Title :
A network controlled load management scheme for domestic charging of electric vehicles
Author :
Khan, Reduan H. ; Studli, S. ; Khan, Jamil Y.
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Callaghan, NSW, Australia
fDate :
Sept. 29 2013-Oct. 3 2013
Abstract :
This paper proposes a end-to-end load management scheme for domestic charging of electric vehicles (EVs) based on the bidirectional communication capabilities of the smart grid. In particular, the paper considers the case of using EV fleets for night-time valley-filling of the daily load curve. The novel concept of discontinuous EV charging based on small energy bursts is introduced that utilizes the benefit of the statistical multiplexing to accommodate higher number of vehicles and to provide differentiated energy supply against a variable energy-budget within a pre-defined time. The paper also suggests two energy scheduling algorithms to ensure priority and/or fairness among the contending vehicles. A wide-area smart grid communications network based on WiMAX technology has been used as a proof of concept for this study. Simulations are conducted using an integrated OPNET model to jointly examine the performances of the energy scheduling algorithms and the communications network for a large-scale EV charging system. The results show that the proposed scheme can efficiently support the EV charging load in an equitable manner with a very low communications overhead.
Keywords :
WiMax; battery powered vehicles; load management; power engineering computing; power generation scheduling; smart power grids; OPNET model; WiMAX technology; bidirectional communication; differentiated energy supply; discontinuous EV charging; domestic charging; electric vehicles; end to end load management scheme; energy scheduling algorithms; large scale EV charging system; network controlled load management scheme; statistical multiplexing; variable energy budget; wide-area smart grid communications network; Batteries; Communication networks; Load management; Resource management; Scheduling algorithms; System-on-chip; Vehicles;
Conference_Titel :
Power Engineering Conference (AUPEC), 2013 Australasian Universities
Conference_Location :
Hobart, TAS
DOI :
10.1109/AUPEC.2013.6725361