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 :
Hanoi Univ. of Technol., Hanoi
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 regarding phase loads that create better estimation for voltage sag performance for the distribution system.
Keywords :
distribution networks; fault location; normal distribution; power supply quality; stochastic processes; bivariate normal distribution; distribution systems; fault distribution modeling; phase loads; power quality; stochastic bivariate models; stochastic prediction; voltage sag; 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 (PQ); stochastic prediction; voltage sag frequency;
Journal_Title :
Power Delivery, IEEE Transactions on
DOI :
10.1109/TPWRD.2007.905817