Location of electric vehicle charging stations based on INSGAII

Wei Xiao; Ting Li; Ye Chang; Dou Hong

doi:10.1117/12.3035082

21 July 2024 Location of electric vehicle charging stations based on INSGAII

Wei Xiao, Ting Li, Ye Chang, Dou Hong

Proceedings Volume 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024); 132193O (2024) https://doi.org/10.1117/12.3035082
Event: 4th International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2024), 2024, Kaifeng, China

Abstract

With the increasing popularity of electric vehicles (EVs), the location of charging stations has gained significant attention in the auto industry. However, unreasonable locations can lead to reduced return on investment, land resource wastage, and user attrition. Therefore, this study fully considered the interests of investors and user requirements in determining EV charging station locations. An improved non-dominated sorting genetic algorithm II (INSGAII) was developed, incorporating a double-layer coding strategy and hierarchical elite individual selection. Moreover, a multi-objective optimization model was proposed, considering investment costs and user comprehensive costs, along with constraints such as charging pile numbers, service range, and charging uniqueness. Performance validation against traditional nondominated sorting genetic algorithm II (NSGAII) and multi-objective particle swarm optimization algorithm (MOPSO) using the same dataset, alongside verification with actual test case data, confirmed the effectiveness and practicality of INSGAII in determining optimal EV charging station locations.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wei Xiao, Ting Li, Ye Chang, and Dou Hong "Location of electric vehicle charging stations based on INSGAII", Proc. SPIE 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024), 132193O (21 July 2024); https://doi.org/10.1117/12.3035082

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available