Costing a Natural Disaster: An Accounting Perspective

Ciccotosto, Susan

doi:10.1016/b978-0-12-817465-4.00015-7

Cited by 1 publication

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Secondly, the wind-based FCs obtained from analytical techniques such as the ones in 42] for transmission systems and [11][12][13] for distribution systems provide answers to some of the previously questions but still pose the following concerns • The external factors, such as objects affecting the line, are very difficult to model and need further exploration. • The fatigue due to previous events of the same nature…”

Section: Factors Influencing the Fcsmentioning

confidence: 99%

“…On the other hand, helpful information regarding the severity of earthquakes can be found in [10]. The economic losses caused by this type of natural disaster are estimated to cost roughly $502 billion yearly [11]. As an example, an earthquake of 8.8 on the Richter scale hit the south-central area of Chile on February 27 th , 2010, at 03:34 AM.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Review and Comparison of the Fragility Curves Used for Resilience Assessments in Power Systems

Serrano-Fontova,

Li,

Liao

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Over the years, power systems have been severely affected by extreme events. This situation has worsened given that climate change has proven to exacerbate their frequency and magnitude. In this context, resilience assessments have proved crucial to prevent and tackle the effects of these events on power systems. Some resilience studies have taken advantage of the so-called fragility curves (FCs) to evaluate the vulnerability of the system components against these natural hazards. Conceptually, FCs provide the failure probability of a particular grid asset according to the intensity of an extreme event, which can be determined based on the hazard intensity inherently dictated by the nature of the event. The probability of failure can be obtained following diverse methodologies and criteria. Thus, the resilience assessment of the event may vary significantly depending on how the probability of failure was determined. This paper provides, for the first time, a comprehensive review of the FCs used to model the vulnerability of the power system components, classifying them according to the physical magnitude and the system element subject to each type of event. Furthermore, a comparison of results obtained applying different FCs is developed to show the relevance of their modelling. The content of this paper can be used as a hands-on guide for researchers and power systems engineers to perform resilience studies.

show abstract

Section: Factors Influencing the Fcsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%