Cascading Failure Mechanism Research Articles

Robustness evaluation method and defense strategy of electricity-heat integrated energy system

Even though electricity-heat integrated energy systems (IESs) can improve energy utilization, the faults generated by extreme events can induce more complex and wider impacts. Therefore, it is urgent to study the effective defense strategies associated with electricity-heat IES. Considering the theory of complex networks, a dynamic model was established in this paper which comprehensively considered the actual operating characteristics and cascading failure process of the electricity-heat IES. The structural and functional robustness of the electricity-heat IES after failure was evaluated by link survivability, capacity survivability and power survivability. According to the post-disaster system robustness evaluation results and system characteristics without adopting the defense strategy, the critical links of the system were identified. Also, seven defense strategies were formulated based on the cascading failure mechanism of the electricity-heat IES. The testing network coupled with an improved IEEE118-node power grid and 23-node heat supply network was used to verify the effectiveness of the proposed defense strategy and to provide a theoretical basis for the resilience enhancement strategy and defense resource allocation of the electricity-heat IES.

A network-based simulation framework for robustness assessment of accessibility in healthcare systems with the consideration of cascade failures

The accessibility of healthcare system is vulnerable to various types of hazards, where the failure of one system component may lead to a diffusion of the pressure and result in cascading failures. This study proposes a network-based simulation framework for robustness assessment of access to healthcare through integrating cascading failure mechanism. Weighted complex networks are constructed to model the accessible patient transfer under both general and elderly healthcare scenarios. The cascade failure mechanism is incorporated into the constructed networks, and several attack strategies (including random, initial degree (ID), initial betweenness (IB), recalculated degree (RD), and recalculated betweenness (RB) attack) are adopted to simulate the process of system robustness assessment. Results indicate that the proposed framework enables to discover the vulnerable nodes in the constructed healthcare accessibility networks, where the robustness metric combining network efficiency and relative size of the largest component acts as a benchmark; all the intentional attack strategies outperform the random attack strategy, which indicates the effectiveness of the detection of vulnerable healthcare facilities by the developed model; and the metrics of node degree and betweenness centrality make progress on identifying the vulnerable healthcare facility nodes, which should be taken heed of to optimize the management and operation of healthcare systems.

Hierarchical Blocking Control for Mitigating Cascading Failures in Power Systems with Wind Power Integration

The increasing uncertainty of wind power brings greater challenges to the control for mitigation of cascading failures. In order to minimize the risk of cascading failures in large-scale wind power systems at a lower economic cost, a multi-stage blocking control model is proposed based on sensitivity analysis. Firstly, the propagation mechanism of cascading failures in power systems with wind power integration is analyzed, and the propagation path of such failures is predicted. Subsequently, sensitive lines that are prone to failure are identified using the power sensitivity matrix, taking into account the effects of blocking control on the propagation path. By constraining the power flow of these sensitive lines, a multi-stage blocking control model for the predicted cascading failure path is proposed with the objective of minimizing the control cost and cascading failure probability. Based on probabilistic optimal power flow calculations, the constraints related to wind power uncertainty are transformed into opportunity constraints. To validate the effectiveness of the proposed model, the IEEE 39-node system is used as an example, and the results show that the obtained control method is able to balance economy and safety. In addition, the control costs for the same initial failure are higher as the wind power penetration rates and confidence levels increase.

(Invited) Challenges for Accelerating Life Testing of Commercial Lithium-Ion Batteries

Life testing of commercial lithium-ion batteries is critical for predicting lifetime, anticipating failure, and guaranteeing safe operation of real-world battery energy storage systems. The traditional method for conducting life testing is to use accelerated aging experiments, where stress factors such as temperature, charge/discharge rate, or daily charge-throughput are pushed to extremes to drive cell failure, while taking care not to induce degradation mechanisms that do not reflect real-world use. But even ‘accelerated’ aging tests generally require 6 months to several years of testing to reach end-of-life for the current generation of mass-produced lithium-ion batteries. So, many efforts have been made to accelerate ‘accelerated aging’ of commercial cells throughout the battery community. But it is critical to ensure that the results of invasive or novel accelerated life testing experiments match well with not only changes to the electrochemical performance of traditionally aged cells, but also that the impacts of physical or chemical degradation mechanisms are also well characterized.This work compares the results of a 2-year accelerated aging test conducted on 23 commercial large-format NMC-Gr cells with a variety of other accelerated life testing experiments. Coin-cell experiments using both full-cell and symmetric-cell configurations were used to study the microstructural changes and electrochemical behavior of both NMC and graphite electrodes, with the small format allowing for destructive characterization of many test replicates throughout cell lifetime; these experiments can be conducted more quickly than their large-format counterparts, and enable more detailed understanding of the degradation trajectory than the large-format test. However, difficulties in transferring electrochemical trends from the coin-cell format to the large-format cell will be discussed. In addition, cascading failure mechanisms observed in the large-format cells may not occur in coin-cells due to differences in the mechanical and thermal environment of each system. Implications for the design of small-format accelerated life testing using electrodes harvested from commercial batteries will be discussed. Calendar aging was accelerated by monitoring daily self-discharge and quantifying both reversible and irreversible capacity losses; challenges for making quantitative predictions from short-term calendar aging tests will be presented.

Cascading failure mechanism of major drainage system in mountainous city: Taking the basin of the main urban area of Chongqing as an example, China

Failure of major drainage systems is almost always accompanied by waterlogging. Understanding the operation and failure mechanism of major drainage systems is an important prerequisite for understanding and managing waterlogging. The natural and artificial environments in mountainous cities are more complex, and the major drainage system, as an open system for excessive surface runoff discharge and storage, is more prone to local overload and cascading failure. Existing theories and methods are difficult to explain and analyze the cascading failure characteristics and principles of major drainage systems in mountainous cities. Based on the complex network technology and the principle of runoff balance, the cascade failure model of major drainage system was constructed, and the characteristics and laws of cascade failure under six kinds of terrain, six kinds of short duration rainstorm and two kinds of surface environments were quantitatively analyzed. Research has found that the cascading failure of major drainage systems and waterlogging in mountainous cities should be the same phenomenon from different perspectives, and the simulated matching degree between the two can reach 79.5%. Meanwhile, 456 potential waterlogging locations were discovered in the study area, which is much larger than the actual 73 locations. When urban construction and rainfall conditions change, these unstable potential waterlogging locations are easily apparent. Among them, terrain is the main factor restricting the cascading failure of major drainage systems. Low lying valley areas often quickly accumulate a large amount of overflow, while flat areas are prone to overflow spreading to the surrounding areas; Slope areas are not prone to overflow, but are prone to local flooding. The change of short duration rainstorm and the difference of surface environmental openness will further interfere with the cascade failure of the major drainage system. The longer the return period of the short duration rainstorm or the increase of the peak value of the rainfall pattern, the greater the discharge and storage pressure of the major drainage system per unit time, resulting in intensified waterlogging. The open and unobstructed surface environment will lead to the small-scale spread of waterlogging, but this will significantly reduce the overall degree of waterlogging in the late rainstorm. The study revealed the spatiotemporal principles and basic laws of cascading failure of major drainage systems in mountainous cities. The conclusion is helpful for mountainous cities to formulate urban construction management strategies and climate change adaptation strategies, and to cope with current and future potential waterlogging disasters.

Mission Reliability Modeling of Multistation Manufacturing Systems Considering Cascading Functional Failure

The core function of the manufacturing system is to output high-quality products at a stable production rhythm. However, there are complex interactions between physical and functional failures of machines in the station. Functional failures can be propagated to other stations through material flow, resulting in the increasing risk of system performance degradation, which deserves further study. Therefore, in this article, a mission reliability modeling method considering the cascading functional failure of multistation manufacturing systems is presented. First, from the perspective of functional output, the cascading failure mechanism of a manufacturing system is discussed, and the connotation of functional failure and mission reliability is proposed. Second, the interaction model between machine performance and product quality is established to analyze the production rhythm considering the imperfect inspection. Third, the cascading functional failure model is constructed based on the mechanism of failure propagation. The integrated mission reliability modeling method of a multistation manufacturing system is proposed. Finally, a case study of a ferrite phase-shifting unit manufacturing system is conducted to illustrate the effectiveness and advancement of the proposed method.

Exploring the impacts of major events on the systemic risk of the international energy market

This study examines the systemic risk caused by major events in the international energy market (IEM) and proposes a management strategy to mitigate it. Using the tail-event driven network (TENET) method, this study constructed a tail-risk spillover network (TRSN) of IEM and simulated the dynamic spillover tail-risk process through the cascading failure mechanism. The study found that renewable energy markets contributed more to systemic risk during the Paris Agreement and the COVID-19 pandemic, while fossil energy markets played a larger role during the Russia-Ukraine conflict. This study identifies systemically important markets (SM) and critical tail-risk spillover paths as potential sources of systemic risk. The research confirms that cutting off the IEM risk spillover path can greatly reduce systemic risk and the influence of SM. This study offers insights into the management of systemic risk in IEM and provides policy recommendations to reduce the impact of shock events.

Modeling two-stage failure mechanism of cascading in cyber-physical power systems

Interdependency in cyber-physical power systems enables efficient monitor and control, but also brings out many threats, leading to catastrophic blackouts. To address this problem, the propagation mechanism of cascading failure in systems is analyzed. In this paper, we propose the partial random coupling systems model, and detail the interactive mechanism between physical power grid and communication network. Then, the modified failure mechanism is present, including two-stage redistribution types of traffic loads in physical power grid, and stochastic routing strategies in communication network. In simulation, the impact of attack scenes and topology structure on systems robustness is studied. Compared with random attack, high degree/betweenness attack results in first-order transition of cascading failure at a critical point, and causes more serious damage on systems. Besides, we have proved the positive correlation between clustering coefficient and robustness. To random attack, the systems consisted of double-star network behave more robust than systems consisted of mesh network, and also indicate the misproportion of increase between average dependent degree and systems robustness.

Evaluating the resilience of cyber–physical​ power systems by weighted spectral analysis

With the development of the Internet of Things, the interdependency between the physical system and the cyber system becomes intense and improves operational efficiency. But the interdependency also increases the risk of failure propagation. The resilience of the cyber–physical system is important for security facing extreme events. Based on complex network theory, a weighted multiplex network model is proposed to realize the unified modeling of the power system and communication system. In addition, the cascading failure mechanism in the cyber–physical power system is built based on power dispatch and information transmission mechanisms in the actual scenario. Then, spectral metrics are introduced to evaluate structural resilience from a global perspective. Finally, simulations of cascading failure are performed to verify the effectiveness of spectral metrics on resilience evaluation. The proposed model and metrics provide a convenient approach to quantifying the resilience of an interdependent system. The results of resilience evaluation can be used as a reference for system structure planning.

Sequential recovery of cyber-physical power systems based on improved Q-learning

Cascading failures are one of the most severe threats to cyber-physical power systems. Most studies explore the cascading failure problem from the attacker’s perspective while recovering the system from cascading failures is still lacking. This paper proposes a sequential recovery analysis process built within the framework of the cascading failure model, which considers the coupling mechanism of cyber-physical power systems and cascading failures. Then the improved Q-learning based on candidate room and dynamic factor idea of simulated annealing is employed to achieve faster and more efficient identification of optimal recovery sequence for failed lines under resource-limited conditions. Finally, the load recovery performance of four recovery strategies in the single-layer and double-layer systems are compared. The simulation results prove the effectiveness of the proposed sequential recovery process and the recovery strategy based on improved Q-learning.

Reliability Evaluation of Cyber–Physical Power Systems Considering Supply- and Demand-Side Uncertainties

To reach effective monitoring and control, a physical power grid couples with a communication network and evolves into cyber–physical power systems (CPPS), but this cyber–physical interdependence may exacerbate failure on the physical/cyber side and may turn into a cascading failure. Furthermore, distributed generators (DGs) and plug-in hybrid electric vehicles (PHEVs) introduced into CPPS add uncertainties to both the supply side and demand side of power energy. In this paper, we detail the model of CPPS and its coupling mechanism in operation and discuss the propagation mechanism of cascading failure within and across a physical power grid and a communication network. For uncertainties of power energy in the supply and demand sides, the generation and load of each day are divided into 24 time segments for modeling. In the case study, the well-being criteria and reliability indexes are employed to analyze the effect of DGs and cyber–physical interdependence on the reliability of CPPS when DGs suffer aging failure and cyber attacks, and the simulations indicate that introducing DGs can effectively enhance the period of healthy and marginal states. Furthermore, cyber attacks can sharply destroy the CPPS compared with aging failure.

IKN-CF: An Approach to Identify Key Nodes in Inter-Domain Routing Systems Based on Cascading Failures.

Inter-domain routing systems is an important complex network in the Internet. Research on the vulnerability of inter-domain routing network nodes is of great support to the stable operation of the Internet. For the problem of node vulnerability, we proposed a method for identifying key nodes in inter-domain routing systems based on cascading failures (IKN-CF). Firstly, we analyzed the topology of inter-domain routing network and proposed an optimal valid path discovery algorithm considering business relationships. Then, the reason and propagation mechanism of cascading failure in the inter-domain routing network were analyzed, and we proposed two cascading indicators, which can approximate the impact of node failure on the network. After that, we established a key node identification model based on improved entropy weight TOPSIS (EWT), and the key node sequence in the network can be obtained through EWT calculation. We compared the existing three methods in two real inter-domain routing networks. The results indicate that the ranking results of IKN-CF are high accuracy, strong stability, and wide applicability. The accuracy of the top 100 nodes of the ranking result can reach 83.6%, which is at least 12.8% higher than the average accuracy of the existing three methods.

The Vulnerability of the Power Grid Structure: A System Analysis Based on Complex Network Theory.

The safety and reliability of the power grid are related to national power security, economic development and people’s daily life. The occurrence of extreme weather changes the external environment greatly. Including generators and transmission lines, many power grid units cannot resist such a huge attack and get damaged easily, which forces units to quit from the power grid running system for a while. Furthermore, if the number of influenced units is high enough, the whole power system will be destroyed by cascading failure caused by extreme weather. Aiming at dealing with the cascading failure emergencies, this paper is trying to improve the traditional power structural vulnerability model so that it can be used to discuss extreme weather and propose a theoretical topological model to help scholars measure the damage caused by extreme cases. Based on previous research in this field, this paper utilizes complex network knowledge to build the power grid topology model. Then, considering extreme cases and the three attack modes simulation process, this paper makes use of the characteristic parameters of the power grid topology model and designs an algorithm, according to the realistic situation of the propagation mechanism of cascading failure of the power grid model as well as extreme weather research. Finally, taking IEEE-30 and IEEE-118 node bus system as examples, which shows that the structural vulnerability method proposed in this paper can properly address the mechanism of unbalanced load of cascading failure of power grid units under extreme conditions and can provide theoretical reference for preventing and reducing the impact of extreme cases on power grid which improves the reliability of the power grid.

Searching for Critical Power System Cascading Failures With Graph Convolutional Network

Power system cascading failures become more time variant and complex because of the increasing network interconnection and higher renewable energy penetration. High computational cost is the main obstacle for a more frequent online cascading failure search, which is essential to improve system security. We propose a more efficient search framework with the aid of a graph convolutional network (GCN) to identify as many critical cascading failures as possible with limited attempts. The complex mechanism of cascading failures can be well captured by training a GCN offline. Subsequently, the search for critical cascading failures can be significantly accelerated with the aid of the trained GCN model. We further enable the interpretability of the GCN model by a layerwise relevance propagation algorithm. The proposed method is tested on both the IEEE RTS-79 test system and China's Henan Province power system. The results show that the GCN-guided method can not only accelerate the search of critical cascading failures, but also reveal the reasons for predicting the potential cascading failures.

Network isolators inhibit failure spreading in complex networks

In our daily lives, we rely on the proper functioning of supply networks, from power grids to water transmission systems. A single failure in these critical infrastructures can lead to a complete collapse through a cascading failure mechanism. Counteracting strategies are thus heavily sought after. In this article, we introduce a general framework to analyse the spreading of failures in complex networks and demostrate that not only decreasing but also increasing the connectivity of the network can be an effective method to contain damages. We rigorously prove the existence of certain subgraphs, called network isolators, that can completely inhibit any failure spreading, and we show how to create such isolators in synthetic and real-world networks. The addition of selected links can thus prevent large scale outages as demonstrated for power transmission grids.

Simulation-based vulnerability assessment in transit systems with cascade failures

The urban transit system is vulnerable to various types of hazards and failures, where the failure of a system component may lead to a redistribution of the pressure and result in cascade failures. It is of great significance to develop an efficient approach to model and assess the system vulnerability for achieving a sustainable transit system. This research develops a novel holistic approach to assess the vulnerability of the urban transit system toward sustainable development. The cascading failure mechanism is incorporated in the established complex network to simulate the process in a dependent system, where the failure of one or a few system components can trigger the failure of other components. Several attack strategies (i.e., static and dynamic intentional attack and random attack strategies) are used to test the system vulnerability, and the impacts of the tolerance parameter and passenger transfer rate on the loss of transport capacity are explored. A complex network consisting of 198 nodes and 415 edges is constructed to model the urban transit system with cascade failures. A realistic urban transit system in China is used as a case to testify the applicability and effectiveness of the developed approach. Results indicate that: (1) The interchange stations display high vulnerability in the network and Xianggang Rd station, Hongtu Boulevard station, Taipingyang station, and Zhongnan Rd are the most vulnerable stations, which should be paid more attention in the operation management; (2) The damage of the attacks in the intentional attack strategies are much more significant than that in the random attack, indicating that the proposed approach presents the ability to identify the important nodes; (3) The metric of node betweenness would be more efficient to identify the vulnerable nodes in the intentional attack; (4) The optimal value of the tolerance parameter is the range [0.8, 0.9], while keeping the passenger transfer rate in the range [0.3, 0.4] can effectively reduce the effect of cascade failures with minimum resources. The developed approach can be used as a decision tool to not only assess the vulnerability in the existing transit system but also optimize the planning of the new transit system.

Sequential Recovery of Complex Networks Suffering From Cascading Failure Blackouts

Over the past decades, prevention and mitigation against cascading failure blackouts in complex networked systems have been extensively studied. In reality, the functional and structural restoration of complex networks suffering from large-scale cascading failures may involve a sequence of repairing actions. In this paper, we propose a novel sequential recovery model that takes into consideration both the operating mechanism of complex power transmission networks and potential cascading failures triggered during the recovery process. From a complex network perspective, we introduce a new tool called the sequential recovery graph (SRG) to identify the critical nodes and the order of their restorations which lead to better performance in the recovery process. We further develop a practical sequential recovery strategy based on SRG. We perform simulations on three benchmark power grids and five baseline methods for performance comparison. Simulation results and complexity analysis demonstrate the effectiveness and low computational complexity of the proposed SRG-based strategy.

Prevention and Mitigation of Catastrophic Failures in Demand-Supply Interdependent Networks

We propose a generic system model for a special category of interdependent networks, demand-supply networks, in which the demand and the supply nodes are associated with heterogeneous loads and resources, respectively. Our model sheds a light on a unique cascading failure mechanism induced by resource/load fluctuations, which in turn opens the door to conducting stress analysis on interdependent networks. Compared to the existing literature mainly concerned with the node connectivity, we focus on developing effective resource allocation methods to prevent these cascading failures from happening and to mitigate/confine them upon occurrence in the network. To prevent cascading failures, we identify some dangerous stress mechanisms, based on which we quantify the robustness of the network in terms of the resource configuration scheme. Afterward, we identify the optimal resource configuration under two resource/load fluctuations scenarios: uniform and proportional fluctuations. We further investigate the optimal resource configuration problem considering heterogeneous resource sharing costs among the nodes. To mitigate/confine ongoing cascading failures, we propose two network adaptations mechanisms: intentional failure and resource re-adjustment, based on which we propose an algorithm to mitigate an ongoing cascading failure while reinforcing the surviving network with a high robustness to avoid further failures.

Cascading Failure Modeling for Circuit Systems Using Impedance Networks: A Current-Flow Redistribution Approach

The collapse of circuits is usually a cascading failure rather than a simple failure event. It is usually difficult to model this kind of failure due to the complex structural and functional coupling. In this article, the impedance network is introduced as a prototypical model for characterizing the cascading failure of the circuit. A current-flow redistribution approach is proposed to analyze the cascading failure mechanisms of the circuits. Specific current-flow redistribution factors for two typical failure modes, i.e., the open circuit and short circuit, are put forward to determine the effect of the failed component on the remaining components. A health confidence value is further introduced to assess the health status of the impedance network. Then, a simulation framework for cascading failure propagation is proposed to capture the dynamic failure process. Finally, an example is presented to show the cascading failure behavior. The proposed model is also validated by comparing the obtained results with those of the SPICE software simulation.

Study on Cascading Failures of Power Grid Information Physics Fusion System Based on Pattern Search

In a complex power grid, cascading failures that are triggered by some small disturbances can induce global catastrophic effects over the entire network. Based on the discussion of occurrence mechanism of power grid information physics fusion system cascading failures, this paper proposes an improved fault pattern search method. Compared with traditional search method, this method helps to improve the chain reaction set that causes the system failure, and makes it possible to make a comprehensive forecast search for grid link failures.