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INTELLIGENT DYNAMIC CHARGING ASSIGNMENT FOR INCREASING EFFICIENCY IN EV DRIVING

机译:智能电动充电装置,提高电动汽车行驶效率

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摘要

As electric vehicles are being considered to provide clean mobility in the future, Ensuring sustainable integration of electric vehicle charging provides challenges for all levels of the charging ecosystem. While charging at moderate charging levels can be integrated in load balancing and flexible scheduling schemes, the fast and high power level charging (above 30kW) is so far less considered in control concepts, besides its high impact on the power grid and its effect on user acceptance. In this paper, we propose a sophisticated method to guide an EV user in his charging needs in balance with the charging infrastructure and other EV users' demands. The prime idea is a multi-objective optimization aiming for increasing the user travel experience with respect to EV charging and for maximizing the usage of available resources dispersed among the charging stations. The method is assessed through simulations and benchmarked against a naive charging scenario. The analysis shows a significant reduction in waiting queue size and waiting times for the intelligent dynamic assignment. Moreover, we see an improved overall distribution of the energy consumption between the charging stations.
机译:由于考虑将电动汽车提供未来的清洁出行,确保电动汽车充电的可持续集成为所有级别的充电生态系统带来了挑战。尽管可以将中等充电水平的充电集成到负载平衡和灵活的调度方案中,但到目前为止,在控制概念中,除了对电网的巨大影响及其对用户的影响外,快速和高功率水平充电(30kW以上)的考虑还很少。验收。在本文中,我们提出了一种复杂的方法来指导电动汽车用户满足其充电需求,同时兼顾充电基础设施和其他电动汽车用户的需求。首要思想是多目标优化,旨在提高用户在EV充电方面的出行体验,并最大限度地利用分散在充电站之间的可用资源。该方法通过仿真进行评估,并以天真的计费场景为基准。分析显示,智能动态分配的等待队列大小和等待时间显着减少。此外,我们发现充电站之间的能耗总体分配有所改善。

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