Development of Transmission Line Failure Rate Model using Polynomial Regression

  • Abstract
  • Keywords
  • References
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  • Abstract

    Drastic climate change and more frequent occurrences of natural disaster which destruct power system infrastructure results in 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 transmission line outage has been carried out by numerous researcher. Generally, this risk study involves two major parts; one is the assessment of voltage collapse impact due to the line outage and the other is the assessment of probability of line outage to occur. According 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 technique. 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 proposed 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.


  • Keywords

    OLS; Polynomial model; probability estimation; transmission line outage; transmission line failure rate model.

  • References

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Article ID: 17508
DOI: 10.14419/ijet.v7i3.15.17508

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