Plug-in electric vehicle charging station placement using hybrid genetic algorithm-particle swarm optimization

Primatama, Ardhito ORCID: https://orcid.org/0009-0002-8944-7003, Suyono, Hadi and Hasanah, Rini Nur (2025) Plug-in electric vehicle charging station placement using hybrid genetic algorithm-particle swarm optimization. IJEIE : International Journal of Electrical and Intelligent Engineering, 1 (2). pp. 22-29. ISSN 3110-7079

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Abstract

Plug-in electric vehicles are seen to be one way to address environmental problems. Plug-in electric vehicle penetration causes additional issues for the distribution network as the network's load rises. When determining the best location and management plan for a charging station, the primary considerations are power loss, voltage stability, and distribution network dependability. Roads and electrical grids are involved in the challenging task of charging station planning. The charger placement problem examined in this paper was resolved using the Hybrid between Genetic Algorithm and Particle Swarm Optimization (HGAPSO). The HGAPSO strikes an excellent mix between exploration and exploitation. Moreover, HGAPSO reduces the possibility of getting trapped in local optima and early convergence. In comparison to other metaheuristics like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), simulation results demonstrate the effectiveness of the HGAPSO in resolving the charger location problem.

Item Type:	Journal Article
Keywords:	charging station placement; distribution network; hybrid optimization; plug-in electric vehicle; power loss
Subjects:	09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090608 Renewable Power and Energy Systems Engineering (excl. Solar Cells) 09 ENGINEERING > 0906 Electrical and Electronic Engineering
Divisions:	Faculty of Technology > Department of Electrical Engineering
Depositing User:	Ardhito Primatama
Date Deposited:	25 Jun 2026 15:43

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