Multiobjective evolutionary optimization of substation maintenance using decision-varying Markov model

被引：43
|
作者：
Yang, F. [1 ]
Kwan, Chung Min [1 ]
Chang, C. S. [1 ]
机构：
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117548, Singapore
来源：
IEEE TRANSACTIONS ON POWER SYSTEMS | 2008年 / 23卷 / 03期
关键词：
decision-varying Markov model; minimum cut sets; multiobjective evolutionary algorithm; pareto front; substation maintenance;
D O I：
10.1109/TPWRS.2008.922637
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：1328 / 1335
页数：8
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