DocumentCode
1373905
Title
Automated Graph-Based Methodology for Fault Detection and Location in Power Systems
Author
Düstegör, Dilek ; Poroseva, Svetlana V. ; Hussaini, M. Yousuff ; Woodruff, Stephen
Author_Institution
Center for Adv. Power Syst., Florida State Univ., Tallahassee, FL, USA
Volume
25
Issue
2
fYear
2010
fDate
4/1/2010 12:00:00 AM
Firstpage
638
Lastpage
646
Abstract
This study investigates how the model-based fault detection and location approach of structural analysis can be adapted to meet the needs of power systems, where challenges associated with increased system complexity make conventional protection schemes impractical. With a global view of the protected system and the systematic and automated use of the system´s analytical redundancy, faults are detected and located by more than one means. This redundancy can be used as a confirmation mechanism within a wide-area protection scheme to avoid unnecessary or false tripping due to protection component failure or disturbance. Furthermore, this redundancy turns the sensor configuration problem into an optimization problem with regard to fault detection and location. The effectiveness of different system topologies can then be compared on the basis of the optimal number of sensors they require. The principle of structural analysis is described in detail and illustrated on a simple power system model. Pertinence of the approach is demonstrated through simulation.
Keywords
graph theory; optimisation; power system faults; power system protection; automated graph-based methodology; model-based fault detection; model-based fault location; optimization problem; power system protection; protection component disturbance; protection component failure; sensor configuration problem; structural analysis; system complexity; wide-area protection scheme; Fault diagnosis; power system protection; structural analysis; wide-area protection;
fLanguage
English
Journal_Title
Power Delivery, IEEE Transactions on
Publisher
ieee
ISSN
0885-8977
Type
jour
DOI
10.1109/TPWRD.2009.2037005
Filename
5371843
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