Please use this identifier to cite or link to this item: https://doi.org/10.1109/TPWRS.2008.922637
Title: Multiobjective evolutionary optimization of substation maintenance using decision-varying Markov model
Authors: Yang, F.
Kwan, C.M.
Chang, C.S. 
Keywords: Decision-varying Markov model
Minimum cut sets
Multiobjective evolutionary algorithm
Pareto front
Substation maintenance
Issue Date: 2008
Source: Yang, F., Kwan, C.M., Chang, C.S. (2008). Multiobjective evolutionary optimization of substation maintenance using decision-varying Markov model. IEEE Transactions on Power Systems 23 (3) : 1328-1335. ScholarBank@NUS Repository. https://doi.org/10.1109/TPWRS.2008.922637
Abstract: Reducing overall substation cost and improving reliability are the two prime but often conflicting objectives of electric power distribution. Proper scheduling of substation preventive maintenance provides an effective means to tradeoff between these two objectives. Decision-varying Markov models relating the deterioration process with maintenance operations is proposed to predict the availability of individual component. Minimum cut-sets method is employed to identify the critical components and evaluate the overall reliability of substation. A multiobjective evolutionary algorithm is proposed to optimize the two objectives to provide Pareto-fronts or tradeoff curves for a holistic view of the conflicting relationships between them. Through simulations, abilities of our proposed algorithm are demonstrated for robust search towards optimal solutions for large-size distribution. © 2008 IEEE.
Source Title: IEEE Transactions on Power Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/56718
ISSN: 08858950
DOI: 10.1109/TPWRS.2008.922637
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