Optimizing preventive maintenance of substation components using Monte Carlo

In this paper, a population of substation components is considered for preventive maintenance prior to which they were only repaired upon failure. Monte Carlo simulation technique is used to study and compare three different operation and maintenance scenarios. In the first scenario it is assumed that no maintenance takes places and components are repaired upon failure. In the second scenario it is assumed that maintenance is carried out after specific intervals. In the third scenario it is assumed that maintenance is carried out only once. Statistical analysis of these three scenarios is performed over thirty years to identify the most feasible scenario that can be used to operate and maintain the substation components. Optimum maintenance interval for the given system is also recommended based on the ratio of mean cost of maintenance and mean cost of repair. It is also demonstrated that an important effect of preventive maintenance is an increase in the meantime to failure (MMTF). In the case of ideal repair, this translates into the finding that, for components with an increasing hazard function, regular performance of maintenance reduces the frequency of repairs. To examine this hypothesis quantitatively, we assume that maintenance intervals T_M are fixed and maintenance is ideal and perfect.