@inproceedings{14e23c4d75514a19a7a4b6c91ac507ca,
title = "PSO-based method to find electric vehicle's optimal charging schedule under dynamic electricity price",
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 = "Dynamic electricity price, Electric vehicle, Optimal charging, PSO",
author = "Jing An and Huang, {Bing Yao} and Qi Kang and Zhou, {Meng Chu}",
year = "2013",
doi = "10.1109/ICNSC.2013.6548859",
language = "English (US)",
isbn = "9781467351980",
series = "2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013",
pages = "913--918",
booktitle = "2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013",
note = "2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013 ; Conference date: 10-04-2013 Through 12-04-2013",
}