Failure rate analysis and prediction for switchgears in power systems

Abstract

Electricity demand has been on an upward trend in recent years. Switchgears are becoming ever more relied upon by businesses and consumers. Power systems are crucial in generating and distributing electricity. Switchgears in power systems play an important role by protecting, controlling and isolating electrical equipment. A failure in a switchgear would negatively impact the whole power grid, which may lead to serious losses in businesses and in essential services. If we are able to determine an effective method to predict switchgear faults and take preventive maintenance before switchgear faults occur, the probability of switchgear faults can be reduced to a large extent. In addition, preventive maintenance can also extend the lifetime of switchgears, leading to lower costs in the long run. This final year project report will explain the background of predicting switchgear faults, analyse simulated data using statistical modeling and using tests to compare the models and fit. The language used will be Python Programming in a Jupyter notebook environment. Survival analysis using Weibull distribution and estimating time-to-failure using Kaplan-Meier will also be implemented in this project.