An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments

Mohammad Al Ja'idi; Nauman Aslam; Xiaomin Chen; Omprakash Kaiwartya; Muhammad Khalid

doi:10.1109/ICICS49469.2020.239501

An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments

Mohammad Al Ja'idi, Nauman Aslam, Xiaomin Chen, Omprakash Kaiwartya, Muhammad Khalid

Computer and Information Sciences Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

19 Citations (Scopus)

Abstract

Due to recent developments in electric mobility, public charging infrastructure will be essential for modern transportation systems. As the numbers of electric vehicles (EVs) increase, public charging infrastructure needs to adopt efficient charging practices. A key challenge is the assignment of EVs to charging stations in an energy efficient manner. In this paper, we propose a novel scheme that solves the assignment problem by taking into account a combination of factors including displacement between the current location of EV and the charging station, difference in elevation between their locations and the capacity of charging stations. The displacement and the difference in elevation between the locations of the EVs and charging stations are considered to calculate the amount of energy consumption for the EVs to reach charging stations. The problem has been formulated as a Mixed Integer Linear Programming (MILP) problem, and solved using Branch and Bound (B&B) algorithm.

Original language	English
Title of host publication	2020 11th International Conference on Information and Communication Systems (ICICS 2020)
Place of Publication	Piscataway
Publisher	IEEE
Pages	161-166
Number of pages	6
ISBN (Electronic)	9781728162270
ISBN (Print)	9781728162287
DOIs	https://doi.org/10.1109/ICICS49469.2020.239501
Publication status	Published - Apr 2020
Event	2020 11th International Conference on Information and Communication Systems - Jordan University of Science and Technology, Irbid, Jordan Duration: 7 Apr 2020 → 9 Apr 2020 https://www.just.edu.jo/icics/icics2020/

Publication series

Name	International Conference on Information and Communication Systems
Publisher	IEEE
ISSN (Electronic)	2471-125X

Conference

Conference	2020 11th International Conference on Information and Communication Systems
Abbreviated title	ICICS
Country/Territory	Jordan
City	Irbid
Period	7/04/20 → 9/04/20
Internet address	https://www.just.edu.jo/icics/icics2020/

Keywords

Electric vehicle assignment
charging station
energy consumption
displacement
elevation
capacity

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICICS49469.2020.239501

Cite this

Al Ja'idi, M., Aslam, N., Chen, X., Kaiwartya, O., & Khalid, M. (2020). An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments. In 2020 11th International Conference on Information and Communication Systems (ICICS 2020) (pp. 161-166). Article 239501 (International Conference on Information and Communication Systems). IEEE. https://doi.org/10.1109/ICICS49469.2020.239501

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title = "An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments",

abstract = "Due to recent developments in electric mobility, public charging infrastructure will be essential for modern transportation systems. As the numbers of electric vehicles (EVs) increase, public charging infrastructure needs to adopt efficient charging practices. A key challenge is the assignment of EVs to charging stations in an energy efficient manner. In this paper, we propose a novel scheme that solves the assignment problem by taking into account a combination of factors including displacement between the current location of EV and the charging station, difference in elevation between their locations and the capacity of charging stations. The displacement and the difference in elevation between the locations of the EVs and charging stations are considered to calculate the amount of energy consumption for the EVs to reach charging stations. The problem has been formulated as a Mixed Integer Linear Programming (MILP) problem, and solved using Branch and Bound (B&B) algorithm.",

keywords = "Electric vehicle assignment, charging station, energy consumption, displacement, elevation, capacity",

author = "{Al Ja'idi}, Mohammad and Nauman Aslam and Xiaomin Chen and Omprakash Kaiwartya and Muhammad Khalid",

year = "2020",

month = apr,

doi = "10.1109/ICICS49469.2020.239501",

language = "English",

isbn = "9781728162287",

series = "International Conference on Information and Communication Systems",

publisher = "IEEE",

pages = "161--166",

booktitle = "2020 11th International Conference on Information and Communication Systems (ICICS 2020)",

address = "United States",

note = "2020 11th International Conference on Information and Communication Systems, ICICS ; Conference date: 07-04-2020 Through 09-04-2020",

url = "https://www.just.edu.jo/icics/icics2020/",

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Al Ja'idi, M, Aslam, N, Chen, X, Kaiwartya, O & Khalid, M 2020, An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments. in 2020 11th International Conference on Information and Communication Systems (ICICS 2020)., 239501, International Conference on Information and Communication Systems, IEEE, Piscataway, pp. 161-166, 2020 11th International Conference on Information and Communication Systems, Irbid, Jordan, 7/04/20. https://doi.org/10.1109/ICICS49469.2020.239501

An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments. / Al Ja'idi, Mohammad; Aslam, Nauman; Chen, Xiaomin et al.
2020 11th International Conference on Information and Communication Systems (ICICS 2020). Piscataway: IEEE, 2020. p. 161-166 239501 (International Conference on Information and Communication Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments

AU - Al Ja'idi, Mohammad

AU - Aslam, Nauman

AU - Chen, Xiaomin

AU - Kaiwartya, Omprakash

AU - Khalid, Muhammad

PY - 2020/4

Y1 - 2020/4

N2 - Due to recent developments in electric mobility, public charging infrastructure will be essential for modern transportation systems. As the numbers of electric vehicles (EVs) increase, public charging infrastructure needs to adopt efficient charging practices. A key challenge is the assignment of EVs to charging stations in an energy efficient manner. In this paper, we propose a novel scheme that solves the assignment problem by taking into account a combination of factors including displacement between the current location of EV and the charging station, difference in elevation between their locations and the capacity of charging stations. The displacement and the difference in elevation between the locations of the EVs and charging stations are considered to calculate the amount of energy consumption for the EVs to reach charging stations. The problem has been formulated as a Mixed Integer Linear Programming (MILP) problem, and solved using Branch and Bound (B&B) algorithm.

AB - Due to recent developments in electric mobility, public charging infrastructure will be essential for modern transportation systems. As the numbers of electric vehicles (EVs) increase, public charging infrastructure needs to adopt efficient charging practices. A key challenge is the assignment of EVs to charging stations in an energy efficient manner. In this paper, we propose a novel scheme that solves the assignment problem by taking into account a combination of factors including displacement between the current location of EV and the charging station, difference in elevation between their locations and the capacity of charging stations. The displacement and the difference in elevation between the locations of the EVs and charging stations are considered to calculate the amount of energy consumption for the EVs to reach charging stations. The problem has been formulated as a Mixed Integer Linear Programming (MILP) problem, and solved using Branch and Bound (B&B) algorithm.

KW - Electric vehicle assignment

KW - charging station

KW - energy consumption

KW - displacement

KW - elevation

KW - capacity

U2 - 10.1109/ICICS49469.2020.239501

DO - 10.1109/ICICS49469.2020.239501

M3 - Conference contribution

SN - 9781728162287

T3 - International Conference on Information and Communication Systems

SP - 161

EP - 166

BT - 2020 11th International Conference on Information and Communication Systems (ICICS 2020)

PB - IEEE

CY - Piscataway

T2 - 2020 11th International Conference on Information and Communication Systems

Y2 - 7 April 2020 through 9 April 2020

ER -

Al Ja'idi M, Aslam N, Chen X, Kaiwartya O, Khalid M. An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments. In 2020 11th International Conference on Information and Communication Systems (ICICS 2020). Piscataway: IEEE. 2020. p. 161-166. 239501. (International Conference on Information and Communication Systems). Epub 2020 Apr 27. doi: 10.1109/ICICS49469.2020.239501

An Energy Efficient Strategy for Assignment of Electric Vehicles to Charging Stations in Urban Environments

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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Cite this