Abstract
Extensive use has been made of lifecycle-cost assessment to enhance the cost-effectiveness and resilience of facilities management. However, if such assessments are to be truly effective, supplemental information will be needed on the major costs to be expected over buildings’ entire lives. Electricity generation and distribution systems, for example, are absolutely indispensable to industry and human society, not least in the operation of buildings and other infrastructure as networks. The widespread disruption that ensues when such power systems are damaged often carries considerable repair costs. Natural disasters likewise can cause extensive societal, economic, and environmental damage. Such damage is often associated with lengthy power outages that, as well as being directly harmful, can hinder emergency response and recovery. Accordingly, the present study investigated the correlations of natural hazard indicators such as wind speed and rainfall, along with environmental data regarding the power failure in Florida caused by Hurricane Irma in 2017 utilizing multiple regression analysis. The environmental data in question, selected on the basis of a thorough literature review, was tree density. Our analysis indicated that the independent variables, maximum wind speed, total rainfall, and tree density, were all significantly correlated with the dependent variable, power failure. Among these, rainfall was the least significant. Despite there being only three independent variables in the model, its adjusted coefficient of determination (0.512) indicated its effectiveness as a predictor of the power outages caused by Hurricane Irma. As such, our results can serve the construction industry’s establishment of advanced safety guidelines and structural designs power transmission systems in regions at risk of hurricanes and typhoons. Additionally, insurance companies’ loss-assessment modeling for power-system facilities would benefit from incorporating the three identified risk indicators. Finally, our findings can serve as a useful reference to policymakers tasked with mitigating power outages’ effects on infrastructure in hurricane-prone areas. It is hoped that this work will be extended, facilitating infrastructure restoration planning and making societies and economies more sustainable.
Highlights
Hurricanes, typhoons, and tropical cyclones have been occurring more frequently and increasing in intensity because of global warming [1,2,3,4]
N stands for the total number of relative outage frequency (ROF) data points during Hurricane Irma’s passage through Florida in September 2017
The insurance industry, for its part, can benefit from using the natural hazard indicators we identified, for risk-management and risk-mitigation of insured properties or infrastructure facilities, and maximizing their profits
Summary
Hurricanes, typhoons, and tropical cyclones have been occurring more frequently and increasing in intensity because of global warming [1,2,3,4]. A Munich Re report [8] revealed that the 2017 damage caused to the United States by hurricanes—around $220 billion—was the highest ever recorded, due to the trio of Hurricanes Harvey, Irma, and Maria. Such events can cause severe economic, environmental, and societal damage, not least through lengthy interruptions to the supply of electric power, one of the most important of which is increases to the lifecycle costs of buildings and other infrastructure. In the U.S, the costs of damage due to power outages have been increasing [9,10], and are closely associated with hurricanes. Hurricane Irene, for example, deprived 6.5 million people of power in 2011, while the parallel figure for Hurricane Sandy the following year was 8.5 million [9]
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