Two probabilistic methods for voltage sag estimation in distribution systems

This paper presents a comparison between Monte Carlo simulation and fault position (state enumeration) methods applied for estimating voltage sag indices in radial unbalanced distribution network regarding to accuracy and CPU time. The system is represented in phase coordinates and the fault analysis is fulfilled using the admittance summation method. Tests are performed in the medium voltage CIGRÈ Benchmark System for Network Integration of Renewable and Distributed Energy Resources. The results show that the fault position method is competitive with the Monte Carlo simulation regarding to the precision of the assessed indices even when a few states are considered. It results in a smaller CPU time for the fault position in comparison with the Monte Carlo method.