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. (In Press)
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.
Citations:
Citation countsare sourced monthly from Scopus and Web of Science citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.
Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads:
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
| ID Code: | 46704 |
|---|---|
| Item Type: | Conference Paper |
| 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: | 31 Oct 2011 09:02 |
| Last Modified: | 19 Jan 2012 23:00 |
Export: EndNote | Dublin Core | BibTeX
Repository Staff Only: item control page