  The estimation of the conditional failure rate (CFR) of an overhead
transmission line (OTL) is essential for power system operational reliability
assessment. It is hard to predict the CFR precisely, although great efforts
have been made to improve the estimation accuracy. One significant difficulty
is the lack of available outage samples, due to which the law of large numbers
is no longer applicable and no convincing statistical result can be obtained.
To address this problem, in this paper a novel imprecise probabilistic approach
is proposed to estimate the CFR of an OTL. The imprecise Dirichlet model (IDM)
is applied to establish the imprecise probabilistic relation between a single
conditional variable and the failure rate of an OTL. Then a credal network is
constructed to integrate the IDM estimation results corresponding to different
conditional variables and infer the CFR. Instead of providing a single-valued
estimation result, the proposed approach predicts the possible interval of the
CFR in order to explicitly indicate the uncertainty of the estimation and more
objectively represent the available knowledge. The proposed approach is
illustrated by estimating the CFRs of two LGJ-300 transmission lines located in
the same region; the test results validate its effectiveness.
