toughness and stability of the power grid are improved.

The invention provides a cascade reliability index determination method for a multi-level inter-city road network, and the method comprises the steps: constructing the multi-level inter-city road network of a target region, and the multi-level inter-city road network comprises a first node set and a road segment set; calculating the initial load and capacity of any first node of the first node set; utilizing an attack strategy based on betweenness centrality to trigger cascade failure of the multi-level intercity road network so as to determine an initial failure node from the first node set; taking the initial failure node as a starting point, and simulating a cascade failure propagation process by using a multipath load redistribution model identified and driven by an equiimpedance line until the propagation process is finished; and determining the number of newly added failure nodes, the network efficiency ratio, the global node cascading failure rate and the local node cascading failure rate in each round in the cascading failure propagation process as cascading reliability indexes of the multi-level intercity road network. According to the invention, the authenticity and accuracy of the cascade reliability index of the multi-level inter-city road network of the target area are improved.

The invention discloses a cascading failure-based wind power credible capacity evaluation method and device, and the method comprises the steps: obtaining the topological structure information of a power transmission network frame of a target power system, the conventional attribute information of a conventional unit, and the wind power attribute information of a wind turbine unit, and obtaining the actual power grid operation information of a target region within a preset time period; on the basis of the information, representative scenes of the target power system before, during and after the cascading failure occur are constructed; fault evolution operation simulation is carried out on the target power system in the representative scene before the fault, the representative scene in the fault and the representative scene after the fault, and a power grid state characteristic matrix of the target power system in each representative scene is determined based on simulation results; and based on the power grid state characteristic matrix, determining the wind power credible capacity through alternate iteration by using the upper layer model and the lower layer model.

The invention belongs to the technical field of network security, and discloses an optimization filter-based cyber-physical system cascading failure security assessment detection method, which comprises the following steps of: performing data acquisition on a power system by analyzing a CPS (Cyber-Physical System) architecture, and respectively constructing a data uploading model and a data issuing model; then, learning an optimal filter over time by using the sensor observations to filter out malicious sensor observations while retaining other sensor measurements during data stream transmission; and finally, whether the data stream is attacked in the transmission process is judged by analyzing whether the data transmission quantity is suddenly and abnormally increased or decreased, a detector is optimized, and the false alarm rate is reduced. According to the method, cascading failure analysis is carried out on the CPS through the dynamic complex network, the analysis accuracy is enhanced, and therefore the reliability of the CPS is improved.

The application discloses a kind of energy router cascade failure defense and recovery method, comprising: obtaining the operating state data of multiple ports of energy router, wherein current control mode of each port is contained;Based on operating state data, by constructing a dynamic coupling matrix dependent on real-time control mode, to assess the cascade failure risk of system level, obtain system cascade failure risk index;In response to risk index over-limit or actual failure occurs, by solving an optimization problem with control mode as the core decision variable, generate and execute control instructions for suppressing cascade failure propagation;In response to fault clearance, execute risk-aware ordered recovery process, and perform closed-loop safety review after each step of the recovery sequence to ensure the stability of the recovery process.The application can improve the accuracy of cascade failure risk prediction, the effectiveness of active failure defense and the safety of system failure recovery.

The invention discloses an electric power system cascading failure risk assessment method and system considering new energy power generation uncertainty, and belongs to the technical field of electric power system safety. According to the fault risk assessment method disclosed by the invention, the cascading fault of the power system is modeled to obtain system power flow redistribution and relay protection execution conditions after large-scale transfer of system power flow after the fault, and in addition, rapid simulation of a cascading fault risk model is realized based on a depth-first algorithm of risk estimation knowledge. According to early-stage risk assessment experience and fault feature knowledge, key simulation paths are intelligently screened, high-risk node calculation is preferentially processed, unnecessary calculation branches are greatly reduced, simulation efficiency is effectively improved, the dynamic propagation process of cascading faults in a complex power system is rapidly simulated, and risks can be comprehensively assessed.

This invention proposes a multi-energy safety assessment method and system considering multiple time scales and coupled faults. The method includes: establishing an intermediate time-scale model and a long-time-scale model of the integrated energy system; conducting a safety assessment for each fault scenario in a fault scenario set; wherein, using the long-time-scale model to perform an N-1 safety scan of the fault scenarios considering coupled faults, calculating system risk assessment indicators; when the system risk assessment indicators reflect that the fault scenario may lead to water hammer consequences, using the intermediate time-scale model to calculate the overpressure value generated during the water hammer process; and generating the final safety assessment result of the integrated energy system based on the safety assessment results of each fault scenario. This invention can capture the water hammer effect of the heating network and the cascading faults caused by the coupling of the logical and geographical layers, which are often overlooked in traditional assessments, achieving a more comprehensive and accurate safety assessment of the integrated energy system and helping to improve the operational safety of the system.

The invention discloses a searching method suitable for a cascading failure chain containing a direct current system, and belongs to the technical field of power systems, and the searching method comprises the following steps: S1, early-stage data preparation and format conversion: collecting full-amount basic data of a power grid and uniformly converting multi-format data; s2, constructing an accident chain model containing non-direct current characteristics; s3, setting a fault search constraint and termination criterion, including limiting a search range and defining an accident chain termination criterion; s4, dynamically iteratively searching a cascading failure chain; s5, screening and verifying a high-risk fault chain; and S6, outputting a search result. According to the searching method suitable for the cascading failure chain containing the direct-current system, the risk value is calculated, the high-risk chain is screened, and simulation verification is carried out; and finally, outputting a fault chain evolution diagram and a risk parameter table, thereby accurately positioning a high-risk cascading fault chain in the AC / DC hybrid power grid, providing a clear fault evolution path and risk parameters for power grid dispatching personnel, assisting in formulating a scientific prevention and control strategy, and effectively reducing the occurrence probability of blackout accidents.

This application provides a two-layer prevention and control method and system for grid cascading faults considering the integration of new energy sources. Based on the probability density function and output power function of wind farms and photovoltaic farms, the Monte Carlo method is used to calculate stochastic power flow. Assuming an initial fault occurs on a line and it is disconnected by backup protection, for the remaining lines other than the line with the initial fault, an expression for whether a cascading fault occurs in the grid is established based on the calculated power flow value and its corresponding setting value. The node injection power combination is obtained based on the calculated power flow value, and a grid safety margin is established based on the node injection power combination. An inner-layer optimization model is constructed with minimizing the grid safety margin as the first objective function, and an outer-layer optimization model is constructed with maximizing the grid safety margin and minimizing grid loss cost as the second objective function. The two-layer prevention and control model for cascading faults is solved to obtain a cascading fault prevention and control strategy, thereby enabling early identification and precise and effective prevention and control of cascading faults.

The invention discloses a complex network cascade failure robustness optimization method based on structural hole constraint, and belongs to the technical field of complex network survivability optimization. According to the method, an effective scale index in a social network is introduced, a structural hole theory is combined, a node pair with the maximum structural hole influence is preferentially selected in a complex network for edge adding operation, and dynamic optimization and load balance distribution of the shortest path are achieved. According to the method, the network betweenness range can be effectively reduced, the cascade failure range is reduced, the robustness of a power grid, a communication network and other complex systems is remarkably improved while low calculation complexity is kept, and the method has high practical value and popularization significance.