PSO-based method to find electric vehicle´s optimal charging schedule under dynamic electricity price

Author

Jing An ; Bingyao Huang ; Qi Kang ; Mengchu Zhou

Author_Institution

Sch. of Electr. & Electron. Eng., Shanghai Inst. of Technol., Shanghai, China

fYear

2013

fDate

10-12 April 2013

Firstpage

913

Lastpage

918

Abstract

Owning to greenhouse effect and exhaustible gasoline, there is a need for the automobile industry to develop electric vehicles (EVs). EV owners´ major concern is about how to minimize operating cost under dynamic market electricity price. Optimization of a charging scenario draws great attention from the researchers worldwide. This paper presents a particle swarm optimization (PSO) based optimization approach that can help EV owners achieve the most economical charging behavior.

Keywords

cost reduction; electric vehicles; particle swarm optimisation; power markets; pricing; secondary cells; EV owners; PSO-based method; automobile industry; dynamic market electricity price; economical charging behavior; electric vehicles optimal charging schedule; exhaustible gasoline; greenhouse effect; operating cost minimization; particle swarm optimization; Batteries; Dynamic programming; Electricity; Heuristic algorithms; Optimization; Schedules; Vehicles; Dynamic electricity price; Electric vehicle; Optimal charging; PSO;

fLanguage

English

Publisher

ieee

Conference_Titel

Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on

Conference_Location

Evry

Print_ISBN

978-1-4673-5198-0

Electronic_ISBN

978-1-4673-5199-7

Type

conf

DOI

10.1109/ICNSC.2013.6548859

Filename

6548859