DocumentCode :
3535054
Title :
Charging of electric vehicles utilizing random wind: A stochastic optimization approach
Author :
Goonewardena, Mathew ; Long Bao Le
Author_Institution :
INRS-EMT, Univ. of Quebec, Montreal, QC, Canada
fYear :
2012
fDate :
3-7 Dec. 2012
Firstpage :
1520
Lastpage :
1525
Abstract :
In this paper, we present a general stochastic framework for the optimization of charging of electric vehicles (EVs) utilizing wind energy. The framework considers different key components of the Smart Grid including stochastic wind energy, bulk and real-time purchase of energy from the grid operator, penalties or sell back of unutilized committed energy and flexible demand of the EV users. We formulate the joint vehicle charging and power purchase problem as a stochastic optimization program. Then we describe how to obtain its solution numerically. We also present a widely used alternative problem formulation using expected values of the random wind and real-time prices. Numerical results are presented to demonstrate the efficacy of the proposed framework and the significant performance gain compared to an expected-value approach.
Keywords :
battery powered vehicles; expectation-maximisation algorithm; secondary cells; stochastic programming; wind power; EV users; electric vehicle charging; expected-value approach; random wind; real-time prices; stochastic optimization approach; stochastic wind energy; wind energy; Joints; Numerical models; Optimization; Real-time systems; Vectors; Wind energy; Wind power generation; electric vehicle; power scheduling; smart grid; stochastic optimization; wind power;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Globecom Workshops (GC Wkshps), 2012 IEEE
Conference_Location :
Anaheim, CA
Print_ISBN :
978-1-4673-4942-0
Electronic_ISBN :
978-1-4673-4940-6
Type :
conf
DOI :
10.1109/GLOCOMW.2012.6477811
Filename :
6477811
Link To Document :
بازگشت