In wind and solar renewable-dominant hybrid alternating current/direct current(AC/DC)power systems,the active power of high-voltage direct current(HVDC)system is significantly limited by the security and stability eve...In wind and solar renewable-dominant hybrid alternating current/direct current(AC/DC)power systems,the active power of high-voltage direct current(HVDC)system is significantly limited by the security and stability events caused by cascading failures.To identify critical lines in cascading failures,a rapid risk assessment method is proposed based on the gradient boosting decision tree(GBDT)and frequent pat-tern growth(FP-Growth)algorithms.First,security and stability events triggered by cascading failures are analyzed to explain the impact of cascading failures on the maximum DC power.Then,a cascading failure risk index is defined,focusing on the DC power being limited.To handle the strong nonlinear relationship between the maximum DC power and cascading failures,a GBDT with an update strategy is utilized to rapidly predict the maximum DC power under uncertain operating conditions.Finally,the FP-Growth algorithm is improved to mine frequent patterns in cascading failures.The importance index for each fault in a frequent pattern is defined by evaluating its impact on cascading failures,enabling the identification of critical lines.Simulation results of a modified Ningxia–Shandong hybrid AC/DC system in China demonstrate that the proposed method can rapidly assess the risk of cascading failures and effectively identify critical lines.展开更多
Compared to single-layer networks,multilayer networks exhibit a more complex node degree composition,comprising both intra-layer and inter-layer degrees.However,the distinct impacts of these degree types on cascading ...Compared to single-layer networks,multilayer networks exhibit a more complex node degree composition,comprising both intra-layer and inter-layer degrees.However,the distinct impacts of these degree types on cascading failures remain underexplored.Distinguishing their effects is crucial for a deeper understanding of network structure,information propagation,and behavior prediction.This paper proposes a capacity-load model to influence and compare the influence of different degree types on cascading failures in multilayer networks.By designing three node removal strategies based on total degree,intra-layer degree,and inter-layer degree,simulation experiments are conducted on four types of networks.Network robustness is evaluated using the maximum number of removable nodes before collapse.The relationships between network robustness and the coupling coefficient,as well as load and capacity adjustment parameters,are also analyzed.The results indicate that the node removal strategy with the least impact on cascading failures varies across different types of networks,revealing the significance of different node degrees in failure propagation.Compared to other models,the proposed model enables networks to maintain a higher maximum number of removable nodes during cascading failures,demonstrating superior robustness.展开更多
The local-world (LW) evolving network model shows a transition for the degree distribution between the exponential and power-law distributions, depending on the LW size. Cascading failures under intentional attacks in...The local-world (LW) evolving network model shows a transition for the degree distribution between the exponential and power-law distributions, depending on the LW size. Cascading failures under intentional attacks in LW network models with different LW sizes were investigated using the cascading failures load model. We found that the LW size has a significant impact on the network's robustness against deliberate attacks. It is much easier to trigger cascading failures in LW evolving networks with a larger LW size. Therefore, to avoid cascading failures in real networks with local preferential attachment such as the Internet, the World Trade Web and the multi-agent system, the LW size should be as small as possible.展开更多
Cascading failures are common phenomena in many of real-world networks,such as power grids,Internet,transportation networks and social networks.It's worth noting that once one or a few users on a social network ar...Cascading failures are common phenomena in many of real-world networks,such as power grids,Internet,transportation networks and social networks.It's worth noting that once one or a few users on a social network are unavailable for some reasons,they are more likely to influence a large portion of social network.Therefore,an effective mitigation strategy is very critical for avoiding or reducing the impact of cascading failures.In this paper,we firstly quantify the user loads and construct the processes of cascading dynamics,then elaborate the more reasonable mechanism of sharing the extra user loads with considering the features of social networks,and further propose a novel mitigation strategy on social networks against cascading failures.Based on the realworld social network datasets,we evaluate the effectiveness and efficiency of the novel mitigation strategy.The experimental results show that this mitigation strategy can reduce the impact of cascading failures effectively and maintain the network connectivity better with lower cost.These findings are very useful for rationally advertising and may be helpful for avoiding various disasters of cascading failures on many real-world networks.展开更多
Cascading failures often occur in congested networks such as the Internet. A cascading failure can be described as a three-phase process： generation, diffusion, and dissipation of the congestion. In this account, we ...Cascading failures often occur in congested networks such as the Internet. A cascading failure can be described as a three-phase process： generation, diffusion, and dissipation of the congestion. In this account, we present a function that represents the extent of congestion on a given node. This approach is different from existing fimctions based on betweenness centrality. By introducing the concept of ＇delay time＇, we designate an intergradation between permanent removal and nonremoval. We also construct an evaluation fimction of network efficiency, based on congestion, which measures the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability and packet generation speed on congestion propagation. Also, we uncover the relationship between the cascade dynamics and some properties of the network such as structure and size.展开更多
In this article, we investigate cascading failures in complex networks by introducing a feedback. To characterize the effect of the feedback, we define a procedure that involves a self-organization of trip distributio...In this article, we investigate cascading failures in complex networks by introducing a feedback. To characterize the effect of the feedback, we define a procedure that involves a self-organization of trip distribution during the process of cascading failures. For this purpose, user equilibrium with variable demand is used as an alternative way to determine the traffic flow pattern throughout the network. Under the attack, cost function dynamics are introduced to discuss edge overload in complex networks, where each edge is assigned a finite capacity （controlled by parameter α）. We find that scale-free networks without considering the effect of the feedback are expected to be very sensitive to α as compared with random networks, while this situation is largely improved after introducing the feedback.展开更多
At present,the proportion of new energy in the power grid is increasing,and the random fluctuations in power output increase the risk of cascading failures in the power grid.In this paper,we propose a method for ident...At present,the proportion of new energy in the power grid is increasing,and the random fluctuations in power output increase the risk of cascading failures in the power grid.In this paper,we propose a method for identifying high-risk scenarios of interlocking faults in new energy power grids based on a deep embedding clustering(DEC)algorithm and apply it in a risk assessment of cascading failures in different operating scenarios for new energy power grids.First,considering the real-time operation status and system structure of new energy power grids,the scenario cascading failure risk indicator is established.Based on this indicator,the risk of cascading failure is calculated for the scenario set,the scenarios are clustered based on the DEC algorithm,and the scenarios with the highest indicators are selected as the significant risk scenario set.The results of simulations with an example power grid show that our method can effectively identify scenarios with a high risk of cascading failures from a large number of scenarios.展开更多
Among various power system disturbances,cascading failures are considered the most serious and extreme threats to grid operations,potentially leading to significant stability issues or even widespread power blackouts....Among various power system disturbances,cascading failures are considered the most serious and extreme threats to grid operations,potentially leading to significant stability issues or even widespread power blackouts.Simulating power systems’behaviors during cascading failures is of great importance to comprehend how failures originate and propagate,as well as to develop effective preventive and mitigative control strategies.The intricate mechanism of cascading failures,characterized by multi-timescale dynamics,presents exceptional challenges for their simulations.This paper provides a comprehensive review of simulation models for cascading failures,providing a systematic categorization and a comparison of these models.The challenges and potential research directions for the future are also discussed.展开更多
This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system,and identifies vulnerable nodes.First,considering the monitoring and control func...This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system,and identifies vulnerable nodes.First,considering the monitoring and control functions of a cyber network and power flow characteristics of a power network,a power cyber-physical system model is established.Then,the influences of a false data attack on the decision-making and control processes of the cyber network communication processes are studied,and a cascading failure analysis process is proposed for the cyber-attack environment.In addition,a vulnerability evaluation index is defined from two perspectives,i.e.,the topology integrity and power network operation characteristics.Moreover,the effectiveness of a power flow betweenness assessment for vulnerable nodes in the cyberphysical environment is verified based on comparing the node power flow betweenness and vulnerability assessment index.Finally,an IEEE14-bus power network is selected for constructing a power cyber-physical system.Simulations show that both the uplink communication channel and downlink communication channel suffer from false data attacks,which affect the ability of the cyber network to suppress the propagation of cascading failures,and expand the scale of the cascading failures.The vulnerability evaluation index is calculated for each node,so as to verify the effectiveness of identifying vulnerable nodes based on the power flow betweenness.展开更多
With society＇s increasing dependence on critical infrastructure such as power grids and communications systems, the robustness of these systems has attracted significant attention.Failure of some nodes can trigger a ...With society＇s increasing dependence on critical infrastructure such as power grids and communications systems, the robustness of these systems has attracted significant attention.Failure of some nodes can trigger a cascading failure, which completely fragments the network, necessitating recovery efforts to improve robustness of complex systems. Inspired by real-world scenarios, this paper proposes repair models after two kinds of network failures, namely complete and incomplete collapse. In both models, three kinds of repair strategies are possible, including random selection（RS）, node selection based on single network node degree（SD）, and node selection based on double network node degree（DD）. We find that the node correlation in each of the two coupled networks affects repair efficiency. Numerical simulation and analysis results suggest that the repair node ratio and repair strategies may have a significant impact on the economics of the repair process. The results of this study thus provide insight into ways to improve the robustness of coupled networks after cascading failures.展开更多
This paper investigates cascading failures in networks by considering interplay between the flow dynamic and the network topology, where the fluxes exchanged between a pair of nodes can be adaptively adjusted dependin...This paper investigates cascading failures in networks by considering interplay between the flow dynamic and the network topology, where the fluxes exchanged between a pair of nodes can be adaptively adjusted depending on the changes of the shortest path lengths between them. The simulations on both an artificially created scale-free network and the real network structure of the power grid reveal that the adaptive adjustment of the fluxes can drastically enhance the robustness of complex networks against cascading failures. Particularly, there exists an optimal region where the propagation of the cascade is significantly suppressed and the fluxes supported by the network are maximal. With this understanding, a costless strategy of defense for preventing cascade breakdown is proposed. It is shown to be more effective for suppressing the propagation of the cascade than the recent proposed strategy of defense based on the intentional removal of nodes.展开更多
With the development of network science,the coupling between networks has become the focus of complex network research.However,previous studies mainly focused on the coupling between nodes,while ignored the coupling b...With the development of network science,the coupling between networks has become the focus of complex network research.However,previous studies mainly focused on the coupling between nodes,while ignored the coupling between edges.We propose a novel cascading failure model of two-layer networks.The model considers the different loads and capacities of edges,as well as the elastic and coupling relationship between edges.In addition,a more flexible load-capacity strategy is adopted to verify the model.The simulation results show that the model is feasible.Different networks have different behaviors for the same parameters.By changing the load parameters,capacity parameters,overload parameters,and distribution parameters reasonably,the robustness of the model can be significantly improved.展开更多
Network robustness is one of the core contents of complex network security research.This paper focuses on the robustness of community networks with respect to cascading failures,considering the nodes influence and com...Network robustness is one of the core contents of complex network security research.This paper focuses on the robustness of community networks with respect to cascading failures,considering the nodes influence and community heterogeneity.A novel node influence ranking method,community-based Clustering-LeaderRank(CCL)algorithm,is first proposed to identify influential nodes in community networks.Simulation results show that the CCL method can effectively identify the influence of nodes.Based on node influence,a new cascading failure model with heterogeneous redistribution strategy is proposed to describe and analyze node fault propagation in community networks.Analytical and numerical simulation results on cascading failure show that the community attribute has an important influence on the cascading failure process.The network robustness against cascading failures increases when the load is more distributed to neighbors of the same community instead of different communities.When the initial load distribution and the load redistribution strategy based on the node influence are the same,the network shows better robustness against node failure.展开更多
In order to accurately receive early warning of the cascading failures caused by coordinated cyber-attacks(CFCC)in grid cyber-physical systems(GCPS),an adaptive early warning method of CFCC is proposed.First,the evolu...In order to accurately receive early warning of the cascading failures caused by coordinated cyber-attacks(CFCC)in grid cyber-physical systems(GCPS),an adaptive early warning method of CFCC is proposed.First,the evolutionary mechanism of CFCC is analyzed from the attackers'view,the CFCC mathematical model is established,and the transition processes of GCPS running states under the influence of CFCC staged failures are discussed.Then,the mathematical model of the adaptive early warning method is established.Further,the mathematical model of the adaptive early warning method is mapped as an adaptive control process with tolerating staged failures damage,and the solving process is presented to infer the CFCC and its next evolution trend.A decision-making idea for the optimal active defense scheme is proposed considering the costs and gains of various defense measures.Finally,to verify the effectiveness of the adaptive early warning method,the warning and defense processes of a typical CFCC are simulated in a GCPS experimental system based on CEPRI-36 BUS.展开更多
Critical infrastructures are becoming increasingly interdependent and vulnerable to cascading failures. Existing studies have analyzed the vulnerability of interdependent networks to cascading failures from the static...Critical infrastructures are becoming increasingly interdependent and vulnerable to cascading failures. Existing studies have analyzed the vulnerability of interdependent networks to cascading failures from the static perspective of network topology structure. This paper develops a more realistic cascading failures model that considers the dynamic redistribution of load in power network to explore the vulnerability of interdependent power-water networks. In this model, the critical tolerance threshold is originally proposed to indicate the vulnerability of network to cascading failures. In addition, some key parameters that are important to network vulnerability are identified and quantified through numerical simulation. Results show that cascading failures can be prevented when the values of tolerance parameter are above a critical tolerance threshold. Otherwise interdependent networks collapse after attacking a critical fraction of power nodes. Interdependent networks become more vulnerable with the increase in interdependence strength, which implies the importance of protecting those interconnected nodes to reduce the consequences of cascading failures. Interdependent networks are most vulnerable under high-load attack, which shows the significance of protecting high-load nodes.展开更多
Analyzing the vulnerability of power systems in cascading failures is generally regarded as a challenging problem.Although existing studies can extract some critical rules,they fail to capture the complex subtleties u...Analyzing the vulnerability of power systems in cascading failures is generally regarded as a challenging problem.Although existing studies can extract some critical rules,they fail to capture the complex subtleties under different operational conditions.In recent years,several deep learning methods have been applied to address this issue.However,most of the existing deep learning methods consider only the grid topology of a power system in terms of topological connections,but do not encompass a power system’s spatial information such as the electrical distance to increase the accuracy in the process of graph convolution.In this paper,we construct a novel power-weighted line graph that uses power system topology and spatial information to optimize the edge weight assignment of the line graph.Then we propose a multi-graph convolutional network(MGCN)based on a graph classification task,which preserves a power system’s spatial correlations and captures the relationships among physical components.Our model can better handle the problem with power systems that have parallel lines,where our method can maintain desirable accuracy in modeling systems with these extra topology features.To increase the interpretability of the model,we present the MGCN using layer-wise relevance propagation and quantify the contributing factors of model classification.展开更多
Power grids,due to their lack of network redundancy and structural interdependence,are particularly vulnerable to cascading failures,a phenomenon where a few failed nodes—having their loads exceeding their capacities...Power grids,due to their lack of network redundancy and structural interdependence,are particularly vulnerable to cascading failures,a phenomenon where a few failed nodes—having their loads exceeding their capacities—can trigger a widespread collapse of all nodes.Here,we extend the cascading failure(Motter-Lai)model to a more realistic perspective,where each node’s load capacity is determined to be nonlinearly correlated with the node’s centrality.Our analysis encompasses a range of synthetic networks featuring small-world or scale-free properties,as well as real-world network configurations like the IEEE bus systems and the US power grid.We find that fine-tuning this nonlinear relationship can significantly enhance a network’s robustness against cascading failures when the network nodes are under attack.Additionally,the selection of initial nodes and the attack strategies also impact overall network robustness.Our findings offer valuable insights for improving the safety and resilience of power grids,bringing us closer to understanding cascading failures in a more realistic context.展开更多
Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analy...Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analysis of interdependent net-works is insufficient for describing the load characteristics and dependencies of subnetworks,and it is difficult to use for model-ing and failure analysis of power-combat(P-C)coupling net-works.This paper considers the physical characteristics of the two subnetworks and studies the mechanism of fault propaga-tion between subnetworks and across systems.Then the surviv-ability of the coupled network is evaluated.Firstly,an integrated modeling approach for the combat system and power system is predicted based on interdependent network theory.A heteroge-neous one-way interdependent network model based on proba-bility dependence is constructed.Secondly,using the operation loop theory,a load-capacity model based on combat-loop betweenness is proposed,and the cascade failure model of the P-C coupling system is investigated from three perspectives:ini-tial capacity,allocation strategy,and failure mechanism.Thirdly,survivability indexes based on load loss rate and network sur-vival rate are proposed.Finally,the P-C coupling system is con-structed based on the IEEE 118-bus system to demonstrate the proposed method.展开更多
This paper discusses the primary causes from the point of synergistic effects to improve power system vulnerability in the power system planning and safety operation. Based on the vulnerability conception in the compl...This paper discusses the primary causes from the point of synergistic effects to improve power system vulnerability in the power system planning and safety operation. Based on the vulnerability conception in the complex network theory the vulnerability of the power system can be evaluated by the minimum load loss rate when considering power supply ability.Consequently according to the synergistic effect theory the critical line of the power system is defined by its influence on failure set vulnerability in N-k contingencies.The cascading failure modes are proposed based on the criterion whether the acceptable load curtailment level is below a preset value.Significant conclusions are revealed by results of IEEE 39 case analysis weak points of power networks and heavy load condition are the main causes of large-scale cascading failures damaging synergistic effects can result in partial failure developed into large-scale cascading failures vulnerable lines of power systems can directly lead the partial failure to deteriorate into a large blackout while less vulnerable lines can cause a large-scale cascading failure.展开更多
Based on the relationship between capacity and load, cascading failure on weighted complex networks is investigated, and a load-capacity optimal relationship （LCOR） model is proposed in this paper. Compared with thr...Based on the relationship between capacity and load, cascading failure on weighted complex networks is investigated, and a load-capacity optimal relationship （LCOR） model is proposed in this paper. Compared with three other kinds of load- capacity linear or non-linear relationship models in model networks as well as a number of real-world weighted networks including the railway network, the airports network and the metro network, the LCOR model is shown to have the best robustness against cascading failure with less cost. Furthermore, theoretical analysis and computational method of its cost threshold are provided to validate the effectiveness of the LCOR model. The results show that the LCOR model is effective for designing real-world networks with high robustness and less cost against cascading failure.展开更多
基金supported by the National Key Research and Development Program of China"Key technologies for system stability and HVDC transmission of large-scale renewable energy generation base without conventional power support(2022YFB2402700)"the project of the State Grid Corporation of China(52272222001J).
文摘In wind and solar renewable-dominant hybrid alternating current/direct current(AC/DC)power systems,the active power of high-voltage direct current(HVDC)system is significantly limited by the security and stability events caused by cascading failures.To identify critical lines in cascading failures,a rapid risk assessment method is proposed based on the gradient boosting decision tree(GBDT)and frequent pat-tern growth(FP-Growth)algorithms.First,security and stability events triggered by cascading failures are analyzed to explain the impact of cascading failures on the maximum DC power.Then,a cascading failure risk index is defined,focusing on the DC power being limited.To handle the strong nonlinear relationship between the maximum DC power and cascading failures,a GBDT with an update strategy is utilized to rapidly predict the maximum DC power under uncertain operating conditions.Finally,the FP-Growth algorithm is improved to mine frequent patterns in cascading failures.The importance index for each fault in a frequent pattern is defined by evaluating its impact on cascading failures,enabling the identification of critical lines.Simulation results of a modified Ningxia–Shandong hybrid AC/DC system in China demonstrate that the proposed method can rapidly assess the risk of cascading failures and effectively identify critical lines.
基金supported by the National Social Science Fund Project(No.23&ZD115)the Graduate Student Research Innovation Project of the School of Mathematics and Statistics,Hubei Minzu University(No.STK2023011)。
文摘Compared to single-layer networks,multilayer networks exhibit a more complex node degree composition,comprising both intra-layer and inter-layer degrees.However,the distinct impacts of these degree types on cascading failures remain underexplored.Distinguishing their effects is crucial for a deeper understanding of network structure,information propagation,and behavior prediction.This paper proposes a capacity-load model to influence and compare the influence of different degree types on cascading failures in multilayer networks.By designing three node removal strategies based on total degree,intra-layer degree,and inter-layer degree,simulation experiments are conducted on four types of networks.Network robustness is evaluated using the maximum number of removable nodes before collapse.The relationships between network robustness and the coupling coefficient,as well as load and capacity adjustment parameters,are also analyzed.The results indicate that the node removal strategy with the least impact on cascading failures varies across different types of networks,revealing the significance of different node degrees in failure propagation.Compared to other models,the proposed model enables networks to maintain a higher maximum number of removable nodes during cascading failures,demonstrating superior robustness.
基金the National Basic Research Program (973) of China (No. 2004CB217902)the National Natural Science Foundation of China (Nos. 60421002 and 60804045)the Postdoctoral Science Foundation of China (No. 20070421163)
文摘The local-world (LW) evolving network model shows a transition for the degree distribution between the exponential and power-law distributions, depending on the LW size. Cascading failures under intentional attacks in LW network models with different LW sizes were investigated using the cascading failures load model. We found that the LW size has a significant impact on the network's robustness against deliberate attacks. It is much easier to trigger cascading failures in LW evolving networks with a larger LW size. Therefore, to avoid cascading failures in real networks with local preferential attachment such as the Internet, the World Trade Web and the multi-agent system, the LW size should be as small as possible.
基金supported by the National Key Technology R&D Program of China under Grant No.2012BAH46B04
文摘Cascading failures are common phenomena in many of real-world networks,such as power grids,Internet,transportation networks and social networks.It's worth noting that once one or a few users on a social network are unavailable for some reasons,they are more likely to influence a large portion of social network.Therefore,an effective mitigation strategy is very critical for avoiding or reducing the impact of cascading failures.In this paper,we firstly quantify the user loads and construct the processes of cascading dynamics,then elaborate the more reasonable mechanism of sharing the extra user loads with considering the features of social networks,and further propose a novel mitigation strategy on social networks against cascading failures.Based on the realworld social network datasets,we evaluate the effectiveness and efficiency of the novel mitigation strategy.The experimental results show that this mitigation strategy can reduce the impact of cascading failures effectively and maintain the network connectivity better with lower cost.These findings are very useful for rationally advertising and may be helpful for avoiding various disasters of cascading failures on many real-world networks.
基金the National Natural Science Foundation of China (No. 60573128)the Ph.D. Programs Foundation of Ministry of Education of China (No. 20060183043)+1 种基金the China–British Columbia Innovation and Commercialization Strategic Develop-ment Grant (No. 2008DFA12140)the Jilin University 985 Graduate Student Innovation Foundation (No. 20080235)
文摘Cascading failures often occur in congested networks such as the Internet. A cascading failure can be described as a three-phase process： generation, diffusion, and dissipation of the congestion. In this account, we present a function that represents the extent of congestion on a given node. This approach is different from existing fimctions based on betweenness centrality. By introducing the concept of ＇delay time＇, we designate an intergradation between permanent removal and nonremoval. We also construct an evaluation fimction of network efficiency, based on congestion, which measures the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability and packet generation speed on congestion propagation. Also, we uncover the relationship between the cascade dynamics and some properties of the network such as structure and size.
基金Project partly supported by National Basic Research Program of China (Grant No 2006CB705500)National Natural Science Foundation of China (Grant Nos 70631001, 70671008 and 70801005)the Innovation Foundation of Science and Technology for Excellent Doctorial Candidate of Beijing Jiaotong University (Grant No 48033)
文摘In this article, we investigate cascading failures in complex networks by introducing a feedback. To characterize the effect of the feedback, we define a procedure that involves a self-organization of trip distribution during the process of cascading failures. For this purpose, user equilibrium with variable demand is used as an alternative way to determine the traffic flow pattern throughout the network. Under the attack, cost function dynamics are introduced to discuss edge overload in complex networks, where each edge is assigned a finite capacity （controlled by parameter α）. We find that scale-free networks without considering the effect of the feedback are expected to be very sensitive to α as compared with random networks, while this situation is largely improved after introducing the feedback.
基金funded by the State Grid Limited Science and Technology Project of China,Grant Number SGSXDK00DJJS2200144.
文摘At present,the proportion of new energy in the power grid is increasing,and the random fluctuations in power output increase the risk of cascading failures in the power grid.In this paper,we propose a method for identifying high-risk scenarios of interlocking faults in new energy power grids based on a deep embedding clustering(DEC)algorithm and apply it in a risk assessment of cascading failures in different operating scenarios for new energy power grids.First,considering the real-time operation status and system structure of new energy power grids,the scenario cascading failure risk indicator is established.Based on this indicator,the risk of cascading failure is calculated for the scenario set,the scenarios are clustered based on the DEC algorithm,and the scenarios with the highest indicators are selected as the significant risk scenario set.The results of simulations with an example power grid show that our method can effectively identify scenarios with a high risk of cascading failures from a large number of scenarios.
基金supported by UT-Battelle,LLC under Contract No.DE-AC05-00OR22725 with the U.S.Department of Energy.
文摘Among various power system disturbances,cascading failures are considered the most serious and extreme threats to grid operations,potentially leading to significant stability issues or even widespread power blackouts.Simulating power systems’behaviors during cascading failures is of great importance to comprehend how failures originate and propagate,as well as to develop effective preventive and mitigative control strategies.The intricate mechanism of cascading failures,characterized by multi-timescale dynamics,presents exceptional challenges for their simulations.This paper provides a comprehensive review of simulation models for cascading failures,providing a systematic categorization and a comparison of these models.The challenges and potential research directions for the future are also discussed.
基金the National Natural Science Foundation of China(61873057)the Education Department of Jilin Province(JJKH20200118KJ).
文摘This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system,and identifies vulnerable nodes.First,considering the monitoring and control functions of a cyber network and power flow characteristics of a power network,a power cyber-physical system model is established.Then,the influences of a false data attack on the decision-making and control processes of the cyber network communication processes are studied,and a cascading failure analysis process is proposed for the cyber-attack environment.In addition,a vulnerability evaluation index is defined from two perspectives,i.e.,the topology integrity and power network operation characteristics.Moreover,the effectiveness of a power flow betweenness assessment for vulnerable nodes in the cyberphysical environment is verified based on comparing the node power flow betweenness and vulnerability assessment index.Finally,an IEEE14-bus power network is selected for constructing a power cyber-physical system.Simulations show that both the uplink communication channel and downlink communication channel suffer from false data attacks,which affect the ability of the cyber network to suppress the propagation of cascading failures,and expand the scale of the cascading failures.The vulnerability evaluation index is calculated for each node,so as to verify the effectiveness of identifying vulnerable nodes based on the power flow betweenness.
基金supported by the National Natural Science Foundation of China(60972145)the National Aerospace Science Foundation of China(20140751008)
文摘With society＇s increasing dependence on critical infrastructure such as power grids and communications systems, the robustness of these systems has attracted significant attention.Failure of some nodes can trigger a cascading failure, which completely fragments the network, necessitating recovery efforts to improve robustness of complex systems. Inspired by real-world scenarios, this paper proposes repair models after two kinds of network failures, namely complete and incomplete collapse. In both models, three kinds of repair strategies are possible, including random selection（RS）, node selection based on single network node degree（SD）, and node selection based on double network node degree（DD）. We find that the node correlation in each of the two coupled networks affects repair efficiency. Numerical simulation and analysis results suggest that the repair node ratio and repair strategies may have a significant impact on the economics of the repair process. The results of this study thus provide insight into ways to improve the robustness of coupled networks after cascading failures.
基金Project supported by the National Natural Science Foundation of China(Grant No.30570432)the General Project of Hunan Provincial Educational Department of China(Grant No.07C754)
文摘This paper investigates cascading failures in networks by considering interplay between the flow dynamic and the network topology, where the fluxes exchanged between a pair of nodes can be adaptively adjusted depending on the changes of the shortest path lengths between them. The simulations on both an artificially created scale-free network and the real network structure of the power grid reveal that the adaptive adjustment of the fluxes can drastically enhance the robustness of complex networks against cascading failures. Particularly, there exists an optimal region where the propagation of the cascade is significantly suppressed and the fluxes supported by the network are maximal. With this understanding, a costless strategy of defense for preventing cascade breakdown is proposed. It is shown to be more effective for suppressing the propagation of the cascade than the recent proposed strategy of defense based on the intentional removal of nodes.
基金the National Natural Science Foundation of China(Grant No.61663030)the Natural Science Foundation of Jiangxi Province,China(Grant No.20142BAB207021)the Innovation Fund Designated for Graduate Students of Jiangxi Province,China(Grant No.YC2021-S680).
文摘With the development of network science,the coupling between networks has become the focus of complex network research.However,previous studies mainly focused on the coupling between nodes,while ignored the coupling between edges.We propose a novel cascading failure model of two-layer networks.The model considers the different loads and capacities of edges,as well as the elastic and coupling relationship between edges.In addition,a more flexible load-capacity strategy is adopted to verify the model.The simulation results show that the model is feasible.Different networks have different behaviors for the same parameters.By changing the load parameters,capacity parameters,overload parameters,and distribution parameters reasonably,the robustness of the model can be significantly improved.
基金the National Natural Science Foundation of China(Grant Nos.62203229,61672298,61873326,and 61802155)the Philosophy and Social Sciences Research of Universities in Jiangsu Province(Grant No.2018SJZDI142)+2 种基金the Natural Science Research Projects of Universities in Jiangsu Province(Grant No.20KJB120007)the Jiangsu Natural Science Foundation Youth Fund Project(Grant No.BK20200758)Qing Lan Project and the Science and Technology Project of Market Supervision Administration of Jiangsu Province(Grant No.KJ21125027)。
文摘Network robustness is one of the core contents of complex network security research.This paper focuses on the robustness of community networks with respect to cascading failures,considering the nodes influence and community heterogeneity.A novel node influence ranking method,community-based Clustering-LeaderRank(CCL)algorithm,is first proposed to identify influential nodes in community networks.Simulation results show that the CCL method can effectively identify the influence of nodes.Based on node influence,a new cascading failure model with heterogeneous redistribution strategy is proposed to describe and analyze node fault propagation in community networks.Analytical and numerical simulation results on cascading failure show that the community attribute has an important influence on the cascading failure process.The network robustness against cascading failures increases when the load is more distributed to neighbors of the same community instead of different communities.When the initial load distribution and the load redistribution strategy based on the node influence are the same,the network shows better robustness against node failure.
基金supported by National Natural Science Foundation of China(No.51977155).
文摘In order to accurately receive early warning of the cascading failures caused by coordinated cyber-attacks(CFCC)in grid cyber-physical systems(GCPS),an adaptive early warning method of CFCC is proposed.First,the evolutionary mechanism of CFCC is analyzed from the attackers'view,the CFCC mathematical model is established,and the transition processes of GCPS running states under the influence of CFCC staged failures are discussed.Then,the mathematical model of the adaptive early warning method is established.Further,the mathematical model of the adaptive early warning method is mapped as an adaptive control process with tolerating staged failures damage,and the solving process is presented to infer the CFCC and its next evolution trend.A decision-making idea for the optimal active defense scheme is proposed considering the costs and gains of various defense measures.Finally,to verify the effectiveness of the adaptive early warning method,the warning and defense processes of a typical CFCC are simulated in a GCPS experimental system based on CEPRI-36 BUS.
基金Acknowledgments This work is supported by National Natural Science Foundation of China （No. 71501158 71471146） and ＂the Fundamental Research Funds for the Central Universities＂. The authors would like to thank the referees for their efforts to improve the quality of this paper.
文摘Critical infrastructures are becoming increasingly interdependent and vulnerable to cascading failures. Existing studies have analyzed the vulnerability of interdependent networks to cascading failures from the static perspective of network topology structure. This paper develops a more realistic cascading failures model that considers the dynamic redistribution of load in power network to explore the vulnerability of interdependent power-water networks. In this model, the critical tolerance threshold is originally proposed to indicate the vulnerability of network to cascading failures. In addition, some key parameters that are important to network vulnerability are identified and quantified through numerical simulation. Results show that cascading failures can be prevented when the values of tolerance parameter are above a critical tolerance threshold. Otherwise interdependent networks collapse after attacking a critical fraction of power nodes. Interdependent networks become more vulnerable with the increase in interdependence strength, which implies the importance of protecting those interconnected nodes to reduce the consequences of cascading failures. Interdependent networks are most vulnerable under high-load attack, which shows the significance of protecting high-load nodes.
基金Project supported by the National Natural Science Foundation of China(No.U1866602)the Natural Science Foundation of Zhejiang Province,China(No.LZ22F020015)。
文摘Analyzing the vulnerability of power systems in cascading failures is generally regarded as a challenging problem.Although existing studies can extract some critical rules,they fail to capture the complex subtleties under different operational conditions.In recent years,several deep learning methods have been applied to address this issue.However,most of the existing deep learning methods consider only the grid topology of a power system in terms of topological connections,but do not encompass a power system’s spatial information such as the electrical distance to increase the accuracy in the process of graph convolution.In this paper,we construct a novel power-weighted line graph that uses power system topology and spatial information to optimize the edge weight assignment of the line graph.Then we propose a multi-graph convolutional network(MGCN)based on a graph classification task,which preserves a power system’s spatial correlations and captures the relationships among physical components.Our model can better handle the problem with power systems that have parallel lines,where our method can maintain desirable accuracy in modeling systems with these extra topology features.To increase the interpretability of the model,we present the MGCN using layer-wise relevance propagation and quantify the contributing factors of model classification.
基金supported by the National Key R&D Program of China for International S&T Cooperation Projects(No.2019YFE0118700)National Natural Science Foundation of China(Nos.62222306 and 61973110)+1 种基金Hunan Young Talents Science and Technology Innovation Project(No.2020RC3048)Natural Science Found for Distinguished Young Scholars of Hunan Province(No.2021JJ10030).
文摘Power grids,due to their lack of network redundancy and structural interdependence,are particularly vulnerable to cascading failures,a phenomenon where a few failed nodes—having their loads exceeding their capacities—can trigger a widespread collapse of all nodes.Here,we extend the cascading failure(Motter-Lai)model to a more realistic perspective,where each node’s load capacity is determined to be nonlinearly correlated with the node’s centrality.Our analysis encompasses a range of synthetic networks featuring small-world or scale-free properties,as well as real-world network configurations like the IEEE bus systems and the US power grid.We find that fine-tuning this nonlinear relationship can significantly enhance a network’s robustness against cascading failures when the network nodes are under attack.Additionally,the selection of initial nodes and the attack strategies also impact overall network robustness.Our findings offer valuable insights for improving the safety and resilience of power grids,bringing us closer to understanding cascading failures in a more realistic context.
基金supported by the National Natural Science Foundation of China(72271242)Hunan Provincial Natural Science Foundation of China for Excellent Young Scholars(2022JJ20046).
文摘Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analysis of interdependent net-works is insufficient for describing the load characteristics and dependencies of subnetworks,and it is difficult to use for model-ing and failure analysis of power-combat(P-C)coupling net-works.This paper considers the physical characteristics of the two subnetworks and studies the mechanism of fault propaga-tion between subnetworks and across systems.Then the surviv-ability of the coupled network is evaluated.Firstly,an integrated modeling approach for the combat system and power system is predicted based on interdependent network theory.A heteroge-neous one-way interdependent network model based on proba-bility dependence is constructed.Secondly,using the operation loop theory,a load-capacity model based on combat-loop betweenness is proposed,and the cascade failure model of the P-C coupling system is investigated from three perspectives:ini-tial capacity,allocation strategy,and failure mechanism.Thirdly,survivability indexes based on load loss rate and network sur-vival rate are proposed.Finally,the P-C coupling system is con-structed based on the IEEE 118-bus system to demonstrate the proposed method.
基金The National Natural Science Foundation of China(No.51277028)
文摘This paper discusses the primary causes from the point of synergistic effects to improve power system vulnerability in the power system planning and safety operation. Based on the vulnerability conception in the complex network theory the vulnerability of the power system can be evaluated by the minimum load loss rate when considering power supply ability.Consequently according to the synergistic effect theory the critical line of the power system is defined by its influence on failure set vulnerability in N-k contingencies.The cascading failure modes are proposed based on the criterion whether the acceptable load curtailment level is below a preset value.Significant conclusions are revealed by results of IEEE 39 case analysis weak points of power networks and heavy load condition are the main causes of large-scale cascading failures damaging synergistic effects can result in partial failure developed into large-scale cascading failures vulnerable lines of power systems can directly lead the partial failure to deteriorate into a large blackout while less vulnerable lines can cause a large-scale cascading failure.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 60804066 and 61165007)the Scientific and Technological Project of Education Department of Jiangxi Province, China (Grant Nos. GJJ12286 and KJLD12068)
文摘Based on the relationship between capacity and load, cascading failure on weighted complex networks is investigated, and a load-capacity optimal relationship （LCOR） model is proposed in this paper. Compared with three other kinds of load- capacity linear or non-linear relationship models in model networks as well as a number of real-world weighted networks including the railway network, the airports network and the metro network, the LCOR model is shown to have the best robustness against cascading failure with less cost. Furthermore, theoretical analysis and computational method of its cost threshold are provided to validate the effectiveness of the LCOR model. The results show that the LCOR model is effective for designing real-world networks with high robustness and less cost against cascading failure.
