RCM scheduling optimization for circuit breakers based on LS-SVM

Optimization of circuit breakers (CBs) maintenance schedule based on RCM can enhance substation reliability and lower maintenance cost. In this paper, a RCM approach based on Least Squares Support Vector Machines (LS-SVM) is proposed. Historical operation data are utilized to build a defects tree. A bi-level optimization algorithm is used to choose LS-SVM parameters. The LS-SVM algorithm is used to predict the distribution of defects before and after scheme optimization using aggregated defect data, outage duration, maintenance operation defect detection rate, etc. After the defect loss is quantified based on an expert scoring method and the Gross Domestic Product to power consumption ratio, a cost effect measurement is used to determine the best scheme. The effect of the proposed approach is verified using a numerical simulation of an electric power corporation.