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

机译:基于智能城市交通密度的公共收费站最优分配

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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:插入式电动车(PEV)巨大介绍将有助于提高空气质量,但是,有限的驾驶范围可能对这种新的替代流动性的潜在消费者来说造成一些兴趣。因此,公共收费站(PCS)是必不可少的,通过最佳部署规划,这保证了PEV运营商铺设了考虑Maxim达到距离的PC。因此,文章为PCS提供了具有交通流量限制的最佳部署,驱动Maxim距离,负载密度和PEV与Load Publicate(IPC)的基础设施环境的关系;此外,需要多种连接的PC(缓慢,快速,快速充电)。最后,提出的启发式认为具有空间方法的理论模型。研究区域数据是通过OSM文件获得的,由OpenStreetMap平台提供。因此,该模型知道区域和制图现实,介绍制图现实取代了PEV的PC。

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