Identification of Cascading Failure Scenarios of Infrastructure Systems using Multi-Group Non-Dominant Sorting Algorithm

Power transmission networks are critical infrastructure systems of urban communities, but are prone to cascading failures due to their high level of interconnectivity. Therefore, it is of great interest to identify critical components of the network that may trigger cascading failures. However, existing approaches to identify critical cascading failures focus on topological effect for a limited number of initial component failures. Meanwhile, identification based on load flow analysis without a limit on the number of triggering component failures has not been extensively studied. In this study, we simulate the overload-induced cascading failures to find the most critical scenarios of initial failure events in a power grid. The proposed approach uses the multi-group non-dominant sorting algorithm (Choi and Song, 2017) with two objective functions, i.e. network impact measure, and the number of initial component failures. Numerical experiments on a 30-bus network demonstrate that the identified critical cascading scenarios, triggered by single and multiple component failures, may not share common components necessarily. The proposed approach is expected to identify a group of critical components, which may be neglected by existing approaches.The research was supported by the National Research Foundation of Korea (NRF) Grant (No. 2018M2A8A4052), funded by the Korean Government (MSIP)

Optimizing protections against cascades in network systems: A modified binary differential evolution algorithm

International audienceThis paper addresses the optimization of protection strategies in critical infrastructures within a complex network systems perspective. The focus is on cascading failures triggered by the intentional removal of a single network component. Three different protection strategies are proposed that minimize the consequences of cascading failures on the entire system, on predetermined areas or on both scales of protective intervention in a multi-objective optimization framework. We optimize the three protection strategies by devising a modified binary differential evolution scheme that overcomes the combinatorial complexity of this optimization problem. We exemplify our methodology with reference to the topology of an electricity infrastructure, i.e. the 380 kV Italian power transmission network. We only focus on the structure of this network as a test case for the suggested protection strategies, with no further reference on its physical and electrical properties

Quantitative maritime security assessment: a 2020 vision

Maritime security assessment is moving towards a proactive risk-based regime. This opens the way for security analysts and managers to explore and exploit flexible and advanced risk modelling and decision-making approaches in maritime transport. In this article, following a review of maritime security risk assessment, a generic quantitative security assessment methodology is developed. Novel mathematical models for security risk analysis and management are outlined and integrated to demonstrate their use in the developed framework. Such approaches may be used to facilitate security risk modelling and decision making in situations where conventional quantitative risk analysis techniques cannot be appropriately applied. Finally, recommendations on further exploitation of advances in risk and uncertainty modelling technology are suggested with respect to maritime security risk quantification and management

Analysis of vulnerabilities in maritime supply chains

This paper aims to analyze the different concepts of “vulnerability” used in maritime supply chains, and to develop a novel framework with supporting models to identify and analyze the relevant vulnerabilities in the chains. A real case of the Maersk shipping line in its Asia-Europe route is studied to demonstrate the applicability of the proposed framework. We find that the investigated network has stronger robustness against random failures than that when facing deliberate attacks. Furthermore, to identify vulnerable nodes (i.e. ports) of the network, two different types of analysis are undertaken through a multi-centrality model and a robustness analysis model, respectively. Consequently, the vulnerabilities estimated through robustness analysis can ascertain those by the classical centrality methods when they appear on both analysis results. More importantly, the similarity between the two outcomes can help gain more confidence on the accuracy in terms of the identification of the vulnerabilities in the system, while the difference (if any) such as those identified by the robustness analysis but not by the centrality analysis (or vice versa) can trigger a further investigation to find the comprehensive vulnerable nodes against different threats/hazards. It will aid rational decision on design and operation of resilient and robust maritime supply chains. © 2017 Elsevier Lt

Identifying groups of critical edges in a realistic electrical network by multi-objective genetic algorithms

International audienceIn this paper, an analysis of the vulnerability of the Italian high-voltage (380 kV) electrical transmission network (HVIET) is carried out for the identification of the groups of links (or edges, or arcs) most critical considering the network structure and flow. Betweenness centrality and network connection efficiency variations are considered as measures of the importance of the network links. The search of the most critical ones is carried out within a multi-objective optimization problem aimed at the maximization of the importance of the groups and minimization of their dimension. The problem is solved using a genetic algorithm. The analysis is based only on information on the topology of the network and leads to the identification of the most important single component, couples of components, triplets and so forth. The comparison of the results obtained with those reported by previous analyses indicates that the proposed approach provides useful complementary information

Risk Assessment and Management of Petroleum Transportation Systems Operations

Petroleum Transportation Systems (PTSs) have a significant impact on the flow of crude oil within a Petroleum Supply Chain (PSC), due to the great demand on this natural product. Such systems are used for safe movement of crude and/or refined products from starting points (i.e. production sites or storage tanks), to their final destinations, via land or sea transportation. PTSs are vulnerable to several risks because they often operate in a dynamic environment. Due to this environment, many potential risks and uncertainties are involved. Not only having a direct effect on the product flow within PSC, PTSs accidents could also have severe consequences for the humans, businesses, and the environment. Therefore, safe operations of the key systems such as port, ship and pipeline, are vital for the success of PTSs. This research introduces an advanced approach to ensure safety of PTSs. This research proposes multiple network analysis, risk assessment, uncertainties treatment and decision making techniques for dealing with potential hazards and operational issues that are happening within the marine ports, ships, or pipeline transportation segments within one complete system. The main phases of the developed framework are formulated in six steps. In the first phase of the research, the hazards in PTSs operations that can lead to a crude oil spill are identified through conducting an extensive review of literature and experts’ knowledge. In the second phase, a Fuzzy Rule-Based Bayesian Reasoning (FRBBR) and Hugin software are applied in the new context of PTSs to assess and prioritise the local PTSs failures as one complete system. The third phase uses Analytic Hierarchy Process (AHP) in order to determine the weight of PTSs local factors. In the fourth phase, network analysis approach is used to measure the importance of petroleum ports, ships and pipelines systems globally within Petroleum Transportation Networks (PTNs). This approach can help decision makers to measure and detect the critical nodes (ports and transportation routes) within PTNs. The fifth phase uses an Evidential Reasoning (ER) approach and Intelligence Decision System (IDS) software, to assess hazards influencing on PTSs as one complete system. This research developed an advance risk-based framework applied ER approach due to its ability to combine the local/internal and global/external risk analysis results of the PTSs. To complete the cycle of this study, the best mitigating strategies are introduced and evaluated by incorporating VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and AHP to rank the risk control options. The novelty of this framework provides decision makers with realistic and flexible results to ensure efficient and safe operations for PTSs