Reliability Prediction for GIL Equipment Based on Multilayer Directed and Weighted Network and Failure Propagation

• Published in: IEEE transactions on reliability 2020-12, Vol.69 (4), p.1207-1229
• Main Authors: Wang, Zhen, Wang, Rong-Xi, Gao, Jian-Min, Chen, Kun, Liang, Yan-Jie, Tang, Ze-Zhou
• Format: Article
• Language: English
• Subjects: Analytical models; Electric cables; Failure; Failure analysis; Failure modes; Failure propagation; Failure rates; gas insulated metal enclosed transmission line; multilayer directed and weighted network (M-LDAWN); Multilayers; Network reliability; Power cables; Power lines; Prediction models; Predictive models; Propagation; Reliability analysis; Reliability engineering; reliability prediction; Transmission lines
• ISSN: 0018-9529; 1558-1721
• DOI: 10.1109/TR.2019.2923761

As an effective alternative to the power cables and overhead lines in the electrical transmission networks, the gas-insulated metal enclosed transmission line (GIL) has been receiving ever-increasing usage worldwide. The GIL reliability, as one of the important characteristics of GIL equipment, is greatly determined by the processing technologies used in manufacturing, transportation, and installation stages, and failures caused by poor processing technologies can cause great damage to GIL equipment, which can further result in great losses to the electrified wire netting. Thus, it is necessary to study and accurately predict the reliability of GIL equipment to discover potential failure modes and take precautions before GIL equipment goes into operation. In this paper, a new reliability prediction model called the multilayer directed and weighted network (M-LDAWN) reliability prediction model is proposed to analyze and predict the GIL equipment reliability by concerning failure propagation and practical processing technologies. In the reliability prediction process, the reliability minimum cut sets triggered by substandard processing technologies are searched by the M-LDAWN model, and the increased failure rate of GIL equipment under each reliability minimum cut set is calculated considering the amplification and concatenation effects of failure propagation. Using the proposed reliability prediction model, the effects of substandard processing technologies on the GIL equipment reliability can be quantified, and the reliability fluctuation caused by them can be calculated. The effectiveness of the proposed framework is demonstrated on a practical GIL reliability prediction example.