Research on Double-layer Site Selection and Capacity Determination Planning of Urban Electric Vehicle Charging Stations under the Structure of the Transportation Network

Aiming at the problem that the regional restrictions in urban areas make it difficult to determine the optimal number, site and capacity of electric vehicle charging stations (EVCS), a double-layer site selection and capacity determination model for EVCs under the transportation network structure is proposed. Firstly, it expounds how the charging load affects the distribution network under different charging modes; Next, a two-layer optimization model for site selection and capacity was constructed. The upper layer, from the perspective of minimizing the comprehensive cost of EVCS investors and operators, adopted the improved Particle Swarm Optimization (GDPSO) algorithm to generate the site selection scheme and passed the scheme to the lower layer. From the perspective of electric vehicle users at the lower level, the Floyd algorithm is adopted and the Voronoi diagram is used to divide the service areas of each charging station. The nearest EVCS is given priority for charging, with the goal of reducing the annual loss cost for users. Finally, taking the IEEE 33-node power distribution system and the 25-node transportation network as cases, the correctness of the proposed method was verified. (Abstract)

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Published
2025-05-23
DOI
https://doi.org/10.1109/ecie65947.2025.11086839
Primary Topic
Electric Vehicles and Infrastructure
Type
article
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article

Research on Double-layer Site Selection and Capacity Determination Planning of Urban Electric Vehicle Charging Stations under the Structure of the Transportation Network

Jiaxin Song, Guo Wang
Electric Vehicles and Infrastructure
article

Research on Double-layer Site Selection and Capacity Determination Planning of Urban Electric Vehicle Charging Stations under the Structure of the Transportation Network

Jiaxin Song, Guo Wang
article en

Abstract

Aiming at the problem that the regional restrictions in urban areas make it difficult to determine the optimal number, site and capacity of electric vehicle charging stations (EVCS), a double-layer site selection and capacity determination model for EVCs under the transportation network structure is proposed. Firstly, it expounds how the charging load affects the distribution network under different charging modes; Next, a two-layer optimization model for site selection and capacity was constructed. The upper layer, from the perspective of minimizing the comprehensive cost of EVCS investors and operators, adopted the improved Particle Swarm Optimization (GDPSO) algorithm to generate the site selection scheme and passed the scheme to the lower layer. From the perspective of electric vehicle users at the lower level, the Floyd algorithm is adopted and the Voronoi diagram is used to divide the service areas of each charging station. The nearest EVCS is given priority for charging, with the goal of reducing the annual loss cost for users. Finally, taking the IEEE 33-node power distribution system and the 25-node transportation network as cases, the correctness of the proposed method was verified. (Abstract)

Lanzhou Jiaotong University (CN)
Sustainable cities and communities
Openalex Percentile: Top 82%
Electric Vehicles and Infrastructure
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