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A maintenance cost study of transformers based on markov model utilizing frequency of transition approach

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dc.citedby4
dc.contributor.authorYahaya M.S.en_US
dc.contributor.authorAzis N.en_US
dc.contributor.authorSelva A.M.en_US
dc.contributor.authorKadir M.Z.A.A.en_US
dc.contributor.authorJasni J.en_US
dc.contributor.authorKadim E.J.en_US
dc.contributor.authorHairi M.H.en_US
dc.contributor.authorGhazali Y.Z.Y.en_US
dc.contributor.authorid36083783000en_US
dc.contributor.authorid56120698200en_US
dc.contributor.authorid57203742582en_US
dc.contributor.authorid25947297000en_US
dc.contributor.authorid25632671500en_US
dc.contributor.authorid57188969063en_US
dc.contributor.authorid26422962100en_US
dc.contributor.authorid55336569600en_US
dc.date.accessioned2023-05-29T06:51:20Z
dc.date.available2023-05-29T06:51:20Z
dc.date.issued2018
dc.descriptionDeterioration; Electric transformers; Forecasting; Maintenance; Markov processes; Planning; Probability distributions; Frequency of transition; Health indices; Maintenance cost; Maintenance policy; Markov model; Prediction interval; Transition probabilities; Costsen_US
dc.description.abstractIn this paper, a maintenance cost study of transformers based on the Markov Model (MM) utilizing the Health Index (HI) is presented. In total, 120 distribution transformers of oil type (33/11 kV and 30 MVA) are examined. The HI is computed based on condition assessment data. Based on the HI, the transformers are arranged according to its corresponding states, and the transition probabilities are determined based on frequency of a transition approach utilizing the transformer transition states for the year 2013/2014 and 2012/2013. The future states of transformers are determined based on the MM chain algorithm. Finally, the maintenance costs are estimated based on future-state distribution probabilities according to the proposed maintenance policy model. The study shows that the deterioration states of the transformer population for the year 2015 can be predicted by MM based on the transformer transition states for the year 2013/2014 and 2012/2013. Analysis on the relationship between the predicted and actual computed numbers of transformers reveals that all transformer states are still within the 95% prediction interval. There is a 90% probability that the transformer population will reach State 1 after 76 years and 69 years based on the transformer transition states for the year 2013/2014 and 2012/2013. Based on the probability-state distributions, it is found that the total maintenance cost increases gradually from Ringgit Malaysia (RM) 5.94 million to RM 39.09 million based on transformer transition states for the year 2013/2014 and RM 37.56 million for the year 2012/2013 within the 20 years prediction interval, respectively. 2018 by the authors.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNoen11082006
dc.identifier.doi10.3390/en11082006
dc.identifier.issue8
dc.identifier.scopus2-s2.0-85052826144
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85052826144&doi=10.3390%2fen11082006&partnerID=40&md5=6168d6ef2992cfe9d7425011f015bc61
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23732
dc.identifier.volume11
dc.publisherMDPI AGen_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleEnergies
dc.titleA maintenance cost study of transformers based on markov model utilizing frequency of transition approachen_US
dc.typeArticleen_US
dspace.entity.typePublication
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