Reliability Evaluation of 10kV XLPE Cable Based on Fault Correlation Bayesian Network and Weibull Distribution Model

With the expanding application of 10 kV XLPE cables in power distribution, types of cables are produced by different manufacturers with various quality risks. The daily sampling inspection methods of cables can help discover and eliminate hidden dangers of cable failures. However, regular sampling inspection methods that ignore individual risk differences will lead to a waste of manpower and resources. To ensure the reliable operation of cables and increase economic benefits, an optimization method is proposed for 10 kV XLPE cable sampling in this work. In this paper, the order of supply quality of the qualified suppliers is achieved in combination with the mathematical statistics method. The parameters $\beta$ and $\eta$ that represent the quality of the cable are developed from the data selected from four qualified suppliers. The parameters $\beta$ and $\eta$ of the model can be estimated through Bayes inference by combining 10 kV cable related prior information with operational and failure data. The results of applying in-service 10 kV cables show that the proposed method can be used to analyze the reliability of 10 kV cables and can make full use of limited data and prior information to give relatively more accurate results. This result can provide a valid reference for the sampling of 10 kV XLPE cable.