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...

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Vydané v:2025 5th International Conference on Electronics, Circuits and Information Engineering (ECIE) s. 182 - 186
Hlavní autori: Song, Jiaxin, Wang, Guo
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 23.05.2025
Predmet:
Capacity planning
charging demand forecast
Charging stations
Costs
Electric vehicle charging
freud's algorithm
improve the particle swarm optimization algorithm (key words)
Particle swarm optimization
Planning
planning of electric vehicle charging stations
Roads
Transportation
transportation network model
Urban areas
Weather forecasting
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Popis
Shrnutí: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)
DOI:10.1109/ECIE65947.2025.11086839