Assessment Model for Measuring Cascading Economic Impacts Due to Severe Weather-Induced Power Outages

KwangHyuk Im, Purdue University

Abstract

Annual severe weather-induced power outages result in devastating damages to people and industries. The damages of severe weather-induced power outages cause billions of dollars of economic loss among industries within the U.S. economic system. Building the resilience of the utility industry in regard to electricity is significant to reduce the risk of power outages caused by extreme environmental disasters. This in turn would minimize economic loss among industries in the economic system and improve the security of the utility industry.The existing framework for assessing the impact of extreme weather associated with power outages lacks efficient methods and mechanisms. Therefore, a better understanding of the societal and economic loss from severe weather-induced power outages could be gained from a new framework that assesses the costs and benefits of the investments made in the utility industry with reference to the electricity services. In other words, there is no effective assessment model to measure the economic loss caused and the reliability standards impacted by extreme environmental disasters.To address this gap, this research has developed an assessment model and framework to measure cascading economic impacts in terms of gross domestic product (GDP) loss due to severe weather-induced power outages. The major objectives of this research were to (1) identify physical correlations between different industries within an economic system, (2) define deterministic relationships through the values of interconnectedness and interdependency between 71 industries, (3) complete probabilistic estimation of economic impacts using historical economic data spanning from 1997 to 2016, and (4) develop an assessment model that can be used in the future to measure economic loss in terms of gross domestic product (GDP) across 71 industries.Above all, this research conducted an analysis of the database of the U.S. Bureau of Economic Analysis database, which was released in November 2017. Information from the database about the U.S economic system, consisting 71 industries, served as the fundamental data. An interconnectedness matrix and interdependency matrix covering the 71 industries over 20 years were developed using a normalized make matrix and a normalized use matrix. The interconnectedness and interdependency matrices created with this research modeled interconnectedness and interdependency, respectively, between the 71 industries. The models, representing one of the results of this research, are called “A matrix” and “A* matrix” and show the interconnectedness and interdependency between the 71 industries from 1997 to 2016. This research conducted analyses of patterns, trends, and relationships on a national level using U.S. economic data from the utility Industry’s point of view and completed an assessment of economic impact in terms of GDP loss suffered from inoperability (1%~50%) of the utility Industry due to power outages within the U.S. economic system.Finally, a simulation model was developed to estimate economic loss in terms of GDP due to the ripple effect of severe weather-induced power outages. The several steps involved in this process included (1) defining the inoperability of the utility industry as the direct inoperability to cause GDP loss in the primary stage of economic impact from severe weatherinduced power outages, (2) identifying the top three industries most affected from the inoperability of the utility industry as the indirect inoperability to cause GDP loss in the secondary stage of economic impact, (3) identifying the top nine industries most affected from the inoperability of the utility industry as the induced inoperability to cause GDP.

Degree

M.Sc.

Advisors

Hastak, Purdue University.

Subject Area

Economics|Education|Energy|Finance|Marketing|Petroleum engineering|Political science|Transportation

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