An improved genetic algorithm and graph theory based method for optimal sectionalizer switch placement in distribution networks with DG

Vahidnia, A, Ledwich, G, Ghosh, A and Palmer, E 2011, 'An improved genetic algorithm and graph theory based method for optimal sectionalizer switch placement in distribution networks with DG', in Proceedings of the 21st Australasian Universities Power Engineering Conference (AUPEC 2011), Brisbane, Australia, 25 -28 September 2011, pp. 1-7.


Document type: Conference Paper
Collection: Conference Papers

Title An improved genetic algorithm and graph theory based method for optimal sectionalizer switch placement in distribution networks with DG
Author(s) Vahidnia, A
Ledwich, G
Ghosh, A
Palmer, E
Year 2011
Conference name AUPEC 2011
Conference location Brisbane, Australia
Conference dates 25 -28 September 2011
Proceedings title Proceedings of the 21st Australasian Universities Power Engineering Conference (AUPEC 2011)
Publisher IEEE
Place of publication United States
Start page 1
End page 7
Total pages 7
Abstract In this paper a new graph-theory and improved genetic algorithm based practical method is employed to solve the optimal sectionalizer switch placement problem. The proposed method determines the best locations of sectionalizer switching devices in distribution networks considering the effects of presence of distributed generation (DG) in fitness functions and other optimization constraints, providing the maximum number of costumers to be supplied by distributed generation sources in islanded distribution systems after possible faults. The proposed method is simulated and tested on several distribution test systems in both cases of with DG and non DG situations. The results of the simulations validate the proposed method for switch placement of the distribution network in the presence of distributed generation.
Subjects Power and Energy Systems Engineering (excl. Renewable Power)
Keyword(s) Distributed Generation (DG)
Distribution Networks
Genetic Algorithm (GA)
Reliability
Spanning Tree
Copyright notice © 2011 IEEE
ISBN 9781457717932
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