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Bayesian Inference of Power System Insulation Reliability in the Presence of Voltage Harmonics


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DOI: https://doi.org/10.15866/iree.v11i3.8888

Abstract


This article illustrates a Bayesian inference methodology for the parametric evaluation of the reliability of power system components in the presence of voltage harmonics. The methodology starts from an experimentally-based life model for solid insulation under distorted voltage, which belongs to the class of the popular Inverse Power Model. Thereafter, a novel approach is developed for building the prior distribution of the unknown life model parameters, described by a joint Normal distribution, that implies a Lognormal model for the hazard rate and the Mean Time To Failure. The applicability and efficiency of the proposed Bayesian methodology is checked by means of a broad amount of Monte Carlo simulations performed for the insulation of power capacitors and cables subjected to harmonic voltages. The results prove the satisfactory behavior of the Bayesian methodology especially for quite small samples; this is an important outcome, since – as well known in the case of real power systems - small samples are a common practical case.
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Keywords


Bayesian Methods; Gaussian Distribution; Insulation; Log-Normal Distribution; Power System Harmonics; Power System Reliability

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References


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