A method integrating deterministic and stochastic approaches for the simulation of voltage unbalance in electric power distribution systems

Author

Wang, Yaw-Juen ; Pierrat, Lambert

Author_Institution

Dept. of Electr. Eng., Nat. Yunlin Univ. of Sci. & Technol., Taiwan

Volume

16

Issue

2

fYear

2001

fDate

5/1/2001 12:00:00 AM

Firstpage

241

Lastpage

246

Abstract

This paper deals with modeling, analysis and Monte Carlo simulation of three-phase voltage unbalance based on data measured from a 69/11-kV distribution substation. Random variation of the voltage unbalance factor is modeled with the aid of correlated Gaussian random variables that represent random variations in three-phase active and reactive powers. Also presented in this paper is a network reduction technique using multiple-port Thevenin equivalent circuits that allows the Monte Carlo simulation to be carried out faster. Comparison of simulated and recorded probability distributions of voltage unbalance factors is given, and good agreement has been obtained

Keywords

Monte Carlo methods; distribution networks; equivalent circuits; power supply quality; power system dynamic stability; probability; random processes; reactive power; stochastic processes; substations; 11 kV; 69 kV; Monte Carlo simulation; deterministic approaches; distribution substation; electric power distribution systems; multiple-port Thevenin equivalent circuits; network reduction; network reduction technique; power quality; probability distributions; random processes; stochastic approaches; three-phase active power; three-phase reactive power; three-phase voltage unbalance; voltage unbalance factor random variation; voltage unbalance simulation; Analytical models; Gaussian distribution; Impedance; Induction motors; Power system harmonics; Power system modeling; Random variables; Reactive power; Stochastic processes; Voltage;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.918293

Filename

918293