Hybrid PSO-based Optimal Location of Electric Vehicle Charging Station in Distribution Networks

The widespread adoption of electric vehicles promoted the growth of charging stations in distribution networks. The incorporation of electric vehicle charging stations into the grid leads to an escalation in network losses, thereby causing a detrimental impact on the grid. Strategic planning is impe...

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Bibliographic Details
Published in2024 IEEE Students Conference on Engineering and Systems (SCES) pp. 1 - 6
Main Authors Chandra, Isha, Singh, Apramay, Singh, Navneet Kumar, Samuel, Paulson, Gupta, Om Hari, Singh, Asheesh Kumar
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.06.2024
Subjects
Charging Station
Distribution networks
Electric Vehicles
Optimization methods
Power Loss
Simulation
Stability criteria
Strategic planning
Transportation
Voltage
Voltage Deviation
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Summary:The widespread adoption of electric vehicles promoted the growth of charging stations in distribution networks. The incorporation of electric vehicle charging stations into the grid leads to an escalation in network losses, thereby causing a detrimental impact on the grid. Strategic planning is imperative for the successful incorporation of EVCS into power distribution networks to optimize infrastructure utilization and operational efficiency. This study presents an innovative method for determining the most effective locations for EVCS in 5 different zones of IEEE 33 bus system. To solve the multi-objective function that involves minimalizing the power loss and voltage deviation, a hybrid optimization technique is suggested that combines Gradient Descent (GD) with Particle Swarm Optimisation (PSO). The result shows that losses are minimized by up to 40 \% as compared to uncoordinated charging. The effectiveness of the proposed PSO-GD approach in identifying optimal EVCS locations is demonstrated by simulation results; compared to conventional optimization methods, it achieves significant reductions in power losses and voltage deviations.
DOI:10.1109/SCES61914.2024.10652265