Maximum loadability achievement in SWER networks using optimal sizing and locating of batteries

Arefi, Ali & Ledwich, Gerard (2013) Maximum loadability achievement in SWER networks using optimal sizing and locating of batteries. In Proceedings of the 2013 Australasian Universities Power Engineering Conference (AUPEC), IEEE, Hobart, Tasmania, Australia, pp. 1-6.

View at publisher


This paper presents an optimisation algorithm to maximize the loadability of single wire earth return (SWER) by minimizing the cost of batteries and regulators considering the voltage constraints and thermal limits. This algorithm, that finds the optimum location of batteries and regulators, uses hybrid discrete particle swarm optimization and mutation (DPSO + Mutation). The simulation results on realistic highly loaded SWER network show the effectiveness of using battery to improve the loadability of SWER network in a cost-effective way. In this case, while only 61% of peak load can be supplied without violating the constraints by existing network, the loadability of the network is increased to peak load by utilizing two battery sites which are located optimally. That is, in a SWER system like the studied one, each installed kVA of batteries, optimally located, supports a loadability increase as 2 kVA.

Impact and interest:

1 citations in Scopus
Search Google Scholar™

Citation counts are 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.

ID Code: 68673
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Loadabiity, Optimal sizing and locating, Battery regulator, SWER, DPSO, Mutation
DOI: 10.1109/AUPEC.2013.6725472
ISBN: 9781862959132
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
Deposited On: 18 Mar 2014 02:09
Last Modified: 19 Mar 2014 01:25

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page