Modeling and Analysis of Distribution Reliability Indices

Abstract

Assessment of customer power supply reliability is an important part of distribution system operation and planning. Monte Carlo simulations can be used to find the statistical distribution of the reliability indices, along with their mean and standard deviation. The standard deviation of the reliability indices provides distribution engineers with information on the expected range of the annual values. However, the Monte Carlo simulation usually is a time-consuming computation. In this paper, an efficient Monte Carlo simulation method for distribution system reliability assessment is presented. Analysis of outage data from a practical distribution system is performed to determine the failure and repair models appropriate for use in the Monte Carlo simulation. The sensitivity of the reliability indices to the choice of model is presented. Finally, the impact of protection devices on the statistical distribution of System Average Interruption Frequency Index (SAIFI) for a practical distribution feeder is presented.