Distribution systems reconfiguration using the hyper-cube ant colony optimization algorithm

  • Authors:

  • A. Y. Abdelaziz;Reham A. Osama;S. M. El-Khodary;Bijaya Ketan Panigrahi

  • Affiliations:

  • Department of Electrical Power & Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt;Department of Electrical Power & Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt;Department of Electrical Power & Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt;Department of Electrical Engineering, Indian Institute of Technology, Delhi, India

  • Venue:
  • SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part II
  • Year:
  • 2011

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Abstract

This paper introduces the Ant Colony Optimization algorithm (ACO) implemented in the Hyper-Cube (HC) framework to solve the distribution network minimum loss reconfiguration problem. The ACO is a relatively new and powerful intelligence evolution method inspired from natural behavior of real ant colonies for solving optimization problems. In contrast to the usual ways of implementing ACO algorithms, the HC framework limits the pheromone values by introducing changes in the pheromone updating rules resulting in a more robust and easier to implement version of the ACO procedure. The optimization problem is formulated taking into account the operational constraints of the distribution systems. Results of numerical tests carried out on two test systems from literature are presented to show the effectiveness of the proposed approach.