On Estimation of Equipment Failures in Electric Distribution Systems Using Bayesian Inference

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dc.contributor.authorPeerzada, Aaqib
dc.contributor.authorBegovic, Miroslav M.
dc.contributor.authorRohouma, Wesam
dc.contributor.authorBalog, Robert
dc.date.accessioned2020-12-24T19:38:29Z
dc.date.available2020-12-24T19:38:29Z
dc.date.issued2021-01-05
dc.description.abstractThis paper presents a new statistical parametric model to predict the times-to-failure of broad classes of identical devices such as on-load tap changers, switched capacitors, breakers, etc. A two-parameter Weibull distribution with scale parameter given by the inverse power law is employed to model the survivor functions and hazard rates of on-load tap changers. The resulting three-parameter distribution, referred to as IPL-Weibull, is flexible enough to assume right, left, and even symmetrical modal distribution. In this work, we propose an inferential method based on Bayes’ rule to derive the point estimates of model parameters from the past right-censored failure data. Using the Monte Carlo integration technique, it is possible to obtain such parameter estimates with high accuracy.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.381
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70996
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDistributed, Renewable, and Mobile Resources
dc.subjectasset management
dc.subjectbayesian parameter estimation
dc.subjectrenewable generation
dc.subjectweibull distribution
dc.titleOn Estimation of Equipment Failures in Electric Distribution Systems Using Bayesian Inference
prism.startingpage3131

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