Research Progress and Prospects of Public Transportation Charging Station Layout Methods

Electric buses have been vigorously promoted and implemented in major countries worldwide and have generated a huge demand for charging stations. Optimizing the daily charging experience of electric buses, adapting the daily operation scheduling, improving the utilization rate of charging stations,...

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Bibliographic Details
Published in:World electric vehicle journal 2024-02, Vol.15 (2), p.63
Main Authors: Lei, Hao, Hu, Xinghua, Zhao, Jiahao, Deng, Dongde, Wang, Ran
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Buses
Buses (vehicles)
charging demand analysis
charging station site planning
Cities
Clean technology
Climate change
Cost analysis
Data integration
electric bus
Electric power
Electric power demand
Electric vehicle charging
Electric vehicle charging stations
Electric vehicles
Electricity distribution
Emissions
Energy consumption
Fossil fuels
Layouts
Load distribution
Methods
Operation scheduling
Optimization models
Public transportation
Simulation
summarize
Telematics
Transportation systems
Urban areas
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Summary:Electric buses have been vigorously promoted and implemented in major countries worldwide and have generated a huge demand for charging stations. Optimizing the daily charging experience of electric buses, adapting the daily operation scheduling, improving the utilization rate of charging stations, reducing the load on the power grid, and improving the operation efficiency of electric bus line networks require the reasonable layout of the charging stations. In this study, public transportation charging station layout and siting is the research object. We summarize the progress of analysis methods from the charging station and vehicle sides; introduce related research on the planning and layout of charging stations based on optimization models, including cost analysis and siting and layout for electric bus systems; summarize the data-driven station planning and siting research; and provide an overview of the current charging demand estimation, accuracy, and charging efficiency. Finally, we address the problems of the charging demand estimation accuracy, the mismatch between the charging station layouts for electric buses, and the charging demand on a long time scale. We suggest that research be conducted on data fusion for the temporal and spatial refinement of charging demand prediction in the context of the electrification of public transportation systems and the big data of telematics.
ISSN:2032-6653
2032-6653
DOI:10.3390/wevj15020063