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Development of transmission line failure rate model using polynomial regression

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dc.contributor.authorArshad M.K.N.en_US
dc.contributor.authorAminudin N.en_US
dc.contributor.authorMarsadek M.en_US
dc.contributor.authorNoor S.Z.M.en_US
dc.contributor.authorSalimin R.H.en_US
dc.contributor.authorJohari D.en_US
dc.contributor.authorid57215913768en_US
dc.contributor.authorid24733969500en_US
dc.contributor.authorid26423183000en_US
dc.contributor.authorid16022920600en_US
dc.contributor.authorid25928749500en_US
dc.contributor.authorid24733632200en_US
dc.date.accessioned2023-05-29T06:53:30Z
dc.date.available2023-05-29T06:53:30Z
dc.date.issued2018
dc.description.abstractDrastic climate change and more frequent occurrences of natural disaster which destruct power system infrastructure results i n power delivery congestion at the transmission network. Heavily loaded transmission network that operates during adverse weather is very prone to outage, hence may trigger more critical problem such as voltage collapse. Research on risk of voltage collapse due to tran smission line outage has been carried out by numerous researcher. Generally, this risk study involves two major parts; one is the assessmen t of voltage collapse impact due to the line outage and the other is the assessment of probability of line outage to occur. Acco rding to many literatures, precise probability estimation is very difficult to be evaluated since it is very unpredictable. Therefore, serious attention and studies have been focused in estimating the probability of transmission line outage prudently. The accuracy of probability assessed using Poisson distribution is very much dependent on its failure rate value. In this research, a weather -based transmission line failure rate model is developed using Ordinary Least Square (OLS) polynomial regression techni que. To evaluate the effectiveness of the proposed method, comparative study with previous research which utilized robust MM -estimator technique is conducted. The results revealed that the pr oposed technique is more precise and the weather considered in the study has more significant impact compared to the preceding work. Thus, this finding contributes to more accurate probability estimation in risk of voltage collapse assessment. � 2018 Authors.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.14419/ijet.v7i3.15.17508
dc.identifier.epage94
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85082343903
dc.identifier.spage91
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85082343903&doi=10.14419%2fijet.v7i3.15.17508&partnerID=40&md5=12635e91248c01e8787186cb958a1201
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23955
dc.identifier.volume7
dc.publisherScience Publishing Corporation Incen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleInternational Journal of Engineering and Technology(UAE)
dc.titleDevelopment of transmission line failure rate model using polynomial regressionen_US
dc.typeArticleen_US
dspace.entity.typePublication
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