The sensitivity of electric power infrastructure resilience to the spatial distribution of disaster impacts

Rachunok, Benjamin; Nateghi, Roshanak

doi:10.1016/j.ress.2019.106658

Cited by 34 publications

(12 citation statements)

References 49 publications

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“…For a small service area, the same failure probability of each component is considered when the distribution system suffers from natural disasters [131]. In the case of larger areas, it becomes very important to consider the spatial distribution of an event, in order to better estimate the hazard impact and recovery duration [105]. This can be achieved by defining multiple impact zones and use of failure probability or N-k contingency constraint [123,132].…”

Section: Spatial Scalementioning

confidence: 99%

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Resilience Quantification of Smart Distribution Networks—A Bird’s Eye View Perspective

et al. 2021

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The introduction of pervasive telecommunication devices, in the scope of smart grids (SGs), has accentuated interest in the distribution network, which integrates a huge portion of new grid applications. High impact low probability (HILP) events, such as natural hazards, manmade errors, and cyber-attacks, as well as the inherent fragility of the distribution grid have propelled the development of effective resilience tools and methods for the power distribution network (PDN) to avoid catastrophic infrastructural and economical losses. Multiple resilience evaluation frameworks are proposed in the literature in order to assist distribution system operators (DSOs) in managing their networks when faced with exogenous threats. We conduct detailed analysis of existing quantitative resilience studies in both electric and telecommunication domains of a PDN, focusing on event type, metrics, temporal phases, uncertainty, and critical load. Our work adopts the standpoint of a DSO, whose target is to identify feasible resilience assessment frameworks, which apply to pre-defined requirements in terms of resilience evaluation objectives (planning, reactive response, or simple assessment), time of evaluation, and available enhancement strategies. Finally, results and observations on selected works are presented, followed by discussion of identified challenges and opportunities.

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Section: Spatial Scalementioning

confidence: 99%

“…Examples include percolation theory and complex networks [92], graph theory analysis [21,105], power flow [14,41], agent-based information traffic flow [106], and many simulation software that emulate network behavior [82,96].…”

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confidence: 99%

Resilience Quantification of Smart Distribution Networks—A Bird’s Eye View Perspective

et al. 2021

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“…This leads to resiliency analysis characterized by higher spatial resolution. In particular, the spatial resolution increment in large network disruption analysis is crucial to face adequately with HILP events as described by [18]. 2.…”

Section: Introductionmentioning

confidence: 99%

Enabling Methodologies for Predictive Power System Resilience Analysis in the Presence of Extreme Wind Gusts

Brugnetti

Coletta

et al. 2020

Energies

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Modern power system operation should comply with strictly reliability and security constraints, which aim at guarantee the correct system operation also in the presence of severe internal and external disturbances. Amongst the possible phenomena perturbing correct system operation, the predictive assessment of the impacts induced by extreme weather events has been considered as one of the most critical issues to address, since they can induce multiple, and large-scale system contingencies. In this context, the development of new computing paradigms for resilience analysis has been recognized as a very promising research direction. To address this issue, this paper proposes two methodologies, which are based on Time Varying Markov Chain and Dynamic Bayesian Network, for assessing the system resilience against extreme wind gusts. The main difference between the proposed methodologies and the traditional solution techniques is the improved capability in modelling the occurrence of multiple component faults and repairing, which cannot be neglected in the presence of extreme events, as experienced worldwide by several Transmission System Operators. Several cases studies and benchmark comparisons are presented and discussed in order to demonstrate the effectiveness of the proposed methods in the task of assessing the power system resilience in realistic operation scenarios.

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“…Experts point out that resilience is an intrinsic property which implies a process of detection, anticipation, learning, and adaptation [10]. They define and quantify it in terms of criticality, frequency, impact, and recovery.…”

Section: Introductionmentioning

confidence: 99%

Vulnerability and Resilience Assessment of Power Systems: From Deterioration to Recovery via a Topological Model based on Graph Theory

Beyza

Bravo²,

García-Paricio

et al. 2020

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)

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Traditionally, vulnerability is the level of degradation caused by failures or disturbances, and resilience is the ability to recover after a high-impact event. This paper presents a topological procedure based on graph theory to evaluate the vulnerability and resilience of power grids. A cascading failures model is developed by eliminating lines both deliberately and randomly, and four restoration strategies inspired by the network approach are proposed. In the two cases, the degradation and recovery of the electrical infrastructure are quantified through four centrality measures. Here, an index called flow-capacity is proposed to measure the level of network overload during the iterative processes. The developed sequential framework was tested on a graph of 600 nodes and 1196 edges built from the 400 kV high-voltage power system in Spain. The conclusions obtained show that the statistical graph indices measure different topological aspects of the network, so it is essential to combine the results to obtain a broader view of the structural behaviour of the infrastructure.

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The sensitivity of electric power infrastructure resilience to the spatial distribution of disaster impacts

Cited by 34 publications

References 49 publications

Resilience Quantification of Smart Distribution Networks—A Bird’s Eye View Perspective

Resilience Quantification of Smart Distribution Networks—A Bird’s Eye View Perspective

Enabling Methodologies for Predictive Power System Resilience Analysis in the Presence of Extreme Wind Gusts

Vulnerability and Resilience Assessment of Power Systems: From Deterioration to Recovery via a Topological Model based on Graph Theory

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