DocumentCode :
2888915
Title :
EV charging algorithm implementation with user price preference
Author :
Bin Wang ; Boyang Hu ; Qiu, Charlie ; Chu, Peter ; Gadh, Rajit
Author_Institution :
Dept. of Mech. Eng., Univ. of California, Los Angeles, Los Angeles, CA, USA
fYear :
2015
fDate :
18-20 Feb. 2015
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, we propose and implement a smart Electric Vehicle (EV) charging algorithm to control the EV charging infrastructures according to users´ price preferences. Charging boxes, equipped with bi-directional communication devices and smart meters, can be remotely monitored by the proposed charging algorithm applied to EV control center and mobile app. On the server side, ARIMA model is utilized to fit historical charging load data and perform day-ahead prediction. A pricing strategy with energy bidding policy is proposed and implemented to generate a charging price list to be broadcasted to EV users through mobile app. On the user side, EV drivers can submit their price preferences and daily travel schedules to negotiate with Control Center to consume the expected energy and minimize charging cost simultaneously. The proposed algorithm is tested and validated through the experimental implementations in UCLA parking lots.
Keywords :
automotive electrics; battery powered vehicles; power system economics; ARIMA model; EV charging algorithm implementation; UCLA parking; bi-directional communication devices; charging boxes; historical charging load data; smart electric vehicle charging algorithm; smart meters; user price preference; Load modeling; Predictive models; Pricing; Schedules; Servers; Smart grids; Vehicles; EV charging scheduling; load prediction; price preferences; pricing strategy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Smart Grid Technologies Conference (ISGT), 2015 IEEE Power & Energy Society
Conference_Location :
Washington, DC
Type :
conf
DOI :
10.1109/ISGT.2015.7131895
Filename :
7131895
Link To Document :
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