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arXiv 1706.10074eess.SYcs.SY
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低压配电网中分布式电动汽车网络效用最大化的影响

On the Effects of Distributed Electric Vehicle Network Utility Maximization in Low Voltage Feeders

Technical University Munich(慕尼黑工业大学)

Jose Rivera, Hans Arno Jacobsen

AI总结:

本文研究了在低压配电网中实施基于网络效用最大化的电动汽车充电控制算法的影响,验证了其在捕捉运营约束方面的有效性,并显示了对偶解在防止系统过载方面的优势。

摘要:

电动汽车在配电网络中的快速充电需要实时充电控制以避免电网组件过载。近期研究提出了基于网络效用最大化(NUM)问题的分布式优化解决方案作为拥堵控制协议。虽然NUM公式允许定义具有闭式解的分布式计算,但其简单模型未考虑许多配电网的操作约束。本文研究了在低压配电网中实施此类算法进行拥堵控制的影响。我们回顾了最新的基于NUM的实时电动汽车充电控制算法,并评估了它们在全面的IEEE欧洲低压测试配电网中的行为和影响。结果表明,只要载流限制违规是主要瓶颈,电动汽车NUM问题可以有效捕捉相关运营约束。此外,结果还显示了对偶NUM解在防止系统过载方面的优势。

英文摘要:

The fast charging of Electric Vehicles (EVs) in distribution networks requires real-time EV charging control to avoid the overloading of grid components. Recent studies have proposed congestion control protocols, which result from distributed optimization solutions of the Network Utility Maximization (NUM) problem. While the NUM formulation allows the definition of distributed computations with closed form solutions, its simple model does not account for many of the feeders operational constraints. This puts the resulting control algorithms effectiveness into question. In this paper, we investigate the impact of implementing such algorithms for congestion control in low voltage feeders. We review the latest NUM based algorithms for real-time EV charging control, and evaluate their behavior and impact on the comprehensive IEEE European Low Voltage Test Feeder. Our results show that the EV NUM problem can effectively capture the relevant operational constraints, as long as ampacity violations are the main bottleneck. Moreover, the results demonstrate an advantage of the primal NUM solution over the more conventional dual NUM solution in preventing a system overload.

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。

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