智能电网中电动汽车在线充电调度算法综述
Online Charging Scheduling Algorithms of Electric Vehicles in Smart Grid: An Overview
AI总结：
本文综述了智能电网中电动汽车充电调度算法，探讨了未来事件不确定性对调度算法设计的影响，并展望了未来研究方向。
摘要：
作为传统燃油车辆的环保替代品，电动汽车（EVs）及其组件已被全球广泛开发和部署。将大量电动汽车接入电网既给系统性能带来了挑战也带来了机遇。一方面，电动汽车充电带来的负荷需求对电网的稳定性和效率产生巨大影响。另一方面，电动汽车有可能作为移动储能系统，提高电力网络性能，例如负载平抑、快速频率控制以及促进可再生能源整合。显然，未经控制的电动汽车充电可能导致电力网络运行低效甚至引发安全问题。这促使了大量研究兴趣，致力于设计充电协调机制。这里的关键设计挑战在于缺乏对未来事件的完整知识。事实上，对未来事件的知识量显著影响高效充电控制算法的设计。本文重点介绍了处理不同程度未来知识不确定性和随机性的在线电动汽车充电调度技术。此外，我们还强调了电动汽车充电控制的有前途的研究方向。
英文摘要：
As an environment-friendly substitute for conventional fuel-powered vehicles, electric vehicles (EVs) and their components have been widely developed and deployed worldwide. The large-scale integration of EVs into power grid brings both challenges and opportunities to the system performance. On one hand, the load demand from EV charging imposes large impact on the stability and efficiency of power grid. On the other hand, EVs could potentially act as mobile energy storage systems to improve the power network performance, such as load flattening, fast frequency control, and facilitating renewable energy integration. Evidently, uncontrolled EV charging could lead to inefficient power network operation or even security issues. This spurs enormous research interests in designing charging coordination mechanisms. A key design challenge here lies in the lack of complete knowledge of events that occur in the future. Indeed, the amount of knowledge of future events significantly impacts the design of efficient charging control algorithms. This article focuses on introducing online EV charging scheduling techniques that deal with different degrees of uncertainty and randomness of future knowledge. Besides, we highlight the promising future research directions for EV charging control.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
