Title :
Forced Outage Cause Identification Based on Bayesian Networks
Author :
Tronchoni, A.B. ; Pretto, C.O. ; Licks, V. ; Rosa, M.A. ; Lemos, F.A.B.
Author_Institution :
Electr. Energy Syst. Group, Pontifical Catholic Univ. of Rio Grande do Sul, Rio Grande
Abstract :
The advances in area of information technology and applications, specially mobile and wireless technology, are providing conditions to improve data acquisition to be used in power system analysis. These conditions together with computational intelligence methods help provide an improvement in reliability analysis of distribution systems. This paper presents the development of a computational systems using mobile computing and a methodology based on Bayesian Networks to identify forced outage causes. The proposed system was validated using data collection of Brazilian distribution utility.
Keywords :
belief networks; data acquisition; fault diagnosis; mobile computing; power distribution faults; power distribution reliability; power system analysis computing; Bayesian networks; Brazilian distribution utility; computational intelligence methods; data acquisition; distribution systems; forced outage cause identification; mobile computing; power system analysis; reliability analysis; Bayesian methods; Computer networks; Data acquisition; IEEE members; Information technology; Mobile computing; Personal digital assistants; Power system analysis computing; Power system reliability; Resource management; Bayesian networks; mobile computing; outage; personal digital assistant (PDA); reliability;
Conference_Titel :
Power Tech, 2007 IEEE Lausanne
Conference_Location :
Lausanne
Print_ISBN :
978-1-4244-2189-3
Electronic_ISBN :
978-1-4244-2190-9
DOI :
10.1109/PCT.2007.4538554
