• 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