DocumentCode :
28827
Title :
Incorporation of protection system failures into bulk power system reliability assessment by Bayesian networks
Author :
Eliassi, Mojtaba ; Seifi, Hossein ; Haghifam, Mahmoud-Reza
Author_Institution :
Fac. of Electr. & Comput. Eng., Tarbiat Modares Univ. (TMU), Tehran, Iran
Volume :
9
Issue :
11
fYear :
2015
fDate :
8 6 2015
Firstpage :
1226
Lastpage :
1234
Abstract :
Although protection failures have critical influence on the reliability of power systems, the methodology of assessing composite power system reliability including protection failures has not gone far enough yet. In this study, a Bayesian network (BN)-based analytical methodology is proposed for modelling and analysis of the impact of protection system failures on bulk power system reliability. Initially, basic BN model of composite power system reliability is constructed based on its minimal cutsets (MCs) and logical relationships between components, MCs and system failure. Then, different failure modes of protection system and the interactions among components caused by protection system failures are conveniently incorporated into the basic BN model and the reliability calculations. By using the presented method, several restrictive assumptions, implicit in the other methods, can be removed. Moreover, applying BN provides additional capabilities at modelling and analysis levels. The proposed method is applied to the IEEE reliability test system and the results demonstrate that the proposed method is effective and is flexible in applications.
Keywords :
Bayes methods; failure analysis; graph theory; power system faults; power system protection; power system reliability; set theory; BN model; Bayesian network-based analytical methodology; IEEE reliability test system; bulk power system reliability assessment; composite power system reliability assessment methodology; logical relationships; minimal cutsets; protection system failures; reliability calculations;
fLanguage :
English
Journal_Title :
Generation, Transmission & Distribution, IET
Publisher :
iet
ISSN :
1751-8687
Type :
jour
DOI :
10.1049/iet-gtd.2014.0365
Filename :
7173375
Link To Document :
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