Development of transmission line failure rate model using polynomial regression

M. K.N. Arshad, N. Aminudin, M. Marsadek, S. Z.M. Noor, R. H. Salimin, D. Johari

Research output: Contribution to journalArticle

Abstract

Drastic 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.

Original languageEnglish
Pages (from-to)91-94
Number of pages4
JournalInternational Journal of Engineering and Technology(UAE)
Volume7
Issue number3
DOIs
Publication statusPublished - 01 Jan 2018

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Computer Science (miscellaneous)
  • Environmental Engineering
  • Chemical Engineering(all)
  • Engineering(all)
  • Hardware and Architecture

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