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Decentralised online charging scheduling for large populations of electric vehicles: a cyber-physical system approach

机译:大量电动汽车的分散式在线充电调度:一种网络物理系统方法

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As the number of electric vehicles (EVs) grows, their electricity demands may have significant detrimental impacts on electric power grid when not scheduled properly. In this paper, we model an EV charging system as a cyber-physical system, and design a decentralised online EV charging scheduling algorithm for large populations of EVs, where the EVs can be highly heterogeneous and may join the charging system dynamically. The algorithm couples a clustering-based strategy that dynamically classifies heterogeneous EVs into multiple groups and a sliding-window iterative approach that schedules the charging demand for the EVs in each group in real time. Extensive simulation results demonstrate that our approach provides near-optimal solutions at significantly reduced complexity and communication overhead. It flattens the aggregated load on the power grid and reduces the costs of both the users and the utility.
机译:随着电动汽车(EV)数量的增长,如果安排不当,其电力需求可能会对电网产生重大不利影响。在本文中,我们将EV充电系统建模为网络物理系统,并针对大量EV设计分散的在线EV充电调度算法,其中EV可能具有高度异构性,并且可以动态加入充电系统。该算法结合了基于聚类的策略(可将异构EV动态分类为多个组)和滑动窗口迭代方法,该方法可实时调度每个组中EV的充电需求。大量的仿真结果表明,我们的方法以显着降低的复杂性和通信开销提供了接近最佳的解决方案。它使电网上的总负载平坦化,并降低了用户和公用事业公司的成本。

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