Optimal scheduling of load tap changer and switched shunt capacitors in smart grid with electric vehicles and charging stations

Author

Deilami, Sara ; Masoum, Ali S. ; Jabalameli, Nasim ; Masoum, Mohammad A. S.

Author_Institution

Dept. of Electr. & Comput. Eng., Curtin Univ., Perth, WA, Australia

fYear

2013

fDate

28-30 Nov. 2013

Firstpage

162

Lastpage

166

Abstract

Random charging of plug-in electric vehicles (PEVs) particularly during the peak load hours could impairment the performance of future smart grids. This paper presents genetic algorithms (GAs) for optimal scheduling of LTC and switched shunt capacitors (SSCs) to improve the performance of smart grid with PEV charging at consumer premises in residential feeders and PEV charging stations (PEV-CSs) in distribution networks. The forecasted daily load curves associated with PEV-CSs and residential feeders populated with PEVs are first generated and then incorporated in the GA-based optimal LTC and SSC scheduling solution. Simulation results without and with optimal scheduling are presented for a 449 node smart grid system with 5 PEV-CSs considering random and coordinated charging of 264 PEVs in 22 low voltage residential networks.

Keywords

battery powered vehicles; genetic algorithms; scheduling; secondary cells; smart power grids; LTC; PEV charging stations; SSC scheduling solution; genetic algorithms; load tap changer optimal scheduling; plug-in electric vehicles; residential feeders; smart grid system; switched shunt capacitors; Capacitors; Genetic algorithms; Loading; Optimal scheduling; Smart grids; Switches; Vehicles; LTC; Smart grid; charging stations; coordinated charging; optimal dispatch and GA; plug-in electric vehicle;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Electronics Engineering (ELECO), 2013 8th International Conference on

Conference_Location

Bursa

Print_ISBN

978-605-01-0504-9

Type

conf

DOI

10.1109/ELECO.2013.6713824

Filename

6713824