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Control of EV Charging Points for Thermal and Voltage Management of LV Networks

机译:控制LV网络热电电压管理的EV充电点

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摘要

High penetrations of domestic electric vehicles (EVs) in UK low voltage (LV) networks may result in significant technical problems. This paper proposes an implementable, centralized control algorithm, currently being trialed in 9 UK residential LV networks, that uses limited information to manage EV charging points to mitigate these technical problems. Two real UK LV networks are used to quantify the potential impacts of different EV penetration levels and to demonstrate the effectiveness of the control algorithm (using different control cycles) for simultaneous thermal and voltage management. Monte Carlo simulations (adopting 1-min resolution data) are undertaken to cater for domestic and EV demand uncertainties. Results for these LV networks show that problems may occur for EV penetrations higher than 20%. More importantly, they highlight that even for a 100% penetration and control cycles of up to 10 min, the control algorithm successfully mitigates problems on the examined LV networks. Crucially, to determine effects on the comfort of EV users, a metric is introduced and discussed. The results of different control settings are presented to analyze potential adaptations of the control strategy. Finally, a comparison with an optimization framework highlights that the proposed algorithm is as effective whilst using limited information.
机译:英国低压(LV)网络中的国内电动汽车(EVS)的高穿透可能导致显着的技术问题。本文提出了可实现的集中控制算法,目前在9英国住宅LV网络中试验,该算法使用有限的信息来管理EV充电点以减轻这些技术问题。两个真正的英国LV网络用于量化不同EV渗透水平的潜在影响,并展示控制算法(使用不同控制循环)同时热电和电压管理的有效性。蒙特卡罗模拟(采用1分钟的分辨率数据),以满足国内和EV需求的不确定性。这些LV网络的结果表明,对于高于20%的EV渗透可能会出现问题。更重要的是,它们突出显示,即使对于100%的渗透和控制周期,最多10分钟,控制算法也成功地减轻了检查的LV网络上的问题。至关重要的是,为了确定对EV用户的舒适性的影响,介绍并讨论了一个度量。提出了不同控制设置的结果,以分析控制策略的潜在调整。最后,与优化框架的比较突出显示所提出的算法在使用有限信息时具有有效。

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