Optimal Location of Electric Vehicle Fast Charging Station Using Grasshopper Optimization Algorithm

• Published in: SSRG International Journal of Electrical and Electronics Engineering
• Main Author: Yasin Z.M.; Salim N.A.; Noor S.Z.M.; Aziz N.F.A.; Mohamad H.
• Format: Article
• Language: English
• Published: Seventh Sense Research Group 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173993412&doi=10.14445%2f23488379%2fIJEEE-V10I9P117&partnerID=40&md5=5e8ce0bed325d6e00960b8568f14a37b

The increasing prevalence of Electric Vehicles (EVs) has underscored the critical importance of establishing a comprehensive and effective charging station network. To sufficiently meet the energy demands of electric vehicles, it is imperative to establish a robust charging station infrastructure that can effectively cater to a substantial volume of electric automobiles. This infrastructure must be widely deployed to ensure widespread accessibility and usability. Many EVs’ concurrent usage of electric charging stations may lead to potential unreliability in the distribution setup. Hence, it is imperative to strategically determine the placement and sizing of Fast Charging Stations (FCS) to achieve optimal functionality of the power grid. This paper proposes the Grasshopper Optimization Algorithm (GOA) as a technique for strategically locating FCS to minimize costs. GOA is a computational technique that addresses optimization challenges by formulating a mathematical model that emulates the collective behaviour observed in natural grasshopper swarms. The proposed methodology is evaluated on an IEEE 69-bus radial distribution system. The results indicate that the proposed methodology has successfully identified the most economically efficient location for FCS within a power distribution network compared to alternative optimization methods. © 2023 Seventh Sense Research Group®.