DocumentCode :
73390
Title :
Game Theoretic Based Charging Strategy for Plug-in Hybrid Electric Vehicles
Author :
Bahrami, S. ; Parniani, Mostafa
Author_Institution :
Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran, Iran
Volume :
5
Issue :
5
fYear :
2014
fDate :
Sept. 2014
Firstpage :
2368
Lastpage :
2375
Abstract :
In the future smart grids, Plug-in Hybrid Electric Vehicles (PHEVs) are seen as an important means of transportation to reduce greenhouse gas emissions. One of the main issues regarding to this sort of vehicles is managing their charging time to prevent high peak loads over time. Deploying advanced metering and automatic chargers can be a practical way not only for the vehicle owners to manage their energy consumption, but also for the utilities to manage the electricity load during the day by shifting the charging loads to the off-peak periods. Additionally, an efficient charging schedule can reduce the users´ electricity bill cost. In this paper we propose a new practical demand response (DR) program for PHEVs charging scheduling based on game theoretic approach, aiming at optimizing customers charging cost. In the proposed method, a stochastic model is given for starting time of charging, which makes the method a practical tool for simulating the vehicle owners charging behavior effectively.
Keywords :
battery management systems; demand side management; game theory; hybrid electric vehicles; power generation scheduling; smart power grids; DR program; PHEV; advanced metering; automatic chargers; charging loads; charging schedule; charging time; demand response program; electricity bill cost; electricity load; energy consumption; future smart grids; game theoretic approach; off-peak periods; peak loads; plug-in hybrid electric vehicles; stochastic model; Batteries; Games; Load modeling; Optimization; Plug-in hybrid electric vehicles; Scheduling algorithms; Automatic chargers; game theory; load management; peak load shaving; plug-in hybrid electric vehicles;
fLanguage :
English
Journal_Title :
Smart Grid, IEEE Transactions on
Publisher :
ieee
ISSN :
1949-3053
Type :
jour
DOI :
10.1109/TSG.2014.2317523
Filename :
6845378
Link To Document :
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