Committee Chair
Eltom, Ahmed H.
Committee Member
Karrar, Abdelrahman A.; Kobet, Gary L.
College
College of Engineering and Computer Science
Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
System monitoring and contingency analysis are crucial functions in power control centers. In order to perform these analyses, a complete model of the power network is needed. Moreover, to account for system configuration dynamics, this model must be continuously updated for the purpose of on-line analysis. Several topology processing schemes have been developed in the literature to accomplish this task. The majority of these schemes process breaker statuses to detect changes in system topology. Transformer tap positions as well as statuses of capacitor and reactor bank switches must also be included in the process. This results in a complicated topology processing scheme. In this work, a simple and quick method for on-line detection and identification of system topology changes is introduced. This method is based on representing line outages with fictitious nodal power injections. The injections are calculated using system states obtained from phasor measurement units (PMUs). This scheme can be applied on reduced systems where parts of the network are not covered by PMU measurements. The scheme was tested during different outage events in the IEEE39-bus system. The obtained results validated the algorithm’s ability to detect and identify line outage events effectively and efficiently.
Degree
M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.
Date
12-2016
Subject
Electric power systems -- Automation
Document Type
Masters theses
DCMI Type
Text
Extent
viii, 57 leaves
Language
English
Rights
https://rightsstatements.org/page/InC/1.0/?language=en
License
http://creativecommons.org/licenses/by-nc-nd/3.0/
Date Available
7-1-2017
Recommended Citation
Mohamed, Elamin Ali Elamin, "Fast power network detection of topology change locations using PMU measurements" (2016). Masters Theses and Doctoral Dissertations.
https://scholar.utc.edu/theses/482
Department
Dept. of Electrical Engineering