DocumentCode :
676758
Title :
Study on electric vehicles cluster model considering load response of power grid
Author :
Xiaolei Yu ; Haifeng Liang ; Lijie Yu ; Keyue Liu ; Bei Zheng
Author_Institution :
State Key Lab. of Alternate Electr. Power Syst. with Renewable Energy Sources, North China Electr. Power Univ., Baoding, China
fYear :
2013
fDate :
22-25 Oct. 2013
Firstpage :
1
Lastpage :
5
Abstract :
Large scale of electric vehicles integration will pose inevitable impacts on the planning and operation of power system in the future. Considering electric vehicles as movable and distributed storage units, a cluster model, in which the electric vehicles participate load response of power grid, is built. In this paper, coordinated charging modes and charging time of different kinds of EVs are proposed. The Monte Carlo simulation is applied to determine the starting state of charge(SOC) and the initial charging time, etc. Taking the daily load curve in a certain day for example, the impacts of power demand of EVs in different scales on original load curve are calculated. The results show that the natural charging-discharging characteristic of EVs can be controlled to discharge during the peak load time and charge during the load valley.
Keywords :
Monte Carlo methods; battery powered vehicles; load (electric); power grids; Monte Carlo simulation; coordinated charging modes; distributed storage units; electric vehicles cluster model; electric vehicles integration; initial charging time; load response; natural charging-discharging characteristic; peak load time; power grid; power system operation; power system planning; state of charge; Batteries; Electric vehicles; Gaussian distribution; Load modeling; Power systems; System-on-chip; Monte Carlo; cluster model; electric vehicles; load response;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2013 - 2013 IEEE Region 10 Conference (31194)
Conference_Location :
Xi´an
ISSN :
2159-3442
Print_ISBN :
978-1-4799-2825-5
Type :
conf
DOI :
10.1109/TENCON.2013.6718983
Filename :
6718983
Link To Document :
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