Optimal siting and sizing of electric vehicle charging stations in distribution network considering load uncertainty: An optimization framework

Document Type : Original Article

Authors

1 Graduate University of Advanced Technology

2 Energy Department, Graduate University of Advanced Technology

10.48306/estm.2026.544366.1012
Abstract
Utilization of electric vehicles (EVs) is rapidly increasing in power systems. Due to the impact of EVs on the system performance, from the distribution network's point of view, it is vital to optimally site and size electric vehicle charging stations (EVCSs). This paper establishes an optimization framework for optimal allocation of EVCSs in distribution network. For this goal, development cost of EVCSs and network losses are included in the objective function and the planning problem is solved considering load flow calculations and the constraints. To effectively solve the problem, crow search algorithm (CSA) and differential CSA (CSAdif) are applied and the results are compared. Furthermore, impact of the load uncertainty is investigated on the planning problem. Over the IEEE-33 bus distribution network with photovoltaics (PVs) and wind turbines (WTs) penetration, it can be drawn that it is beneficial to install EVCSs near renewable resources to simply charge batteries. On the other hand, by consideration of the load uncertainty, it is preferred to install more connectors in the stations. Furthermore, compared to CSA, CSAdif finds more promising results in terms of accuracy.

Keywords


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