Energy-efficient EV Charging Station Placement for E-Mobility

Mohammad Al Ja'idi, Nauman Aslam, Xiaomin Chen, Omprakash Kaiwartya, Yousef Ali Al-Gumaei

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Despite all the acknowledged advantages and recent developments in terms of reducing the environmental impact, noise reduction and energy efficiency, the electric mobility market is still below the expectations. Among the most important challenges that limit the market penetration of Electric Vehicles (EVs) as well as achieving a sustainable mobility system in cities is the efficient distribution of adequate EV charging stations (CSs). In this paper, we propose a novel approach to find the best locations for EVCSs that considers a combination of factors including displacement between the EV and CS, elevation difference between their locations and finite capacities of CSs. The problem is formulated as a Mixed Integer Linear problem (MILP) to minimize the total energy consumption of EVs to reach CSs. A combination of the Genetic Algorithm (GA) technique and the Branch and Bound (B&B) algorithm are used to solve the problem. The proposed EVCSs placement technique is experimentally tested considering different case studies. With real world datasets, the results demonstrate the energy centric benefits of the proposed EVCSs placement technique.
Original languageEnglish
Title of host publicationIECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages3672-3678
Number of pages7
ISBN (Electronic)9781728154145
DOIs
Publication statusPublished - 18 Oct 2020

Fingerprint

Dive into the research topics of 'Energy-efficient EV Charging Station Placement for E-Mobility'. Together they form a unique fingerprint.

Cite this