Quantification of Uncertainty in End-of-Life Failure Models of Power Transformers for Transmission Systems Reliability Studies

Abstract

Power system components have a relatively long life span and hence there is not enough data to derive an accurate end-of-life failure model. This contributes to the uncertainty in system reliability assessment. This paper discusses the quantification of the effect of uncertainty in end-of-life failure models on system reliability indices. This paper characterizes the uncertainty by a mixed aleatory-epistemic uncertainty model, where the aleatory uncertainty originated from the variability of failure events and the epistemic uncertainty originated from a lack of data. The mixed aleatory-epistemic uncertainty was propagated using two methods: Second Order Probability and Dempster-Shafer Evidence Theory (DSET). Power transformers were chosen as the case study equipment and the methods were applied on a realistic transmission network.