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Optimal Allocation of Public Charging Stations based on Traffic Density in Smart Cities

机译:基于交通密度的智慧城市公共充电站优化配置

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Plug-in electric vehicle (PEV) massive introduction will contribute to improve the air quality, however, the limited driving range might cause few interests for the potential consumers of this new alternative mobility. Therefore, it's essential that public charging stations (PCS) are planning through optimal deployments, this guarantee that PEV operators lay out PCS that contemplate maxim reach distance. Thus, Article contributes for PCS optimal deployment with traffic flow restrictions, driving maxim distance, load density and relation of PEV with infrastructure environment of load public station (IPCS); besides, PCS in need of multiple connections (slow, fast and ultra-fast charging). Finally, proposed heuristic considers a theoretical model with spatial approach. Study region data was obtained by means of osm file, courtesy of OpenStreetMap platform. Hence, the model knows areas and cartography reality, hereafter cartography reality displaces PCS for PEV.
机译:插电式电动汽车(PEV)的大量推出将有助于改善空气质量,但是,有限的行驶里程可能不会吸引这种新的替代性出行的潜在消费者。因此,至关重要的是,公共充电站(PCS)必须通过最佳部署进行规划,这确保PEV运营商布置考虑最大到达距离的PCS。因此,Article为交通流量限制,行车最大距离,负载密度以及PEV与负载公共站(IPCS)的基础结构环境之间的关系提供了PCS最佳部署的帮助;此外,PCS需要多个连接(慢速,快速和超快速充电)。最后,提出的启发式方法考虑了具有空间方法的理论模型。研究区域数据是通过OpenStreetMap平台的osm文件获得的。因此,模型知道区域和制图现实,此后制图现实取代了用于PEV的PCS。

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