Hurricanes and Power System Reliability-The Effects of Individual Decisions and System-Level Hardening

Reilly, Allison; Tonn, Gina; Zhai, Chengwei; Guikema, Seth D.

doi:10.1109/jproc.2017.2689720

Cited by 21 publications

(24 citation statements)

References 63 publications

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“…The focus of the illustrative example in the following section is on damage to residential buildings from hurricanes, but other consequences could be assessed too. For example, Reilly et al [ 47 ] assessed the likelihood of electric-power outages due to hurricanes.…”

Section: Methodsmentioning

confidence: 99%

“…Damage state three implies extensive house damage including cracks in the foundations (earthquake) or loss of the roof’s sheathing (hurricane). A house in damage state four experiences complete failure and the structure is typically unsalvageable [ 16 , 47 ]. We assume that if more than one hazard affects the region, each house’s most severe damage state in year n is used.…”

Section: Methodsmentioning

confidence: 99%

“…Policies may be simple (e.g., “1% of agents respond to an incentive and mitigate to a higher resistance level”), targeted (e.g., “agents with homes within 1 kilometer of the coastline are eligible for a mitigation subsidy”) [ 59 ], or complex (e.g., structural economic models [ 60 ]). Further, they could be driven by the behavior or collective action of agents [ 47 , 61 ]. Subsidies are not the only mechanism to induce mitigation.…”

Section: Methodsmentioning

confidence: 99%

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Evolution of vulnerability of communities facing repeated hazards

et al. 2017

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The decisions that individuals make when recovering from and adapting to repeated hazards affect a region’s vulnerability in future hazards. As such, community vulnerability is not a static property but rather a dynamic property dependent on behavioral responses to repeated hazards and damage. This paper is the first of its kind to build a framework that addresses the complex interactions between repeated hazards, regional damage, mitigation decisions, and community vulnerability. The framework enables researchers and regional planners to visualize and quantify how a community could evolve over time in response to repeated hazards under various behavioral scenarios. An illustrative example using parcel-level data from Anne Arundel County, Maryland—a county that experiences fairly frequent hurricanes—is presented to illustrate the methodology and to demonstrate how the interplay between individual choices and regional vulnerability is affected by the region’s hurricane experience.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Evolution of vulnerability of communities facing repeated hazards

et al. 2017

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“…Agent based modeling (ABM) provides an opportunity to simulate individual homeowner responses to flooding of their residences (e.g. relocation or reconstruction), the influence of policy incentives on their behavior and their preferences for public investment in community-wide mitigations (Reilly, et al 2017). Coupling the outputs of hydrodynamic storm surge models with these models will drive representative flood levels for each house and the resulting homeowner responses (Pei, et al 2015).…”

Section: Conceptual Design Improvementsmentioning

confidence: 99%

System Engineering Strategies for Coastal Flooding Mitigation

McEligot

Brouse

2018

INCOSE International Symp

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Coastal flooding is a significant economic hazard. Multiple mitigation measures may be complementary or counterproductive. This paper identifies the applicability of System Engineering techniques in the development of a coherent mitigation policy at the community level. Current mitigation design practices are described, improvements are identified and a model‐based approach is recommended. An integrated computational fluid dynamics and agent based modeling framework is proposed to conduct cost‐benefit analysis of public structural mitigations and other options.

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“…The use of machine-learning algorithms has been standard practice for predicting power outages in the past two decades [7][8][9][10][11][12][13]. Nateghi et al used a Bayesian additive regression tree to predict power outages caused from hurricanes and the model showed a root mean squared error (RMSE) of 894 [14].…”

Section: Introductionmentioning

confidence: 99%

The Effect of Lead-Time Weather Forecast Uncertainty on Outage Prediction Modeling

2021

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Weather-related power outages affect millions of utility customers every year. Predicting storm outages with lead times of up to five days could help utilities to allocate crews and resources and devise cost-effective restoration plans that meet the strict time and efficiency requirements imposed by regulatory authorities. In this study, we construct a numerical experiment to evaluate how weather parameter uncertainty, based on weather forecasts with one to five days of lead time, propagates into outage prediction error. We apply a machine-learning-based outage prediction model on storm-caused outage events that occurred between 2016 and 2019 in the northeastern United States. The model predictions, fed by weather analysis and other environmental parameters including land cover, tree canopy, vegetation characteristics, and utility infrastructure variables exhibited a mean absolute percentage error of 38%, Nash–Sutcliffe efficiency of 0.54, and normalized centered root mean square error of 68%. Our numerical experiment demonstrated that uncertainties of precipitation and wind-gust variables play a significant role in the outage prediction uncertainty while sustained wind and temperature parameters play a less important role. We showed that, while the overall weather forecast uncertainty increases gradually with lead time, the corresponding outage prediction uncertainty exhibited a lower dependence on lead times up to 3 days and a stepwise increase in the four- and five-day lead times.

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Hurricanes and Power System Reliability-The Effects of Individual Decisions and System-Level Hardening

Cited by 21 publications

References 63 publications

Evolution of vulnerability of communities facing repeated hazards

Evolution of vulnerability of communities facing repeated hazards

System Engineering Strategies for Coastal Flooding Mitigation

The Effect of Lead-Time Weather Forecast Uncertainty on Outage Prediction Modeling

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