Distributed Frequency Emergency Control With Coordinated Edge Intelligence

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.