Distribution System Reconfiguration for Loss Reduction Based on Ant Colony Behavior

The problem of reconfiguration of distribution systems to minimize power loss was formulated as an optimization problem. This formulation takes into account the operational constraints on line flows and voltages and the radial topology. To solve this problem, the authors propose a method to optimize this reconfiguration of the distribution system, based on the behavior of colonies of ants. To illustrate the proposed method, a numerical example is presented

[1]  Loi Lei Lai,et al.  Application of evolutionary programming to reactive power planning-comparison with nonlinear programming approach , 1997 .

[2]  A. Y. Chikhani,et al.  Feeder reconfiguration for loss reduction: an application of distribution automation , 1991 .

[3]  Y.-T. Hsiao,et al.  Multiobjective optimal feeder reconfiguration , 2001 .

[4]  Felix F. Wu,et al.  Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing , 1989, IEEE Power Engineering Review.

[5]  Hong-Chan Chang,et al.  Network reconfiguration in distribution systems using simulated annealing , 1994 .

[6]  Li Xing-yuan,et al.  Voltage Stability Analysis of Radial Distribution Networks , 2002 .

[7]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[8]  Ming-Tong Tsay,et al.  Distribution feeder reconfiguration with refined genetic algorithm , 2000 .

[9]  M. Kitagawa,et al.  Implementation of genetic algorithm for distribution systems loss minimum re-configuration , 1992 .

[10]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[11]  I. Drezga,et al.  A heuristic nonlinear constructive method for distribution system reconfiguration , 1999 .

[12]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[13]  J. J. Grainger,et al.  Distribution feeder reconfiguration for loss reduction , 1988 .

[14]  Ji-Pyng Chiou,et al.  Distribution network reconfiguration for loss reduction by ant colony search algorithm , 2005 .

[15]  R. Steele.  Optimization , 2005 .

[16]  P.-P. Grasse.  La reconstruction du nid et les coordinations interindividuelles chezBellicositermes natalensis etCubitermes sp. la théorie de la stigmergie: Essai d'interprétation du comportement des termites constructeurs , 1959, Insectes Sociaux.

[17]  Y.-Y. Hsu,et al.  Distribution system service restoration using a heuristic search approach , 1991 .