This paper proposes a joint methodology for quantifying both the aleatory and epistemic uncertainties of the transmission line end-of-life failure model. Aleatory uncertainty accounts for the well-known probabilistic or random failures. Epistemic uncertainty modeling accounts for the lack of knowledge and imprecision in the parameters of the failure model. Imprecision arises due to the lack of historical failure data as transmission lines have long life cycle. The studied transmission lines are also equipped with the dynamic thermal rating system. This reflects the current realistic situation where system operators are able to up-rate their networks due to the advancement of sensors, which is normally preferred over the purchase of new transmission assets. The end-of-life failure is modeled using the Arrhenius-Weibull model from the authors' previous paper. Results from this paper demonstrate that the joint analysis of both types of uncertainties are more useful, as they provide a range of reliability index values rather than a single crisp value as in the pure probabilistic approach.
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Jiashen Teh (2018) studied this question.
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