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

被引：15

作者：

Khanh, Bach Quoc ^{[1
]}

Won, Dong-Jun ^{[2
]}

Moon, Seung-Il ^{[3
]}

机构：

[1] Hanoi Univ Technol, Elect Power Syst Dept, Fac Elect Engn, Hanoi, Vietnam

[2] Inha Univ, Sch Elect Engn, Inchon 402751, South Korea

[3] Seoul Natl Univ, Sch Elect Engn & Comp Sci, Seoul 151742, South Korea

来源：

IEEE TRANSACTIONS ON POWER DELIVERY | 2008年 / 23卷 / 01期

关键词：

bivariate normal distribution; distribution system; fault distribution modeling; phase loads; power quality (PQ); stochastic prediction; voltage sag frequency;

D O I：

10.1109/TPWRD.2007.905817

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：347 / 354

页数：8

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