Masters Theses


"The increasing scale and complexity of power grids exacerbate concerns about failure propagation. A single contingency, such as outage of a transmission line due to overload or weather-related damage, can cause cascading failures that manifest as blackouts. One objective of smart grids is to reduce the likelihood of cascading failure through the use of power electronics devices that can prevent, isolate, and mitigate the effects of faults. Given that these devices are themselves prone to failure, we seek to quantify the effects of their use on dependability attributes of smart grid. This thesis articulates analytical methods for analyzing two dependability attributes - reliability and survivability - and proposes a recovery strategy that limits service degradation. Reliability captures the probability of system-level failure; Survivability describes degraded operation in the presence of a fault. System condition and service capacity are selected as measures of degradation. Both reliability and survivability are evaluated using N-1 contingency analysis. Importance analysis is used to determine a recovery strategy that maintains the highest survivability in the course of the recovery process. The proposed methods are illustrated by application to the IEEE 9-bus test system, a simple model system that allows for clear articulation of the process. Simulation is used to capture the effect of faults in both physical components of the power grid and the cyber infrastructure that differentiates it as a smart grid"--Abstract, page iii.


Sedigh, Sahra

Committee Member(s)

Hurson, A. R.
Joo, Jhi-Young


Computer Science

Degree Name

M.S. in Computer Science


Missouri University of Science and Technology

Publication Date

Fall 2015


viii, 46 pages

Note about bibliography

Includes bibliographical references(pages 42-45).


© 2015 Isam Abdulmunem Alobaidi, All rights reserved.

Document Type

Thesis - Open Access

File Type




Subject Headings

Smart power grids -- Mathematical models
Electric power failures -- Prevention
Intelligent control systems

Thesis Number

T 10777

Electronic OCLC #