Optimal charging station placement of electric vehicles in the smart distribution network based on the mixed integer linear programming

• Proposed method minimizes station setup, energy costs, and voltage deviations effectively. • Study on a 69-bus grid shows smoother voltage profiles and lower energy losses. • MILP model achieves high accuracy with significantly reduced computation time. • Charging stations use V2G for enhanced grid stability and efficient power management. • Strategic station placement minimizes energy losses and boosts network performance. This article discusses the optimal placement of electric vehicle charging stations in the distribution network. The proposed approach is an optimization problem with the objective function equal to minimizing the cost of building charging stations and energy costs. Inevitably, minimizing the voltage deviation from the desired (reference) value is also considered in the objective function. The constraints of this problem include the equations of power flow, the restrictions governing electric vehicles and charging stations, and the limitations of network indicators. The mentioned problem can be described as mixed integer nonlinear programming (MINLP). Nevertheless, the MINLP optimization problem tends to run very slowly when the dimension of the grid increases significantly, and that’s why it is unlikely that we obtain an absolute optimal solution. Consequently, a mixed integer linear programming (MILP) formulation that resembles the main problem is developed. Ultimately, a distribution network consisting of 69 buses is modeled in GAMS to evaluate the proposed formulation. In the proposed plan with the appropriate placement of electric vehicle charging stations, initially a favorable economic cost is obtained for the aforementioned stations. In the following, charging management at the aforementioned stations has caused the network operation status to improve. When EVs are absent, the maximum voltage drop is approximately 0.092p.u. and energy losses reach 2.08 MW. In contrast, with EVs present the voltage drop falls to about 0.037p.u. and energy losses drop to roughly 1.23 MW.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2025-04-15
DOI
https://doi.org/10.1016/j.ijepes.2025.110675
Citations
15
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
10.96

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article

Optimal charging station placement of electric vehicles in the smart distribution network based on the mixed integer linear programming

Hossein Naderian, Mazaher Karimi, Mehdi Veisi
15 citations
International Journal of Electrical Power & Energy Systems
Electric Vehicles and Infrastructure
10.96
article

Optimal charging station placement of electric vehicles in the smart distribution network based on the mixed integer linear programming

Hossein Naderian, Mazaher Karimi, Mehdi Veisi
article en
15 citations

Abstract

• Proposed method minimizes station setup, energy costs, and voltage deviations effectively. • Study on a 69-bus grid shows smoother voltage profiles and lower energy losses. • MILP model achieves high accuracy with significantly reduced computation time. • Charging stations use V2G for enhanced grid stability and efficient power management. • Strategic station placement minimizes energy losses and boosts network performance. This article discusses the optimal placement of electric vehicle charging stations in the distribution network. The proposed approach is an optimization problem with the objective function equal to minimizing the cost of building charging stations and energy costs. Inevitably, minimizing the voltage deviation from the desired (reference) value is also considered in the objective function. The constraints of this problem include the equations of power flow, the restrictions governing electric vehicles and charging stations, and the limitations of network indicators. The mentioned problem can be described as mixed integer nonlinear programming (MINLP). Nevertheless, the MINLP optimization problem tends to run very slowly when the dimension of the grid increases significantly, and that’s why it is unlikely that we obtain an absolute optimal solution. Consequently, a mixed integer linear programming (MILP) formulation that resembles the main problem is developed. Ultimately, a distribution network consisting of 69 buses is modeled in GAMS to evaluate the proposed formulation. In the proposed plan with the appropriate placement of electric vehicle charging stations, initially a favorable economic cost is obtained for the aforementioned stations. In the following, charging management at the aforementioned stations has caused the network operation status to improve. When EVs are absent, the maximum voltage drop is approximately 0.092p.u. and energy losses reach 2.08 MW. In contrast, with EVs present the voltage drop falls to about 0.037p.u. and energy losses drop to roughly 1.23 MW.

International Journal of Electrical Power & Energy SystemsVol. 168
Islamic Azad University Sanandaj Branch (IR), University of Vaasa (FI)
Nordic Energy Research
Affordable and clean energy
Openalex Percentile: Top 1%
Electric Vehicles and Infrastructure
10.96
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