Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)

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Hybrid Harris Hawk Optimization of Electric Vehicle Charging Station Placement

Authors
F. Peter1, S. Robin Divahar1, *, B. Anand2, L. M. Karthikeyan3, Rajiv Selvam4, R. J. Golden Renjith Nimal2
1Department of Automobile Engineering, Noorul Islam Centre for Higher Education, Thuckalay, India
2Department of Mechanical Engineering, Jai Shriram Engineering College, Avinashipalayam, Tirupur, India
3Department of Aerospace Engineering, Noorul Islam Centre for Higher Education, Thuckalay, India
4Department of Mechanical Engineering & Deputy Chairperson – School of Engineering & IT, Manipal Academy of Higher Education, Dubai Campus G04, 345050, Dubai, UAE
*Corresponding author. Email: srobindivahar@niuniv.com
Corresponding Author
S. Robin Divahar
Available Online 24 April 2026.
DOI
10.2991/978-94-6239-654-8_59How to use a DOI?
Keywords
Electric vehicles; Charging station placement; Optimization; Attention mechanism; Deep learning
Abstract

The electric mobility sector has progressed quickly and, consequently, the need for charging facilities has increased tremendously. Therefore, the question of where to place charging stations has become a major research topic. Nevertheless, the majority of the studies carried out up to now have not incorporated a very important factor fairness regarding the location of charging stations along the network mainly because it directly affects the ease of access and user convenience. So as to close this gap, the current paper introduces a Hybrid Harris Hawk Optimization (HHO) framework integrated with an attention mechanism for determining the optimal places for EV charging stations. The proposed method has given equal importance to different factors like the station distribution, location advantages, and user comfort. Fairness was measured by how evenly the stations were distributed, and user comfort was measured by the overall charging time that users underwent. The hybrid model has succeeded in accomplishing these goals. Therefore, one can say that this method offers a superior and more sophisticated way of planning for EV charging stations.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
Series
Advances in Engineering Research
Publication Date
24 April 2026
ISBN
978-94-6239-654-8
ISSN
2352-5401
DOI
10.2991/978-94-6239-654-8_59How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - F. Peter
AU  - S. Robin Divahar
AU  - B. Anand
AU  - L. M. Karthikeyan
AU  - Rajiv Selvam
AU  - R. J. Golden Renjith Nimal
PY  - 2026
DA  - 2026/04/24
TI  - Hybrid Harris Hawk Optimization of Electric Vehicle Charging Station Placement
BT  - Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
PB  - Atlantis Press
SP  - 750
EP  - 765
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-654-8_59
DO  - 10.2991/978-94-6239-654-8_59
ID  - Peter2026
ER  -