Mitigation Of Cascading Failures Research Articles

Aperiodic small signal stability method for detection and mitigation of cascading failures in smart grids

The occurrence of cascading failures poses significant risks to the stability and reliability of modern smart grids. This article presents a novel hybrid algorithm designed to assess and mitigate these failures. The technique combines advanced clustering algorithms, specifically Affinity Propagation Graph (APG) and Self-Propagating Graph (SPG), to detect critical nodes, and Unified Power Flow Controllers (UPFCs) to provide compensation to grid networks. The algorithm first uses APG to divide the network into clusters and considers the center bus as the critical node. If the center bus is not critical, SPG is applied to identify the critical node. This hybrid approach identifies the critical node in just 0.02 s (for both APG and SPG) and with improved accuracy compared to existing methods. After identifying critical nodes, UPFCs are strategically installed to regulate power flow and reduce the probability of cascading failures, with compensation taking approximately 0.14 s. Simulation results demonstrate the effectiveness of the proposed method in enhancing grid resilience and reducing the likelihood of cascading failures. By strategically deploying UPFCs at critical nodes, this approach ensures resilient grid operation in various scenarios. This research significantly contributes to the development of smart grid technologies by providing a comprehensive framework to address cascading failures in power distribution networks. The proposed method shows potential for improving the reliability and stability of power grids amid changing system dynamics and uncertainties.

Static and Dynamic Load-Triggered Cascading Failure Mitigation for Storage Area Networks

Static and Dynamic Load-Triggered Cascading Failure Mitigation for Storage Area Networks

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.

Mitigation strategy of cascading failures in urban traffic congestion based on complex networks

Urban road traffic network is becoming increasingly complex. The increasing travel demand has exceeded facility supply of transportation system. Thus, a scientific way of transportation can solve the problem of traffic congestion. If some central intersections are congested, the road network could easily lose its travel efficiency and further lead to cascading failure. In this regard, from the viewpoint of complex networks, this paper provides a cascading failure mitigation strategy for the urban road traffic network. A load redistribution strategy is represented which can redistribute congestion load reasonably. Random and intentional failures are simulated with MATLAB on Barabási and Albert (BA) scale-free network. The indices related to complex network of different methods are compared on BA network and part of the real road network in Baoding City. The load redistribution strategy in this paper is implemented combined with user equilibrium assignment, then the travel time related to urban road network is compared with another method on the Sioux Falls network. The simulation results suggest that when the capacity parameter reaches the threshold, further increase has little effect on the mitigation time. Comparisons of other mitigation approaches verify the effectiveness of our approach in lessening cascading failure caused by traffic congestion. The increase in total network travel time and additional delay by reason of load redistribution is acceptable.

A risk‐based multi‐step corrective control method for mitigation of cascading failures

Minimizing the risk of cascading failures in a power system is vital to balance the operational economy and security. A multi-step corrective control (MSCC) method is proposed to mitigate cascading effects in terms of reducing risk of blackout by considering the multi-step propagation characteristics of cascading failures caused by overload. Based on fault chain model and the DC power flow equation, the dynamic interaction between the process of cascading failures and control schemes is first discussed. The corrective control problem is then expressed as a multi-step decision-making optimisation problem based on the defined risk indices. The MSCC model with flexibility of control timing is designed by optimizing probability weighting expected cost and overload risk of cascading failure. In this control method, generation re-scheduling and load shedding are selected as the main remedial actions, and a multi-layer coding genetic algorithm is employed to obtain the optimal remedial control schemes. The numerical results indicate that control schemes generated by the proposed method could mitigate the cascading failures and result in better performance than non-recurring corrective control (NCC) in terms of economy and operational risk.

Performance analysis of safety instrumented systems against cascading failures during prolonged demands

Cascading failures may occur in many technical systems where the failure of one component triggers successive events. Safety barriers like safety instrumented systems are installed in many industries to prevent failures and failure propagations. However, little attention has been paid to the impacts of safety instrumented systems employed to prevent cascading failures in the literature. This paper proposes a novel method for analyzing how the performance of safety instrumented systems influences the protection against and mitigation of cascading failures. It considers SIS reliability and SIS durability in the mitigation of cascading failures. The method uses recursive aggregations based on the reliability block diagram and is verified with Monte Carlo simulations. The application is illustrated with a practical case study, where the proposed method is found beneficial to identify the criticality of safety instrumented systems in consideration of their locations and performance.

Mitigation of cascading failures in complex networks

Cascading failures in many systems such as infrastructures or financial networks can lead to catastrophic system collapse. We develop here an intuitive, powerful and simple-to-implement approach for mitigation of cascading failures on complex networks based on local network structure. We offer an algorithm to select critical nodes, the protection of which ensures better survival of the network. We demonstrate the strength of our approach compared to various standard mitigation techniques. We show the efficacy of our method on various network structures and failure mechanisms, and finally demonstrate its merit on an example of a real network of financial holdings.

Reliability and barrier assessment of series–parallel systems subject to cascading failures

Cascading failures can occur in many technical systems where the components are organized as in series–parallel structures. The failures in these systems may propagate from one component to the other, not only within the same parallel sub-structure but also between different sub-structures. This article presents a recursive aggregation method based on the extended models of reliability block diagram, for analyzing the impacts of cascading failures on the reliability of series–parallel systems. Based on the reliability analysis, the effects of safety barriers on preventing cascading failures are studied, and the importance of safety barriers at different locations is evaluated. One simple example of three components and one practical case from an oil production system are presented. The findings in these case studies illustrate how system designers and safety managers can identify the effective and reasonable ways of installing safety barriers by using the proposed approaches, for the mitigation of cascading failures in series–parallel technical systems.

Community-Based Link-Addition Strategies for Mitigating Cascading Failures in Modern Power Systems

The propagation of cascading failures of modern power systems is mainly constrained by the network topology and system parameter. In order to alleviate the cascading failure impacts, it is necessary to adjust the original network topology considering the geographical factors, construction costs and requirements of engineering practice. Based on the complex network theory, the power system is modeled as a directed graph. The graph is divided into communities based on the Fast–Newman algorithm, where each community contains at least one generator node. Combined with the islanding characteristics and the node vulnerability, three low-degree-node-based link-addition strategies are proposed to optimize the original topology. A new evaluation index combining with the attack difficulty and the island ratio is proposed to measure the impacts on the network under sequential attacks. From the analysis of the experimental results of three attack scenarios, this study adopts the proposed strategies to enhance the network connectivity and improve the robustness to some extent. It is therefore helpful to guide the power system cascading failure mitigation strategies and network optimization planning.

Over-Voltage Suppression Methods for the MMC-VSC-HVDC Wind Farm Integration System

In this brief, we study the cascading failure mitigation methods in the system where the remote large-scale wind farm is integrated to the bulk ac power system through high-voltage direct current (HVDC) transmission based on voltage source converter (VSC) in modular multilevel converter (MMC) topology. We first analyze the over-voltage formation mechanism in the MMC-VSC-HVDC wind farm integration system after the short-circuit fault of an ac feed line, and find that the saturation of the integers in the PI controller are the main causes. Based on the analytical conclusions derived, we propose two improvement control strategies implemented in the MMC controller to suppress the over-voltage. We do simulations on a test case with PSCAD. Simulation results verify the efficacy of the proposed methods in the suppression of over-voltage as well as the prevention of cascading failure in power systems.

Robustness analysis of complex networks with power decentralization strategy via flow-sensitive centrality against cascading failures

Most existing cascading failure mitigation strategy of power grids based on complex network ignores the impact of electrical characteristics on dynamic performance. In this paper, the robustness of the power grid under a power decentralization strategy is analysed through cascading failure simulation based on AC flow theory. The flow-sensitive (FS) centrality is introduced by integrating topological features and electrical properties to help determine the siting of the generation nodes. The simulation results of the IEEE-bus systems show that the flow-sensitive centrality method is a more stable and accurate approach and can enhance the robustness of the network remarkably. Through the study of the optimal flow-sensitive centrality selection for different networks, we find that the robustness of the network with obvious small-world effect depends more on contribution of the generation nodes detected by community structure, otherwise, contribution of the generation nodes with important influence on power flow is more critical. In addition, community structure plays a significant role in balancing the power flow distribution and further slowing the propagation of failures. These results are useful in power grid planning and cascading failure prevention.

Realistic control of network dynamics

The control of complex networks is of paramount importance in areas as diverse as ecosystem management, emergency response and cell reprogramming. A fundamental property of networks is that perturbations to one node can affect other nodes, potentially causing the entire system to change behaviour or fail. Here we show that it is possible to exploit the same principle to control network behaviour. Our approach accounts for the nonlinear dynamics inherent to real systems, and allows bringing the system to a desired target state even when this state is not directly accessible due to constraints that limit the allowed interventions. Applications show that this framework permits reprogramming a network to a desired task, as well as rescuing networks from the brink of failure-which we illustrate through the mitigation of cascading failures in a power-grid network and the identification of potential drug targets in a signalling network of human cancer.

Mitigation strategies on scale-free networks against cascading failures

According to the dynamic characteristics of the cascading propagation, we introduce a mitigation mechanism and propose four mitigation methods on four types of nodes. By the normalized average avalanche size and a new measure, we demonstrate the efficiencies of the mitigation strategies on enhancing the robustness of scale-free networks against cascading failures and give the order of the effectiveness of the mitigation strategies. Surprisingly, we find that only adopting once mitigation mechanism on a small part of the overload nodes can dramatically improve the robustness of scale-free networks. In addition, we also show by numerical simulations that the optimal mitigation method strongly depends on the total capacities of all nodes in a network and the distribution of the load in the cascading model. Therefore, according to the protection strength for scale-free networks, by the distribution of the load and the protection price of networks, we can reasonably select how many nodes and which mitigation method to efficiently protect scale-free networks at the lower price. These findings may be very useful for avoiding various cascading-failure-induced disasters in the real world and for leading to insights into the mitigation of cascading failures.

Robustness of complex networks with the local protection strategy against cascading failures

Considering the role of the neighboring nodes of an overload node, we articulate a local protection strategy to address the problem of the optimal defense in the cascading propagation. From two aspects of the global robustness and the different attacks, we numerically demonstrate the effectiveness of this strategy on Barabási–Albert (BA) scale-free networks and the power grid, and show that the robustness of diverse networks against cascading failures can be improved dramatically. And we numerically find the optimal value of the parameter, at which two types of networks can reach the strongest robust level against cascading failures. Next, in BA networks we verify this finding by theoretical analysis. Our results may be very useful for constructing the optimal protection strategy in realistic networks and for leading to insights into the mitigation of cascading failures.

Mitigation of cascading failures on complex networks

To prevent or mitigate the cascading propagation on complex networks more efficiently, taking into account some existing protections and measures in real-life networks, we introduce a new mitigation strategy. Applying the global removal and two attacking strategies, we demonstrate the efficiency of the mitigation method on improving the robustness level against cascading failures in Barabasi–Albert (BA) scale-free networks and in the Internet, as well as in the power grid of the western United States. We show that only making simple adjustments to the overload edges can dramatically enhance the robustness of diverse networks subject to the global removal and targeted attacks. We further compare the mitigation strategy in two attacks and observe to what extent the improvement of the robustness in two attacks depends on the parameters in our cascading model. In addition, by the times that an edge overloads in the cascading propagation, we discuss how to protect the edges with the different load. Our results are useful not only for improving significantly the robustness of complex networks but also for further studying on the control and defense of cascading failures.

Reciprocally altruistic agents for the mitigation of cascading failures in power grids

Cascading failures in electrical power networks often come with disastrous consequences. A variety of schemes for mitigating cascading failures exist, but the vast majority depend upon centralised control architectures. Centralised designs are frequently more susceptible to communications latency and bandwidth limitations and can be vulnerable to random failures and directed attacks. This paper proposes a decentralised approach. We place control agents at each substation in a power network, each of which uses decentralised Model Predictive Control (MPC) to select emergency control actions. When making decisions, the control agents consider not only their own goals, but also the goals of nearby agents. Thus the agents act with Reciprocal Altruism (RA). Results from simulations of extreme cascading failures within the IEEE 300 bus test network indicate that this approach can dramatically reduce the average size and social cost of large cascading failures. Simulations also show that the bandwidth required for message passing is well within the limits of current technology.