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Published in:
2016 | OriginalPaper | Chapter
Reliability Modelling for Electricity Transmission Networks Using Maintenance Records
Authors : Fengfeng Li, Michael E. Cholette, Lin Ma
Published in: Proceedings of the 10th World Congress on Engineering Asset Management (WCEAM 2015)
Publisher: Springer International Publishing
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Abstract
Maintenance decisions for transmission network assets (TNAs) require accurate reliability prediction. However, there are a large number of operating, design and environmental variables that potentially influence their reliability. This paper presents a new reliability prediction method for TNAs. Failure times were identified by extracting significant unplanned maintenance events for critical failure modes. A regression tree-based grouping analysis was utilized to analyse the influences by variety of factors on future unplanned maintenance. These results were then used to build the reliability prediction model allowing a decision maker to have an estimate of future unplanned maintenance requirements. A case study using real industry data was conducted to test the proposed reliability prediction model. The results demonstrate the feasibility of using this approach for TNA maintenance decision support.