Puerto Rico Grid Resilience Assessment Using Binomial Analysis Following Hurricane Maria Considering Storm Effects

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Ng, Y. (2019). Puerto Rico Grid Resilience Assessment Using Binomial Analysis Following Hurricane Maria Considering Storm Effects. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Hurricane Maria was proven to be a very devastating storm in recent history. Ranked as the third costliest storm in the United States, Maria accumulated up to $90 billion in damages and accounted for at least 3,000 deaths. These deaths were primarily due to the aftermath of the storm for which it knocked out Puerto Rico’s entire power grid, leaving 3.4 million people without electricity. The residents were struggling to survive with the lack of proper food and water supplies, health care, and contact services. It took approximately a whole year for the island to have complete power restoration, which was a major issue. Solutions to prevent, or, minimize such major power loss again are important for a small island like Puerto Rico. Various techniques of increased grid resiliency may be implemented, provided with a proper analysis. In this study, binomial analyses were completed to analyze the effects of different storm events that occurred as a result of hurricane Maria. The impact of each storm event along each region of the island were used to help determine adequate solutions to further improve the existing power grid. It is recommended to replace the existing the single-point support and two-legged transmission towers with four-legged towers. In addition, it is also recommended to replace rectangular pole structures with tubular pole structures. The suggested solutions will be immediate solutions; however, a long-term solution is suggested in relation to future intense storms. Complete details of such solutions are further explained in this report.

Details
Author

Ng, Yenki

Title

Puerto Rico Grid Resilience Assessment Using Binomial Analysis Following Hurricane Maria Considering Storm Effects

Physical Description

1 online resource (53 pages) : PDF

Date

2019

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Hurricane Maria was proven to be a very devastating storm in recent history. Ranked as the third costliest storm in the United States, Maria accumulated up to $90 billion in damages and accounted for at least 3,000 deaths. These deaths were primarily due to the aftermath of the storm for which it knocked out Puerto Rico’s entire power grid, leaving 3.4 million people without electricity. The residents were struggling to survive with the lack of proper food and water supplies, health care, and contact services. It took approximately a whole year for the island to have complete power restoration, which was a major issue. Solutions to prevent, or, minimize such major power loss again are important for a small island like Puerto Rico. Various techniques of increased grid resiliency may be implemented, provided with a proper analysis. In this study, binomial analyses were completed to analyze the effects of different storm events that occurred as a result of hurricane Maria. The impact of each storm event along each region of the island were used to help determine adequate solutions to further improve the existing power grid. It is recommended to replace the existing the single-point support and two-legged transmission towers with four-legged towers. In addition, it is also recommended to replace rectangular pole structures with tubular pole structures. The suggested solutions will be immediate solutions; however, a long-term solution is suggested in relation to future intense storms. Complete details of such solutions are further explained in this report.

Genre

masters theses

Subjects--Topics

Civil engineering

Degree

M.S.

Subject Area

Civil Engineering

Advisor(s)

Chen, Shen-En

Committee Members

Pando, Miguel
Tang, Wenwe

Degree Note

Thesis (M.S.)--University of North Carolina at Charlotte, 2019.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

Ng_uncc_0694N_12305

Permalink

http://hdl.handle.net/20.500.13093/etd:2161