Fault distribution modeling using stochastic bivariate models for prediction of voltage sag in distribution systems

Bach Quoc Khanh; Dong Jun Won; Seung Il Moon

doi:10.1109/TPWRD.2007.905817

Fault distribution modeling using stochastic bivariate models for prediction of voltage sag in distribution systems

Bach Quoc Khanh, Dong Jun Won, Seung Il Moon

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Abstract

This paper presents a new method regarding fault distribution modeling for the stochastic prediction study of voltage sags in the distribution system. 2-D stochastic models for fault modeling make it possible to obtain the fault performance for the whole system of interest, which helps to obtain not only sag performance at individual locations but also system sag performance through system indices of voltage sag. By using the bivariate normal distribution for fault distribution modeling, this paper estimates the influence of model parameters on system voltage sag performance. The paper also develops the modified SARFI_X regarding phase loads that create better estimation for voltage sag performance for the distribution system.

Original language	English
Pages (from-to)	347-354
Number of pages	8
Journal	IEEE Transactions on Power Delivery
Volume	23
Issue number	1
DOIs	https://doi.org/10.1109/TPWRD.2007.905817
State	Published - Jan 2008

Bibliographical note

Funding Information:
Manuscript received August 2, 2005; revised December 5, 2006. This work was supported by the Korea Foundation for Advanced Studies’ International Scholar Exchange Fellowship for the academic year of 2004–2005. Paper no. TPWRD-00456-2005.

Keywords

Bivariate normal distribution
Distribution system
Fault distribution modeling
Phase loads
Power quality (PQ)
Stochastic prediction
Voltage sag frequency

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10.1109/TPWRD.2007.905817

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title = "Fault distribution modeling using stochastic bivariate models for prediction of voltage sag in distribution systems",

abstract = "This paper presents a new method regarding fault distribution modeling for the stochastic prediction study of voltage sags in the distribution system. 2-D stochastic models for fault modeling make it possible to obtain the fault performance for the whole system of interest, which helps to obtain not only sag performance at individual locations but also system sag performance through system indices of voltage sag. By using the bivariate normal distribution for fault distribution modeling, this paper estimates the influence of model parameters on system voltage sag performance. The paper also develops the modified SARFIX regarding phase loads that create better estimation for voltage sag performance for the distribution system.",

keywords = "Bivariate normal distribution, Distribution system, Fault distribution modeling, Phase loads, Power quality (PQ), Stochastic prediction, Voltage sag frequency",

author = "Khanh, {Bach Quoc} and Won, {Dong Jun} and Moon, {Seung Il}",

note = "Funding Information: Manuscript received August 2, 2005; revised December 5, 2006. This work was supported by the Korea Foundation for Advanced Studies{\textquoteright} International Scholar Exchange Fellowship for the academic year of 2004–2005. Paper no. TPWRD-00456-2005.",

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KW - Power quality (PQ)

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Fault distribution modeling using stochastic bivariate models for prediction of voltage sag in distribution systems

Abstract

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Keywords

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