Wind Risk Assessment of Electric Power Lines due to Hurricane Hazard

Reinoso, Eduardo; Niño, Mauro; Berny, Emilio; Inzunza, Indira

doi:10.1061/(asce)nh.1527-6996.0000363

Cited by 12 publications

(4 citation statements)

References 31 publications

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“…In the field of disaster risk assessment and management, there is a broad scientific consensus on the proposal of methodological models that include vulnerability, hazards and resilience, understood as the capacity to reduce vulnerability, control risks and manage uncertainty in potential disaster scenarios (from the Hazard, Vulnerability, Capacity and Risk Assessment model, hereafter HVCRA). In this way, we found HVCRA methods in flood risk management (Kamanga et al 2020;Koks et al 2015;Rezende et al 2020), droughts (Ebi and Bowen 2016;Meza et al 2020), risks in areas sensitive to storms or hurricanes (Lagomarsino and Giovinazzi 2006;Reinoso et al 2020;Taramelli et al 2015), earthquakes (Kadam et al 2020;Lantada et al 2009;Zuloaga et al 2020) or consequences of climate change (van Aalst et al 2008;Dolan and Walker 2006;Ford and Smit 2004;Nguyen et al 2016;Preston et al 2011).…”

Section: Introductionmentioning

confidence: 78%

The Social Services Risk Index at Local Level: A Tool for Diagnosis and Decision Making

et al. 2023

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The COVID-19 pandemic has had a decisive impact on our society, generating both direct and indirect effects in a multitude of dimensions, beyond the purely health-related, which have conditioned people’s well-being and quality of life. The social services system has played an essential role in absorbing the consequences of these impacts on the most socially vulnerable population. Analysing the social impacts and monitoring the risks derived from the pandemic can favour the prevention of risk situations, adjust the resources of the social services system to changing social realities and facilitate the strategic decision-making process to mitigate or minimise the impacts of potential socio-annual crises or catastrophes. This article presents a methodological process, based on the HCVRA (Hazards, Capacity Building, Vulnerability, Risk Assessment) disaster management models, designed ad hoc with the aim of identifying, on the one hand, the social impacts of COVID-19 and, on the other hand, the areas with the highest social risk in the post-COVID scenario. The application of this methodological process has made it possible to configure a set of indicators based on public databases, defined by consulting experts and weighted by a panel of stakeholders through a multi-criteria method to obtain a territorialised risk index at the highest level of disaggregation of the available data, based on the dimensions of vulnerability, threat and resilience.

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Section: Introductionmentioning

confidence: 78%

The Social Services Risk Index at Local Level: A Tool for Diagnosis and Decision Making

et al. 2023

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“…The weights in this method combine the subjective and objective weights. After calculating the indicator weights for the AHP and entropy methods and then processing them, the final weights are shown in Equation (18).…”

Section: Ahp-ewm-based Indicator Weighting Modelmentioning

confidence: 99%

“…Another direction has considered the correlation between risks and then quantified the risks of real situations to guide realistic work [17]. Reinoso et al proposed a risk-based maintenance methodology for transmission lines that uses machine learning and survival analysis to assess their condition and prioritize their replacement [18]. Jones et al presented a method for evaluating the accessibility and vulnerability of the transmission lines and roads in Puerto Rico using GIS data and graph theory [19].…”

Section: Introductionmentioning

confidence: 99%

Risk Reliability Assessment of Transmission Lines under Multiple Natural Disasters in Modern Power Systems

Fan,

Zeng,

Ming

et al. 2023

Energies

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Climate change has led to more frequent extreme weather events, and various natural disasters have posed risks to the operation of transmission lines. Line failures caused by natural disasters are unpredictable and bring additional maintenance work. Therefore, this paper proposes a transmission line risk reliability assessment method that considers the combined effects of multiple natural disasters. This method establishes a theory of disaster risk quantification that considers the probability of the occurrence of the risk, the degree of the impact of the risk on the line, and the severity of the risk disaster. The risk weights for different natural disasters are calculated by combining a hierarchical analysis and entropy weighting methods. The example of a transmission line risk assessment under the combined effects of multiple natural disasters for a Sichuan region verifies the proposed method’s effectiveness. The results show that the method effectively assesses the operational risk to transmission lines under the combined effects of natural disasters. The assessment results can be used for disaster recovery and line risk prevention.

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“…Wind hazard losses are catastrophic and devastating specifically for wind-driven by hurricane and tornados. The current literature is populated with many studies that investigate the impact of wind loads on buildings and infrastructure [1][2][3][4]. However, these studies, while they are novel, there is still a huge amount of uncertainties within the input parameters for the wind load calculation and the resistance of the impacted structures [5].…”

Section: Introductionmentioning

confidence: 99%

Stochastic Modeling of Uncertainties in the Wind Load Pressure on Residential Buildings Using Different Stochastic Techniques

Nofal¹

2020

CTCSE

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Wind Risk Assessment of Electric Power Lines due to Hurricane Hazard

Cited by 12 publications

References 31 publications

The Social Services Risk Index at Local Level: A Tool for Diagnosis and Decision Making

The Social Services Risk Index at Local Level: A Tool for Diagnosis and Decision Making

Risk Reliability Assessment of Transmission Lines under Multiple Natural Disasters in Modern Power Systems

Stochastic Modeling of Uncertainties in the Wind Load Pressure on Residential Buildings Using Different Stochastic Techniques

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