Risk assessment of dynamic system cascading collapse for determining the sensitive transmission lines and severity of total loading conditions

Nur Ashida Salim, Muhammad Murtadha Othman, Ismail Musirin, Mohd Salleh Serwan and Stendley Busan

Reliability Engineering and System Safety, 2017, vol. 157, issue C, 113-128

Abstract: This paper presents a computationally accurate technique used to determine the estimated average probability of a dynamic system cascading collapse considering the effect of hidden failure on a protection system. This requires an accurate calculation of the probability of hidden failure as it will give significant effect on the results of the estimated average probability of dynamic system cascading collapse. The estimated average probability of a dynamic system cascading collapse is then used to determine the severe loading condition contributing to a higher risk of a system cascading collapse. This information of risk assessment is important to the utility that will assist them to determine the maximum level of increase in the system loading condition before a critical dynamic system cascading collapse is incurred. Furthermore, initial tripping of sensitive transmission line contributing to a dynamic critical system cascading collapse can also be determined by using the proposed risk assessment. Based on the results obtained from this study, it was found that selecting the accurate probability of hidden failure is very important as it will affect the estimated average probability of a dynamic system cascading collapse used for determining the results of sensitive transmission lines and severity of total loading conditions.

Keywords: Risk based dynamic system cascading collapse; Hidden failure of a protection system; Estimated average probability of a dynamic system cascading collapse; Sensitive transmission lines; Severity of total loading conditions (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:157:y:2017:i:c:p:113-128

DOI: 10.1016/j.ress.2016.08.002

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