Please use this identifier to cite or link to this item: https://doi.org/10.1109/ISAP.2007.4441597
Title: Evolutionary multi-objective optimization of substation maintenance using Markov model
Authors: Chang, C.S. 
Yang, F.
Keywords: Dynamic markov model
Minimum cut sets
Multi-objective evolutionary algorithms
Pareto front
Issue Date: 2007
Source: Chang, C.S.,Yang, F. (2007). Evolutionary multi-objective optimization of substation maintenance using Markov model. 2007 International Conference on Intelligent Systems Applications to Power Systems, ISAP : -. ScholarBank@NUS Repository. https://doi.org/10.1109/ISAP.2007.4441597
Abstract: Improving the reliability and reducing the overall cost are two important but often conflicting objectives for substations. Proper scheduling of preventive maintenance provides an effective means to tradeoff between the two objectives. In this paper, Pareto-based multi-objective evolutionary algorithms are proposed to optimize the maintenance activities because of their abilities of robust search towards best-compromise solutions for large-size optimization problems. Markov model is proposed to predict the deterioration process, maintenance operations, and availability of individual components. Minimum cut sets method is employed to identify the critical components by evaluating the overall reliability of interconnected systems. Pareto-fronts are generated for comparisons with other substation configurations. Results for four different substation configurations are presented to demonstrate potentials of the proposed approach for handling more complicated configurations.
Source Title: 2007 International Conference on Intelligent Systems Applications to Power Systems, ISAP
URI: http://scholarbank.nus.edu.sg/handle/10635/70223
ISBN: 9860130868
DOI: 10.1109/ISAP.2007.4441597
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