Combined genetic algorithm and simulated annealing for preventive unit maintenance scheduling in power system

Author

Suresh, K. ; Kumarappan, N.

Author_Institution

Dept. of Electr. Eng., Arasu Eng. Coll.

fYear

0

fDate

0-0 0

Abstract

The provision of un-interrupted power supply for all customers has always been one of the fundamental concern of maintenance scheduling. The maintenance scheduling (MS) is characterized as a constrained optimization problem. Combined genetic algorithm and simulated annealing (CGASA) are proposed in this paper for reliable preventive unit maintenance scheduling (PUMS). This approach is used to find the timetable of scheduled maintenance outages in power system. It is observed that the proposed method is more reliable and gives better quality of solution with improved search performance. It is tested on 62 unit state electricity system of Victoria

Keywords

genetic algorithms; power system economics; preventive maintenance; scheduling; simulated annealing; uninterruptible power supplies; Victoria; constrained optimization problem; genetic algorithm; preventive unit maintenance scheduling; simulated annealing; state electricity system; uninterrupted power supply; Genetic algorithms; Power generation; Power generation economics; Power system economics; Power system planning; Power system reliability; Power system simulation; Preventive maintenance; Simulated annealing; Temperature;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society General Meeting, 2006. IEEE

Conference_Location

Montreal, Que.

Print_ISBN

1-4244-0493-2

Type

conf

DOI

10.1109/PES.2006.1709254

Filename

1709254