Optimal location planning method of fast charging station for electric vehicles considering operators, drivers, vehicles, traffic flow and power grid

In order to promote penetration and popularity of electric vehicles, it is of critical importance to determine location and size of charging stations more scientifically. There are various factors influential to the charging station location, including economy problem of operators, drivers' cha...

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Veröffentlicht in:Energy (Oxford) 2019-11, Vol.186, p.115826, Article 115826
Hauptverfasser: Kong, Weiwei, Luo, Yugong, Feng, Guixuan, Li, Keqiang, Peng, Huei
Format: Artikel
Sprache:eng
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Zusammenfassung:In order to promote penetration and popularity of electric vehicles, it is of critical importance to determine location and size of charging stations more scientifically. There are various factors influential to the charging station location, including economy problem of operators, drivers' charging satisfactory, power loss of vehicles, traffic jam of transportation system and safety of the power grid. Researches have been done considering a few of them. There is a lack of systematic studies considering the various factors all together. In addition, existing researches are performed based on statistical data. This paper aims to study a novel location planning method of fast charging stations, in order to achieve the overall optimization of operators, drivers, vehicles, traffic condition, and power grid. More importantly, dynamic real-time data related is utilized for optimal planning instead of statistical data, which is more scientific and reasonable. In addition, a universal simulation platform is developed, which is suitable for optimal location planning in different cities or areas. A practical case is studied within the third ring of Beijing, simulation results demonstrate that the proposed method can optimize the economic interest of operators, enhance drivers’ charging satisfaction, and ensure traffic efficiency and safety of power grid. •The optimal method is proposed considering operators, drivers, traffic and grid.•Dynamic real-time data is utilized for planning instead of statistical data.•A universal simulation platform for different area is built up with modular design.•The operators' economic interest can be optimized.•Drivers' charging satisfaction, traffic efficiency, and safety of grid are enhanced.
ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2019.07.156