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

Vahidnia, Arash, Ledwich, Gerard, Ghosh, Arindam, & Palmer, Edward (2011) An improved genetic algorithm and graph theory based method for optimal sectionalizer switch placement in distribution networks with DG. In Ledwich, Gerard & Ghosh, Arindam (Eds.) Proceedings of AUPEC 2011: Integrating Renewables into the Grid, AUPEC/IEEE, Queensland University of Technology, Brisbane, QLD, pp. 1-7.

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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.

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ID Code: 46704
Item Type: Conference Paper
Refereed: Yes
Additional Information: All the presented papers will be made available in the IEEE Xplore Digital Library
Keywords: Distributed Generation (DG), Distribution Networks, Genetic Algorithm (GA), Reliability, Spanning Tree
ISBN: 978-1-921897-07-8
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Power and Energy Systems Engineering (excl. Renewable Power) (090607)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2011 AIPEC/IEEE
Deposited On: 30 Oct 2011 23:02
Last Modified: 27 Jun 2017 09:32

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