Confidence Intervals Estimation for Reliability Data of Power Distribution Equipments Using Bootstrap

The uncertainty assessment in reliability indices is usually performed by the propagation of uncertainties in input data reliability (failure rates and repair times) for the estimated reliability indices using mathematical models, such as fuzzy sets. This analysis cannot be directly applied in distribution networks when there are significant errors between historical and predicted indices. In this case, the propagation of uncertainty in power distribution network must take an opposite direction, that means: to use historical reliability indices to determine the uncertainties associated with reliability input data. The main aim of this paper is to determine the confidence intervals associated with reliability data of power distribution equipments based on available historical indices. These intervals are determined by combining the bootstrap technique with calibration models. The tests with a Brazilian distribution networks demonstrate that the proposed method can estimate the upper and lower bounds for the reliability data in a specified significance level.