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Distribution networks reconfiguration (DNR) is the process of changing the topology of distribution systems by altering the open/closed status of switches to transfer loads among the feeders. One objective of the feeder reconfiguration of distribution systems is to minimize the total power losses for a specific load. This book adopts two new efficient heuristic techniques for reconfiguration of electrical distribution systems; the real ants'-behavior-inspired Ant Colony Optimization (ACO) algorithm implemented in the Hyper Cube (HC) framework and the musicians'-behavior-inspired Harmony Search…mehr

Produktbeschreibung
Distribution networks reconfiguration (DNR) is the process of changing the topology of distribution systems by altering the open/closed status of switches to transfer loads among the feeders. One objective of the feeder reconfiguration of distribution systems is to minimize the total power losses for a specific load. This book adopts two new efficient heuristic techniques for reconfiguration of electrical distribution systems; the real ants'-behavior-inspired Ant Colony Optimization (ACO) algorithm implemented in the Hyper Cube (HC) framework and the musicians'-behavior-inspired Harmony Search (HS) algorithm. To verify the effectiveness of the proposed algorithms, comparative studies are conducted on three test systems with encouraging results. The obtained results are compared with the results of other purely heuristic and AI-based approaches from literature to examine the performance. This book also emphasis the advantages of Insertion of Distributed Generation units (DGs) to the electrical distribution networks and the advantages of reconfiguration in presence of DGs on the total power loss reduction and bus voltage improvement.
Autorenporträt
Reham A. Osama received her B.Sc. and M.Sc. degrees in electrical engineering from Faculty of Engineering, Ain Shams University, Egypt in 2008 and 2012 respectively. She is currently a teaching assistant of electric engineering in Ain Shams University. Her research interests include the application of new optimization techniques to power systems.