Electromagnetic dynamic stability analysis of power electronics-dominated systems using eigenstructure-preserved LTP Theory

Jiabing Hu (), Zeren Guo, Jianhang Zhu (), Jürgen Kurths, Yunhe Hou, Buyang Du, Zefei Wu, Guojie Zhao, Yunfeng Liu, Kai Xin, Jianbo Guo and Shijie Cheng
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Jiabing Hu: Huazhong University of Science and Technology
Zeren Guo: Huazhong University of Science and Technology
Jianhang Zhu: The University of Hong Kong
Jürgen Kurths: Humboldt-University
Yunhe Hou: The University of Hong Kong
Buyang Du: Huazhong University of Science and Technology
Zefei Wu: Huazhong University of Science and Technology
Guojie Zhao: Huazhong University of Science and Technology
Yunfeng Liu: Ltd
Kai Xin: Ltd
Jianbo Guo: China Electric Power Research Institute
Shijie Cheng: Huazhong University of Science and Technology

Nature Communications, 2025, vol. 16, issue 1, 1-10

Abstract: Abstract 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.

Date: 2025
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DOI: 10.1038/s41467-025-62183-1

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