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.
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Abdelaziz, A.Y., Osama, R.A., El-Khodary, S.M., Panigrahi, B.K. (2011). Distribution Systems Reconfiguration Using the Hyper-Cube Ant Colony Optimization Algorithm. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27242-4_30
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DOI: https://doi.org/10.1007/978-3-642-27242-4_30
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