DocumentCode :
25233
Title :
Reconfiguration of electrical networks by an Ant Colony Optimization algorithm
Author :
Scenna, F. ; Anaut, D. ; Passoni, L.I. ; Meschino, G.J.
Author_Institution :
Univ. Nac. de Mar del Plata (FI - UNMdP), Mar del Plata, Argentina
Volume :
11
Issue :
1
fYear :
2013
fDate :
Feb. 2013
Firstpage :
538
Lastpage :
544
Abstract :
Electricity distribution companies constantly require improvements in service, and an appropriate reduction in costs of the system. Finding the optimal configuration of the distribution network reduces power losses, which impacts directly on costs, also leading to significant energy savings. Over recent decades, the problem of network reconfiguration for loss minimization and for other purposes has been widely studied. The algorithms improve the previously obtained minimum power loss and also reduce computational times. This paper proposes the study and application of an algorithm based on Ant Colony Optimization, method covered in the paradigm of Swarm Intelligence, sub-discipline of Computational Intelligence. We show an easy network codification and we performed a detailed study of the ranges of values for the configuration parameters of the algorithm. We achieved the optimal result for testing networks and we found appropriate configurations for more complex networks, taking low computational times.
Keywords :
ant colony optimisation; distribution networks; ant colony optimization algorithm; distribution network reconfiguration; electrical network reconfiguration; electricity distribution company; loss minimization; power loss reduction; Abstracts; Ant colony optimization; Companies; Computational modeling; Electricity; Particle swarm optimization; Vectors; ant colony optimization; electrical networks; modeling; optimization; swarm intelligence;
fLanguage :
English
Journal_Title :
Latin America Transactions, IEEE (Revista IEEE America Latina)
Publisher :
ieee
ISSN :
1548-0992
Type :
jour
DOI :
10.1109/TLA.2013.6502858
Filename :
6502858
Link To Document :
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