Title :
Maximum loadability achievement in SWER networks using optimal sizing and locating of batteries
Author :
Arefi, Ali ; Ledwich, Gerard
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Queensland Univ. of Technol., Brisbane, QLD, Australia
fDate :
Sept. 29 2013-Oct. 3 2013
Abstract :
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.
Keywords :
battery storage plants; distributed power generation; earthing; particle swarm optimisation; voltage regulators; DPSO + Mutation; SWER networks; apparent power 2 kVA; discrete particle swarm optimization and mutation; maximum loadability; optimal sizing and locating; optimisation algorithm; single wire earth return; Australia; Batteries; Educational institutions; Optimization; Regulators; Standards; Voltage control; DPSO; Loadability; SWER; battery; mutation; optimal sizing and locating; regulator;
Conference_Titel :
Power Engineering Conference (AUPEC), 2013 Australasian Universities
Conference_Location :
Hobart, TAS
DOI :
10.1109/AUPEC.2013.6725472