Optimal ranking-based charging station selection for electric vehicles-Reference-Cited by-同舟云学术

Optimal ranking-based charging station selection for electric vehicles

Published:2023-05-26 Issue:0 Volume:0 Page:
ISSN:2194-5756
Container-title:International Journal of Emerging Electric Power Systems
language:en
Short-container-title:

Author:

Devi Nongmaithem Nandini¹^ORCID,Panda Gayadhar²,Thokchom Surmila¹

Affiliation:

1. Department of Computer Science and Engineering , National Institute of Technology Meghalaya , Shillong , India

2. Department of Electrical Engineering , National Institute of Technology Meghalaya , Shillong , India

Abstract

Abstract In recent times, as many people have started using an electric vehicle (EV) as it provides benefits such as low fuel economy, reduced emission, etc., the deployment of fixed electric vehicle charging stations has been a popular method for supplying EVs with charging services. The charging requirement of EVs varies from vehicle to vehicle. Various schemes have been introduced recently regarding electric vehicles’ energy trading, charging station deployments, etc. Selecting an optimal charging station for booking charging slots by electric vehicle is one of the main concerns to avoid inappropriate services. To address this challenge, we proposed an optimal charging station selection scheme to book charging slots by EV. The proposed method used a multi-criteria decision-making technique called technique for order performance by similarity to ideal solution (TOPSIS) based on various parameters of electric vehicle charging stations (EVCSs). In this, the performance score of each EVCS is determined, and the ranking process is made according to their performance score. Then, EV selects the EVCS with the highest ranked and books the charging slot. Further, an analysis of the proposed scheme is carried out for 10 EVCSs and 3 EVs.

Publisher

Walter de Gruyter GmbH

Subject

Energy Engineering and Power Technology

Link

https://www.degruyter.com/document/doi/10.1515/ijeeps-2023-0124/pdf

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