Cargando…

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

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 l...

Descripción completa

Detalles Bibliográficos
Autores principales: Islam, Md. Mainul, Shareef, Hussain, Mohamed, Azah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722383/
https://www.ncbi.nlm.nih.gov/pubmed/29220396
http://dx.doi.org/10.1371/journal.pone.0189170
_version_ 1783285000899133440
author Islam, Md. Mainul
Shareef, Hussain
Mohamed, Azah
author_facet Islam, Md. Mainul
Shareef, Hussain
Mohamed, Azah
author_sort Islam, Md. Mainul
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5722383
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-57223832017-12-15 Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm Islam, Md. Mainul Shareef, Hussain Mohamed, Azah PLoS One Research Article 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. Public Library of Science 2017-12-08 /pmc/articles/PMC5722383/ /pubmed/29220396 http://dx.doi.org/10.1371/journal.pone.0189170 Text en © 2017 Islam et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Islam, Md. Mainul
Shareef, Hussain
Mohamed, Azah
Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm
title Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm
title_full Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm
title_fullStr Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm
title_full_unstemmed Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm
title_short Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm
title_sort improved approach for electric vehicle rapid charging station placement and sizing using google maps and binary lightning search algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722383/
https://www.ncbi.nlm.nih.gov/pubmed/29220396
http://dx.doi.org/10.1371/journal.pone.0189170
work_keys_str_mv AT islammdmainul improvedapproachforelectricvehiclerapidchargingstationplacementandsizingusinggooglemapsandbinarylightningsearchalgorithm
AT shareefhussain improvedapproachforelectricvehiclerapidchargingstationplacementandsizingusinggooglemapsandbinarylightningsearchalgorithm
AT mohamedazah improvedapproachforelectricvehiclerapidchargingstationplacementandsizingusinggooglemapsandbinarylightningsearchalgorithm