Identification Method for Wideband Oscillation Parameters Caused by Grid-Forming Renewable Energy Sources Based on Multiple Matching Synchrosqueezing Transformation

Ping Xiong, Yu Sun, Lie Li, Yifan Zhao, Xiaoqian Zhu, Shunfan He () and Ming Zhang
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Ping Xiong: State Grid Hubei Electric Power Research Institute, Wuhan 430077, China
Yu Sun: State Grid Hubei Electric Power Research Institute, Wuhan 430077, China
Lie Li: State Grid Hubei Electric Power Research Institute, Wuhan 430077, China
Yifan Zhao: State Grid Hubei Electric Power Research Institute, Wuhan 430077, China
Xiaoqian Zhu: State Grid Hubei Electric Power Research Institute, Wuhan 430077, China
Shunfan He: School of Computer Science, South-Central Minzu University, Wuhan 430074, China
Ming Zhang: School of Electronic & Electrical Engineering, Wuhan Textile University, Wuhan 430200, China

Energies, 2025, vol. 18, issue 19, 1-17

Abstract: The oscillation problem has emerged as one of the critical challenges confronting emerging power systems, particularly with the increasing penetration of grid-forming renewable energy sources. This trend can lead to the coexistence of multiple oscillation modes across a wide frequency range. To enhance the safety and stability of power systems, this paper proposes a wideband oscillation parameter identification method based on the multiple matching synchrosqueezing transform (MMSST), addressing the limitations of traditional time–frequency analysis techniques in accurately separating and extracting oscillation components during wideband parameter identification. The method first applies MMSST to decompose the measured oscillation signal into a set of intrinsic mode functions (IMFs). Subsequently, the Hilbert transform is applied to each IMF to extract the instantaneous frequency, amplitude, and initial phase, thereby achieving precise parameter identification of the oscillation signal. The validation study results demonstrate that the MMSST algorithm outperforms the empirical mode decomposition (EMD) and variational mode decomposition (VMD) algorithms in accurately extracting individual oscillation components and estimating their dynamic characteristics. Additionally, the proposed method achieves superior performance in terms of both accuracy and robustness when compared to the EMD and VMD algorithms.

Keywords: wideband oscillation; grid-forming renewable energy sources; multiple matching synchrosqueezing transformation; parameter identification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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