Title :
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
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;
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
DOI :
10.1109/ICNSC.2013.6548859
