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

Jing An, Bing Yao Huang, Qi Kang, Meng Chu Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013
Pages913-918
Number of pages6
DOIs
StatePublished - Aug 14 2013
Event2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013 - Evry, France
Duration: Apr 10 2013Apr 12 2013

Publication series

Name2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013

Other

Other2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013
CountryFrance
CityEvry
Period4/10/134/12/13

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Networks and Communications

Keywords

  • Dynamic electricity price
  • Electric vehicle
  • Optimal charging
  • PSO

Fingerprint Dive into the research topics of 'PSO-based method to find electric vehicle's optimal charging schedule under dynamic electricity price'. Together they form a unique fingerprint.

  • Cite this

    An, J., Huang, B. Y., Kang, Q., & Zhou, M. C. (2013). PSO-based method to find electric vehicle's optimal charging schedule under dynamic electricity price. In 2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013 (pp. 913-918). [6548859] (2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013). https://doi.org/10.1109/ICNSC.2013.6548859