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Smart Control of Fleets of Electric Vehicles in Smart and Connected Communities

机译:智慧互联社区中的电动汽车车队的智能控制

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摘要

The increasing deployment of electric vehicles (EVs) across the United States has introduced many new opportunities and challenges with regards to energy management and control. In smart and connected communities (SCCs), where advanced communication infrastructures are in place, optimal coordination of EVs can significantly impact EV owners, power systems, and charging station owners. This paper develops two scheduling frameworks (static and dynamic) for optimal coordination of a fleet of cooperative EVs in a community with many charging stations and potentially different types of chargers (e.g., level 1, level 2, and DC fast). The scheduling problems are formulated as mixed-integer multi-objective optimization models and then multi-objective solution methods are utilized to find the optimal solution for each of the two scheduling frameworks. Numerical experiments simulated based on the State of Florida verify the usefulness of smart charging for better energy management and satisfying key players' objectives and constraints.
机译:在美国,电动汽车(EV)的部署不断增加,在能源管理和控制方面带来了许多新的机遇和挑战。在拥有高级通信基础设施的智能互联社区(SCC)中,电动汽车的最佳协调会严重影响电动汽车所有者,电力系统和充电站所有者。本文开发了两个调度框架(静态和动态),以在具有许多充电站和潜在不同类型的充电器(例如1级,2级和DC快速充电)的社区中最佳协作电动车队的协调。将调度问题表述为混合整数多目标优化模型,然后利用多目标求解方法为两个调度框架中的每一个找到最优解。基于佛罗里达州进行的数值实验验证了智能充电对更好的能源管理以及满足主要参与者的目标和约束的有效性。

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