Bulk power risk analysis: Ranking infrastructure elements according to their risk significance

Koonce, Anthony; Apostolakis, G.; Cook, Benjamin K.

doi:10.1016/j.ijepes.2007.06.013

Cited by 49 publications

(20 citation statements)

References 17 publications

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“…An alternative, complementary opportunity which is receiving increased attention is that of condition-based maintenance strategies founded on the concepts of monitoring, fault diagnostics and prognostics (Figure 3) (Jarrell et al, 2004;Korbicz et al, 2004). As in Medicine, a clinical picture and diagnosis can be made with the values of some measured parameters related to the health condition of a human being, in any kind of equipment it is also possible to have an idea about its functional condition from the knowledge of the evolution of its significant parameters.…”

Section: Maintenancementioning

confidence: 99%

Reliability engineering: Old problems and new challenges

Zio

2009

Reliability Engineering & System Safety

702

355

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Section: Maintenancementioning

confidence: 99%

Reliability engineering: Old problems and new challenges

Zio

2009

Reliability Engineering & System Safety

702

355

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“…Also, they have presented a scenario-based methodology for ranking the elements of a water supply infrastructure according to their value to the owner. Koonce et al [16] have proposed a methodology for ranking the elements in the bulk power grid based on random failures and malevolent acts. Since interactions between critical infrastructures are, in many respects, similar to human-human interactions, Chai et al [5] have applied social network analysis to study characteristics of infrastructures and have identified oil and gas, information and communications technologies, and electricity as three critical infrastructures that have the greatest potential to produce cascading infrastructure failures.…”

Section: Critical Infrastructure Protection Prioritizationmentioning

confidence: 99%

A quantitative approach for assessing the critical nodal and linear elements of a railway infrastructure

Zhang

2015

International Journal of Critical Infrastructure Protection

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“…Among these models, there are several studies considering MCDM/A approaches (Akgun et al 2010;Sri Bhashyam and Montibeller 2012;Koonce et al 2008;Patterson and Apostolakis 2007).…”

Section: Risk Analysis On Counter-terrorismmentioning

confidence: 99%

Multidimensional Risk Analysis

Almeida

Cavalcante

Alencar

et al. 2015

International Series in Operations Research &Amp; Management Science

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Accidents involve critical consequences that require an appropriate and efficient form of risk management. A multidimensional risk analysis allows a broader view. MCDM/A approaches enable more consistent decision-making, taking into account the DM's rationality (compensatory or non-compensatory), DM's behavior regarding risk (prone, neutral or averse) and the uncertainties inherent in the risk context. This chapter presents numerical applications illustrating the use of multicriteria models in two different contexts: a natural gas pipeline and an underground electricity distribution system. Two different MCDM/A approaches are considered: MAUT (Multiattribute Utility Theory) and the ELECTRE TRI outranking method. In the numerical applications, MCDM/A approach steps for building decision models are presented: identifying hazard scenarios, estimating the set of payoffs, eliciting the MAU function (Multi-attribute Utility function), computing the probability function of consequences and estimating multidimensional risk. Loss functions are introduced in the models to calculate the probability distribution functions over the multiple criteria such as impact on humans, and environmental and financial losses. Therefore, Decision Theory concepts are applied to estimate risk in industrial plants and modes of transportation. Finally, other decision problems related to multidimensional risk analysis, using MCDM/A, are considered in different contexts, such as: power electricity systems, natural hazards, risk analysis on counter-terrorism, nuclear power plant. Justifying the Use of the Multidimensional RiskThe perceived level of risk is directly linked to the perceived intensity of consequences to people and society as well as to issues related to the level of probability. These consequences are multidimensional and are associated to the objectives, represented by criteria and can be approached with an MCDM/A or a multiobjective method (see Chap. 2). Many studies show that using a single dimension of risk may not be realistic (Morgan et al.

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Bulk power risk analysis: Ranking infrastructure elements according to their risk significance

Cited by 49 publications

References 17 publications

Reliability engineering: Old problems and new challenges

Reliability engineering: Old problems and new challenges

A quantitative approach for assessing the critical nodal and linear elements of a railway infrastructure

Multidimensional Risk Analysis

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