DocumentCode
1144484
Title
A novel ACS-based optimum switch relocation method
Author
Teng, Jen-Hao ; Liu, Yi-Hwa
Author_Institution
Dept. of Electr. Eng., I-Shou Univ., Kaohsiung, Taiwan
Volume
18
Issue
1
fYear
2003
fDate
2/1/2003 12:00:00 AM
Firstpage
113
Lastpage
120
Abstract
In this paper, a cooperative agent algorithm, the ant colony system (ACS), for optimum switch relocation is proposed. Switch relocation is a useful tool for distribution automation, since it can reduce the interruption costs without additional capital investments. The formulation of switch relocation is a combinatorial optimization problem with nonlinear and nondifferential objective functions. In this paper, the authors choose the ACS to solve the problem since the ACS has the characteristics of positive feedback, distributed computation, and the use of a constructive greedy heuristic. One of the main goals of this paper is to investigate the applicability of the ACS-based algorithm in the power system optimization problems. Test results show that the proposed ACS-based algorithm can offer a near-optimum solution for switch relocation. The comparisons of the proposed method with a genetic-algorithm (GA)-based method are also shown in the test results to demonstrate the values of the proposed method.
Keywords
costing; evolutionary computation; optimisation; power distribution control; power distribution economics; power distribution faults; power distribution planning; power distribution reliability; switching; ant colony system; capital investments; combinatorial optimization problem; cooperative agent algorithm; customer interruption costs; distributed computation; distribution automation; genetic algorithm; nonlinear nondifferential objective functions; optimum switch relocation; Ant colony optimization; Automation; Costs; Distributed computing; Hydroelectric power generation; Job shop scheduling; Power system reliability; Power systems; Switches; Testing;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2002.807038
Filename
1178780
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