JACIII Vol.17 No.5 pp. 681-689
doi: 10.20965/jaciii.2013.p0681


Improving the Search Ability of Tabu Search in the Distribution Network Reconfiguration Problem

Hirotaka Takano*, Junichi Murata*, Yukino Maki**,
and Makoto Yasuda**

*Faculty of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka-shi, Fukuoka 819-0395, Japan

**Department of Electrical and Information Engineering, Gifu National College of Technology, 2236-2 Kamimakuwa, Motosu-shi, Gifu 501-0495, Japan

March 19, 2013
May 20, 2013
September 20, 2013
distribution network reconfiguration, distribution loss minimization, metaheuristics, tabu search (TS), combinatorial optimization problem
The distribution network reconfiguration problem is to decide whether each sectionalizing switch is to be open or closed in order to maintain or improve electrical power supply reliability, power quality and network operation efficiency. Obtaining the optimal network configuration is, however, extremely difficult because the network reconfiguration problem is actually a large-size combinatorial optimization problem. Many optimization algorithms have thus been applied to the reconfiguration problem to support power utility’s decision-making. This paper proposes a local search-based solution for the reconfiguration problem in which tabu search – one of the most widely used local search-based metaheuristics – is employed to solve the problem. Tabu search is improved by introducing an effective search strategy that utilizes the properties of this kind of problems. Numerical simulations are performed on a complex actual-scale distribution network model in order to verify the validity of the proposed solution.
Cite this article as:
H. Takano, J. Murata, Y. Maki, and M. Yasuda, “Improving the Search Ability of Tabu Search in the Distribution Network Reconfiguration Problem,” J. Adv. Comput. Intell. Intell. Inform., Vol.17 No.5, pp. 681-689, 2013.
Data files:
  1. [1] C. C. Liu, S. J. Lee, and S. S. Venkata, “An Expert System Operational Aid for Restoration and Loss Reduction of Distribution Systems,” IEEE Trans. of Power Systems, Vol.3, pp. 619-626, 1988.
  2. [2] K. Nara et al., “Implementation of Genetic Algorithm for Distribution Systems Loss Minimum Re-configuration,” IEEE Trans. of Power Syst., Vol.7, No.3, pp. 1044-1050, 1992.
  3. [3] R. Taleski and D. Rajicic, “Distribution network reconfiguration for energy loss reduction,” IEEE Trans. of Power Syst., Vol.12, No.1, pp. 398-406, 1997.
  4. [4] V. Parad et al., “Optimization of Electrical Distribution Feeders Using Simulated Annealing,” IEEE Trans. of Power Delivery, Vol.19, No.3, pp. 1135-1141, 2003.
  5. [5] A. C. B. Delbem, A. C. Pd. L. F. de Carvalho, and N. G. Bretas, “Main chain representation for evolutionary algorithms applied to distribution system reconfiguration,” IEEE Trans. of Power Syst., Vol.20, No.1, pp. 425-436, 2005.
  6. [6] H. Takano et al., “A Study on Improvement of Tabu Search-based Determination Method for Distribution Network Configuration,” JICEE, Vol.3, No.1, pp. 61-67, 2013.
  7. [7] Y. Hayashi et al., “Determination Method of for Loss-Minimum Configuration of Three Sectionalized Three Connected Distribution Network,” IEEJ Trans. of PE, Vol.126-B, No.2, pp. 516-524, 2006 (in Japanese).
  8. [8] H. Takano et al., “Effective Enumeration Method to Determine Loss Minimum Distribution Network Configuration,” Proc. of ICEE2006, SE2-02, 001-000307, 2006.
  9. [9] H. Takano et al., “Determination Method for Loss-Minimum Configuration Considering Reconnection of Distributed Generatos,” Electrical Engineering in Japan (Wiley InterScience), Vol.176, Iss.4, pp. 7-14, 2011.
  10. [10] H. Mori and Y. Fukuyama, “Intelligent Systems in Power Systems: Meta-heuristics Methods,” IEEJ Trans. PE, Vol.121-B, No.7, pp. 450-457, 2001 (in Japanese).
  11. [11] H. Mori, “Recent Trends on Applications of Meta-heuristics in Power Systems,” IEEJ Trans. of PE, Vol.123-B, No.10, pp. 1120-1123, 2003 (in Japanese).
  12. [12] Y. Fukuyama, “Applications of Meta-heuristics to Power and Energy Fields,” IEEJ Trans. of PE, Vol.124-B, No.5, pp. 679-682, 2004 (in Japanese).
  13. [13] F. Glover, “Tabu Search, Part I,” ORSA J. on Computing, Vol.1, No.3, pp. 190-206, 1989.
  14. [14] Y. Hayashi et al., “Establishment of a Standard Analytical Model of Distribution Network with Distributed Generators and Development of Multi Evaluation Method for Network Configuration Candidates,” IEEJ Trans. of PE, Vol.126-B, No.10, pp. 1013-1022, 2006(in Japanese).
  15. [15] Y.Hayashi et al., “A Simple Evaluation Method for Annual CO2 Emissions Reduced by Distribution Loss Minimization,” IEEJ Trans. PE, Vol.127-B, No.11, pp. 1137-1144, 2007 (in Japanese).
  16. [16] K. Yasuda, “Proximate Optimality Principle Base Tabu Search,” Proc. of IEEE Int. Conf. on Systems, Man and Cybernetics 2003, Vol.2, pp. 1560-1565, 2003.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jul. 19, 2024