Model for predicting industrial circuit breaker failure tendencies in Uganda

Abstract

The requirement for better asset management frameworks has been a top priority for Uganda's industrial consumers. Poor asset management makes industrial customers more prone to faults, which lowers the quality of the power delivered. This study was carried out in response to the fact that industrial customers in the Kawempe Industrial Area have seen a sharp rise in cascaded failures in connected systems. This has occurred as a result of, among other things, the overuse of Circuit Breakers (CBs) and relays that are subpar, the failure of CB components, environmental factors affecting CB efficiency for instance; temperature and dust as well as carelessness in the conduct of compliance testing. Additionally, existing maintenance policies have been reactive as opposed to predictive, thus necessitating need to develop a prediction model for assessing CB degradation and advising on appropriate replacement time. In an effort to pinpoint the greatest risks that jeopardize the reliability of industrial CBs and establish the right timing for replacement, prediction modeling was done on 175 (2-4 pole) CBs in the Kawempe industrial area. Multi Stage sampling was used due to need to classify consumers based on feeders, CB types per consumer, and failure characteristics per CB. Since CBs are essential to system reliability and account for a sizable percentage of maintenance expenses for utilities, this research concentrated on them. Maximum Likelihood Estimation was used for parametization and Weibull modeling in MATLAB 2018 to investigate the effect of CB degradation on its Remaining Useful Life as well as advising on appropriate replacement time of CBs; findings generally indicated a maximum average hazard rate value of 11% and a mean time-to-failure of 13.47 years for all industrial CBs. Findings also showed that most industrial CBs where in critical condition demonstrating a high propensity to death. This was demonstrated by the increasing CB degradation as RUL kept reducing. Earlier replacement was also necessary due to high costs of industrial CB failure. CBs studied required replacement after 17.15 and 33.3 years of operation. More sophisticated breakers such as MCCBs and ACBs exhibited higher cost functions thus requiring earlier time of replacement. The results of this study recommend that industrialists should consider interoperability of protection system components in reliability assessment. Additionally, stakeholders such as manufacturers should consider reliability performance metrics when establishing condition-based monitoring and prediction systems. Based on findings, it is recommended that predictive maintenance policies should be adopted among industrial consumers when determining CB replacement time.