Models for Seismic Vulnerability Analysis of Power Networks: Comparative Assessment

Cavalieri, Francesco; Franchin, Paolo; Cortés, Jessica A. M. Buriticá; Tesfamariam, Solomon

doi:10.1111/mice.12064

Cited by 60 publications

(32 citation statements)

References 51 publications

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“…Though underlying models of demand changes during recovery from a hazard have not yet been implemented, the proposed procedure can model variation of the baseline demand through a constant demand multiplier to adjust the base demand of every node. This step of the procedure generalizes the work of Cavalieri et al (2012), (2014), Franchin (2014) and Franchin and Cavalieri (2015) who studied the seismic vulnerability of buildings considering both the direct damage to buildings and the inhabitability (loss of functionality) due to loss of utility services.…”

Section: Assessing the Resilience Of Dependent Critical Infrastrucmentioning

confidence: 81%

Modeling the resilience of critical infrastructure: the role of network dependencies

Guidotti

Chmielewski

Unnikrishnan

et al. 2016

Sustainable and Resilient Infrastructure

196

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Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities’ well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure.

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Section: Assessing the Resilience Of Dependent Critical Infrastrucmentioning

confidence: 81%

Modeling the resilience of critical infrastructure: the role of network dependencies

Guidotti

Chmielewski

Unnikrishnan

et al. 2016

Sustainable and Resilient Infrastructure

196

View full text Add to dashboard Cite

show abstract

“…In the latter cases, wind-related trips might be rectified in a few hours; however, the restoration of an entire tower will take considerably longer. In this study, we only consider the collapse of an entire tower and model its resistance against hazard with a fragility curve [38]- [40], which expresses the failure probability of a tower as a function of wind speed. The shape of the curve depends on the strength of the tower and the variability of the different parameters that contribute to that strength.…”

Section: B Fragility Modeling Of Network Componentsmentioning

confidence: 99%

Integrated Approach to Assess the Resilience of Future Electricity Infrastructure Networks to Climate Hazards

Wilkinson

Dawson

et al. 2018

IEEE Systems Journal

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Abstract-Electricity systems are undergoing unprecedented change, with growing capacity for low-carbon generation, and an increasingly distributed approach to network control. Furthermore, the severity of climate related threats is projected to increase. To improve our understanding of the risks from these changes, this paper presents a novel modeling approach to assess the resilience of future electricity networks to climate hazards. The approach involves consideration of the: 1) evolution of electricity networks in response to changes in demand, supply, and infrastructure development policies; 2) implication that these policies have on network configuration and resilience; and 3) impacts of potential changes in climate hazard on network resilience. We demonstrate the research on the National Electricity Transmission System of Great Britain and assess the resilience of this system to changes in the intensity of wind storms under alternative energy futures. The analysis shows that infrastructure policies strongly shape the long-term spatial configuration of electricity networks and consequently this has profound impacts on their resilience. Though the system is resilient to wind storms under the current climate, our analysis shows that the system fails to meet electricity demand after an increase of only 5-10% in the intensity and frequency of wind storms, and a 50% increase could lead to the loss of 85% of peak winter demand. The approach is useful for identifying and communicating potential network risks to wider stakeholders and policy makers seeking to design a transition toward a low-carbon, yet resilient, future electricity systems.Index Terms-Complex system modeling, climate change, electricity networks, infrastructure resilience, resilience assessment.

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“…Vanzi (1996) and Hwang and Huo (1998) only consider the fragility of substations. The SYNER-G project (Cavalieri et al 2014b) proposes a methodology for assessing the overall performance of an electrical power system, but in doing so makes the assumption that conduits are not vulnerable to direct physical damage and so damage potential is limited to substations and generation plants. The HAZUS (NIBS 2003) tool does consider cables but does not model to the risk to each cable individually.…”

Section: Introductionmentioning

confidence: 99%

Seismic performance of buried electrical cables: evidence-based repair rates and fragility functions

Kongar

Giovinazzi

Rossetto

2016

Bull Earthquake Eng

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The fragility of buried electrical cables is often neglected in earthquakes but significant damage to cables was observed during the 2010-2011 Canterbury earthquake sequence in New Zealand. This study estimates Poisson repair rates, similar to those in existence for pipelines, using damage data retrieved from part of the electric power distribution network in the city of Christchurch. The functions have been developed separately for four seismic hazard zones: no liquefaction, all liquefaction effects, liquefactioninduced settlement only, and liquefaction-induced lateral spread. In each zone six different intensity measures (IMs) are tested, including peak ground velocity as a measure of ground shaking and five metrics of permanent ground deformation: vertical differential, horizontal, maximum, vector mean and geometric mean. The analysis confirms that the vulnerability of buried cables is influenced more by liquefaction than by ground shaking, and that lateral spread causes more damage than settlement alone. In areas where lateral spreading is observed, the geometric mean permanent ground deformation is identified as the best performing IM across all zones when considering both variance explained and uncertainty. In areas where only settlement is observed, there is only a moderate correlation between repair rate and vertical differential permanent ground deformation but the estimated model error is relatively small and so the model may be acceptable. In general, repair rates in the zone where no liquefaction occurred are very low and it is possible that repairs present in this area result from misclassification of hazard observations, either in the raw data or due -016-0077-3 to the approximations of the geospatial analysis. Along with hazard intensity, insulation material is identified as a critical factor influencing cable fragility, with paper-insulated lead covered armoured cables experiencing considerably higher repair rates than crosslinked polyethylene cables. The analysis shows no trend between cable age and repair rates and the differences in repair rates between conducting materials is shown not to be significant. In addition to repair rate functions, an example of a fragility curve suite for cables is presented, which may be more useful for analysis of network connectivity where cable functionality is of more interest than the number of repairs. These functions are one of the first to be produced for the prediction of damage to buried cables.123 Bull Earthquake Eng (2017) 15:3151-3181 DOI 10.1007/s10518

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Models for Seismic Vulnerability Analysis of Power Networks: Comparative Assessment

Cited by 60 publications

References 51 publications

Modeling the resilience of critical infrastructure: the role of network dependencies

Modeling the resilience of critical infrastructure: the role of network dependencies

Integrated Approach to Assess the Resilience of Future Electricity Infrastructure Networks to Climate Hazards

Seismic performance of buried electrical cables: evidence-based repair rates and fragility functions

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