Interval Estimation for Conditional Failure Rates of Transmission Lines With Limited Samples

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 One significant difficulty\nis the lack of available outage samples, due to which the law of large numbers\nis no longer applicable and no convincing statistical result can be obtained.\nTo address this problem, in this paper a novel imprecise probabilistic approach\nis proposed to estimate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