A holistic approach to risk based maintenance scheduling for HV cables

Yanqun Liao, Haikang Liu, Jing Yuan, Yang Xu, Wenjun Zhou, Chengke Zhou

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Abstract

Regular maintenance inspection and testing is essential in extending cable life and reducing failure probability. This can be achieved by improving the conduit conditions and taking corrective actions on faulty cable components and accessories. Regulators and corporate governance among power utilities require the implementation of risk-based approaches to asset management. However, practitioners lack sufficient historical event data and knowledge that allow them to determine the failure probability of individual cable components, which is an essential component for risk assessment, due to that the high voltage (HV) cable population are relatively young, and many have not yet reached the end of their design life. This paper presents a novel holistic approach to allow the risk based maintenance strategy to be conveniently implemented for the cable conduit, cable terminations, joints, main bodies and the earthing systems separately for each cable circuit. Contributions include: (i) a failure frequency model which accounts for every past failure record of individual cable circuit components to approximate the probability of failure. This, when multiplying with the cable importance or failure consequence, yields the risk level of an individual cable component or a cable circuit; and (ii) a method of optimally scheduling the maintenance activities by setting the objective functions as the minimal cable system risk. The benefit of the simple failure frequency model has the advantage of not having to depend on human intervention and it does not need a large sample to generate valid results, as is the case with other statistical methods. Results of applying the proposed maintenance scheduling model to 21 selected High Voltage (HV) cable circuits show that the average risk can be significantly reduced while continuing with the same number of inspections and test operations.
Original languageEnglish
Pages (from-to)118975-118985
Number of pages11
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 20 Aug 2019

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