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All Journal International Journal of Electrical and Intelligent Engineering
Ardhito Primatama
Universitas Islam Negeri Maulana Malik Ibrahim
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Plug-in Electric Vehicle Charging Station Placement using Hybrid Genetic Algorithm-Particle Swarm Optimization Ardhito Primatama; Hadi Suyono; Rini Nur Hasanah
International Journal of Electrical and Intelligent Engineering Vol 1, No 2 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i2.33951

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
Co-Authors Rini Nur Hasanah Suyono, Hadi