Degree Type

Thesis

Date of Award

2017

Degree Name

Master of Science

Department

Electrical and Computer Engineering

Major

Electrical Engineering

First Advisor

Ian Dobson

Abstract

The world is highly dependent on electricity, and any service interruptions can be contagious

sometimes leading to devastating blackouts. This in turn have severe impacts on customers.

Large service interruption can impact an entire region. Therefore, reliability is an integral

part of the system operations for utilities. On an interruption of power supply caused by a

transmission or distribution failure, measures taken to restore the service highly depend on the

interruption duration of normal supply paths. This thesis is a systematic study of transmission

line restoration times with statistics obtained from a utility’s data. The empirical probability

distribution of transmission line restoration times is obtained from 14 years of field data. The

distribution of restoration times has a heavy tail that indicates that long restoration times,

although less frequent, routinely occur. The heavy tail differs from the convenient assumption

of exponentially distributed restoration times, impacts power system resilience, and makes

estimates of the mean time to repair highly variable. The mean restoration time of the heavy

tailed distribution and its confidence interval is estimated using special bootstrap methods and

its implications are outlined. The heavy tail in transmission line restoration times is one factor

to be considered in assessing power system resilience.

Copyright Owner

Sameera Kancherla

Language

en

File Format

application/pdf

File Size

43 pages

Included in

Engineering Commons

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