Optimal Electric Vehicle Charging Station Integrating Renewable Energy Using Particle Swarm Optimization

DOI

10.2991/978-94-6463-870-7_2How to use a DOI?

Keywords

Electric Vehicle; Charging Station; Renewable energy; Optimization; Energy Management; Probability

Abstract

Aiming for the reduction in carbon emissions there is a widespread increase in Electric Vehicles. This develops the urge to build fast charging stations. Construction of fast charging station can create strain for the electricity grid. Integration of renewable energy source in the Electric Vehicle Fast Charging Station will reduce impacts from the grid. The selected location for the Charging station design is with latitude 10.9°North and longitude 76.7°East where solar and wind energy sources are abundant. The charging station considered in this research study comprises many chargers to charge the batteries of Electric Vehicle entering to the charging station, solar generators, wind generators and battery storage. The optimal design of the charging station is done through Particle Swarm Optimization. The optimal values are determined for the variables such as number of electric vehicle chargers in the station, power of the charger placed in the station, area of solar panel, energy storage, grid power limit, wind generator type and number of wind generators. Initially the charging station modelling has been done for a year and then further evaluated for 20 years. The entire modelling and simulation of the charging station was done using Matlab programming. The results obtained shows that integration of renewable energy in the charging station resulted in more profit. The cash obtained in the charging station while incorporating renewable energy along with grid power is more compared with cash outflowing (outgoing). Thus resulting in more profit. Also, the Net Present Value evaluated is more while incorporating renewable energy along with grid power.

Copyright

© 2025 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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TY  - CONF
AU  - Merry Cherian
AU  - A. Immanuel Selvakumar
PY  - 2025
DA  - 2025/10/22
TI  - Optimal Electric Vehicle Charging Station Integrating Renewable Energy Using Particle Swarm Optimization
BT  - Proceedings of the International Conference on Smart Innovations in Electrical Engineering (ICSIEE 2025)
PB  - Atlantis Press
SP  - 4
EP  - 11
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-870-7_2
DO  - 10.2991/978-94-6463-870-7_2
ID  - Cherian2025
ER  -