Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm

Md Mainul Islam, Hussain Shareef, Azah Mohamed

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

The electric vehicle (EV) is considered a premium solution to global warming and various types of pollution. Nonetheless, a key concern is the recharging of EV batteries. Therefore, this study proposes a novel approach that considers the costs of transportation loss, buildup, and substation energy loss and that incorporates harmonic power loss into optimal rapid charging station (RCS) planning. A novel optimization technique, called binary lightning search algorithm (BLSA), is proposed to solve the optimization problem. BLSA is also applied to a conventional RCS planning method. A comprehensive analysis is conducted to assess the performance of the two RCS planning methods by using the IEEE 34-bus test system as the power grid. The comparative studies show that the proposed BLSA is better than other optimization techniques. The daily total cost in RCS planning of the proposed method, including harmonic power loss, decreases by 10% compared with that of the conventional method.

Original languageEnglish
Article numbere0189170
JournalPLoS ONE
Volume12
Issue number12
DOIs
Publication statusPublished - Dec 2017

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

Fingerprint

Dive into the research topics of 'Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm'. Together they form a unique fingerprint.

Cite this