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