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Frequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
Home Archives Volume 11 Issue 1 ijcatr11011001

IJCATR Volume 11 Issue 1

Optimal Placement of Fast Charging Station using Hybrid Optimization Algorithm

Ardhito Primatama, Hadi Suyono, Rini Nur Hasanah
10.7753/IJCATR1101.1001
keywords : plug-in electric vehicle; optimization; charging station location; distribution network; power loss

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Plug-in electric vehicle is considered to be one of solutions of environmental issues. Penetration of plug-in electric vehicle brings new problem on the distribution network as the load on the network increases. The distribution network reliability, voltage stability and power loss are the main factors in designing the optimum placement and management strategy of a charging station. The planning of charging stations is a complicated problem involving roads and power grids. The Hybrid between Genetic Algorithm and Particle Swarm Optimization (HGAPSO) used for solving the charger placement problem tested in this work. A good balance between exploitation and exploration is achieved by the HGAPSO. Furthermore, the likelihood of becoming stuck in premature convergence and local optima is minimized in HGAPSO. Simulation results establish the efficacy of the HGAPSO in solving charger placement problem as compared to other metaheuristics such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).
@artical{a1112022ijcatr11011001,
Title = "Optimal Placement of Fast Charging Station using Hybrid Optimization Algorithm",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "11",
Issue ="1",
Pages ="1 - 6",
Year = "2022",
Authors ="Ardhito Primatama, Hadi Suyono, Rini Nur Hasanah"}
  • The paper proposes solution to find optimal location of electrical vehicle charging station.
  • The location and number of chargers determined considering distribution network.
  • Hybrid between Genetic Algorithm and Particle Swarm Optimization used in this research.
  • Power losses and voltage deviation is minimized using the algorithm
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