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Distributed frequency emergency control with coordinated edge intelligence

机译:分布式频率应急控制与协调边缘智能

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摘要

Developing effective strategies to arrest grid frequency drop in case of severe contingencies is an important requirement. While distributed responsive loads for primary frequency control have been studied in the literature, the coordination of the distributed loads relies on high-speed communication or centralized frequency threshold setting. They might be cost-prohibitive or not sufficiently fast in severe contingencies, like the fault of ultrahigh voltage direct current (UHVDC) lines in China. In this paper, a local power loss increment P estimation approach for frequency emergency control is proposed, and the coordination of the distributed loads is achieved by the edge intelligence and Internet-of-Things (IoT) technologies. The proposed approach can enable the distributed loads to provide fast and accurate frequency support to power grids. The parameter-setting in the control center and decision-making at the edge level for the proposed approach are described in detail. Based on a typical IEEE test system and a real bulk power system in China, numerical simulations and hardware experiments are conducted to verify the frequency support performance of the proposed approach. Further, a direct load frequency control system named Grid Sense implemented in China is explicitly described, and the real-world issues for implementing the proposed approach are analyzed.
机译:在严重的情况下,制定逮捕网格频率下降的有效策略是一个重要要求。在文献中研究了用于初级频率控制的分布式敏感载荷,而分布式负载的协调依赖于高速通信或集中频率阈值设置。它们可能是在严重的突发事件中经济高速或不够快速的速度,如中国的超高压直流(UHVDC)线的故障。本文提出了一种频率紧急控制的局部功率损耗增量P估计方法,并通过边缘智能和互联网(物联网)技术实现了分布式负载的协调。所提出的方法可以使分布式负载能够为电网提供快速准确的频率支持。详细描述了所提出方法的控制中心和决策中的参数设置。基于典型的IEEE测试系统和中国的真正散装电力系统,进行了数值模拟和硬件实验,以验证所提出的方法的频率支持性能。此外,明确描述了在中国实施的指定网格感的直接载荷频率控制系统,分析了实现所提出的方法的现实世界问题。

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