Hu Jiabing, Guo Zeren, Zhu Jianhang, Kurths Jürgen, Hou Yunhe, Du Buyang, Wu Zefei, Zhao Guojie, Liu Yunfeng, Xin Kai, Guo Jianbo, Cheng Shijie
State Key Laboratory of Advanced Electromagnetic Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, China.
Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, SAR, China.
Nat Commun. 2025 Jul 25;16(1):6852. doi: 10.1038/s41467-025-62183-1.
Secure operation of power systems, one of the largest man-made systems, is crucial for economic development and societal well-being. Over the past century, initiatives like Europe's Super Grid and China's Dual Carbon plan have driven significant changes in power systems, leading to the widespread integration of diverse power electronic equipment. This has resulted in the emergence of power electronics-dominated power systems. However, they have experienced multiple electromagnetic oscillation accidents, causing large-scale renewable energy disconnections and even power equipment damage. To address these critical stability issues, now a global concern, the prevalent method relies on linear time-invariant approximate modeling, i.e., the eigenstructure-reconfiguration framework. While effective, it is limited by the curse of dimensionality in large-scale systems. Recently, the linear time-periodic theory has shown potential in accelerating calculations, but its analysis methods remain underdeveloped. In response to these challenges, we propose here a generalized linear time-periodic participation factor and sensitivity theory within the eigenstructure-preserved framework. This proposed participation factor significantly improves computational efficiency, outperforming eigenstructure-reconfiguration methods by orders of magnitude. Additionally, the proposed sensitivity analysis overcomes the lack of its analyticity. The potential of our methods is demonstrated through real-world power systems of China.
电力系统作为最大的人造系统之一,其安全运行对经济发展和社会福祉至关重要。在过去的一个世纪里,诸如欧洲超级电网和中国双碳计划等举措推动了电力系统的重大变革,促使各种电力电子设备广泛集成。这导致了以电力电子为主导的电力系统的出现。然而,它们经历了多次电磁振荡事故,造成大规模可再生能源脱网甚至电力设备损坏。为了解决这些目前全球关注的关键稳定性问题,普遍采用的方法依赖于线性时不变近似建模,即特征结构重构框架。虽然有效,但它受到大规模系统维数灾难的限制。最近,线性时间周期理论在加速计算方面显示出潜力,但其分析方法仍不完善。针对这些挑战,我们在此提出一种在特征结构保留框架内的广义线性时间周期参与因子和灵敏度理论。所提出的参与因子显著提高了计算效率,比特征结构重构方法性能提升了几个数量级。此外,所提出的灵敏度分析克服了其缺乏解析性的问题。我们的方法的潜力通过中国的实际电力系统得到了证明。