Abstract
• Maintenance effect is evaluated based on historical data and statistical data. • LS-SVM method is used to predict defects before and after optimization. • Defects are correlated to power loss in capital means. • Capital means is used as constraints whether the optimization is cost-effective. • Evaluate function and constraint function are proposed. An optimized maintenance schedule for circuit breakers (CBs) can enhance substation reliability and lower maintenance cost. In this paper, a Least Squares Support Vector Machines (LS-SVM) based CB maintenance scheduling optimization approach that considers constraint of cost effect 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.
Published Version
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