Date of Award
Master of Science
Electrical and Computer Engineering
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.
Kancherla, Sameera, "Data Analysis of Transmission Line Restoration Times" (2017). Graduate Theses and Dissertations. 16602.