Generators maintenance scheduling using combined fuzzy set theory and GA

Author

Taegon Oh ; Jintaek Lim ; Jaeseok Choi ; Junmin Cha ; Bonhui Ku ; Ungki Baek

Author_Institution

Dept. of Electr. Eng., Gyeongsang Nat. Univ., Jinju, South Korea

fYear

2011

fDate

7-10 Aug. 2011

Firstpage

1

Lastpage

4

Abstract

The maintenance of generating units is implicitly related to power system reliability and has a tremendous bearing on the operation of the power system. A technique using a fuzzy search method which is based on fuzzy multi-criteria function has been proposed for GMS (generator maintenance scheduling) in order to consider multi-objective function. In this study, a new technique using combined fuzzy set theory and genetic algorithm(GA) is proposed for generator maintenance scheduling. The effectiveness of the proposed approach is demonstrated by the simulation results on a practical size test systems.

Keywords

fuzzy set theory; genetic algorithms; maintenance engineering; power generation reliability; power generation scheduling; power system management; GA; GMS; fuzzy multicriteria function; fuzzy search method; fuzzy set theory; generating units; generators maintenance scheduling; genetic algorithm; multiobjective function; power system reliability; practical size test systems; Generators; Next generation networking; Planning; Reliability;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems (MWSCAS), 2011 IEEE 54th International Midwest Symposium on

Conference_Location

Seoul

ISSN

1548-3746

Print_ISBN

978-1-61284-856-3

Electronic_ISBN

1548-3746

Type

conf

DOI

10.1109/MWSCAS.2011.6026447

Filename

6026447