Ant Colony Optimization and Harmony Search algorithms for distribution networks reconfiguration

This paper proposes two Bio-inspired heuristic algorithms to solve the power distribution network reconfiguration problem for loss minimization, "real ants\´-behavior-inspired" Ant Colony Optimization ACO implemented in the Hyper Cube HC framework and "musicians\´-behavior-inspired" Harmony Search IIS algorithm. The optimization problem is formulated taking into account the operational constraints of distribution systems. A 32-bus and 118-bus distribution systems were selected for optimizing the configuration where both algorithms yield the optimum configuration with minimum power loss for each case study. However, the HS required shorter simulation time but more practice of the iterative process than the HC-ACO. Implementing the ACO in the HC framework resulted in a more robust and easier handling of pheromone trails than the standard ACO.