DocumentCode :
3397942
Title :
Fault distribution modeling using stochastic bivariate models for prediction of voltage sag in distribution systems
Author :
Khanh, Bach Quoc ; Won, Dong-Jun ; Moon, Seung-Il
Author_Institution :
Electr. Power Syst. Dept., Hanoi Univ. of Technol., Hanoi
fYear :
2008
fDate :
21-24 April 2008
Firstpage :
1
Lastpage :
8
Abstract :
This paper presents a new method on fault distribution modeling for stochastic prediction study of voltage sags in the distribution system. Two-dimensional stochastic models for fault modeling make it possible to obtain the fault performance for the whole system of interest, which helps obtaining not only sag performance at individual locations but also system sag performance through system indices of voltage sag. By using bivariate normal distribution for fault distribution modeling, the paper estimates the influence of model parameters on system voltage sag performance. The paper also develops the modified SARFIx regarding phase loads that creates better estimation for voltage sag performance for distribution system.
Keywords :
distribution networks; fault diagnosis; normal distribution; power supply quality; stochastic processes; bivariate normal distribution; distribution system voltage sag prediction; fault distribution modeling; stochastic bivariate models; stochastic prediction; Computational modeling; Frequency; Mathematical model; Power quality; Power system modeling; Power system simulation; Predictive models; Stochastic processes; Stochastic systems; Voltage fluctuations; bivariate normal distribution; distribution system; fault distribution modeling; phase loads; power quality; stochastic prediction; voltage sag frequency;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transmission and Distribution Conference and Exposition, 2008. T&D. IEEE/PES
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-1903-6
Electronic_ISBN :
978-1-4244-1904-3
Type :
conf
DOI :
10.1109/TDC.2008.4517161
Filename :
4517161
Link To Document :
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