DocumentCode :
1471999
Title :
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
Link To Document :
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