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| Dynamic frequency estimation of wideband oscillations based on successive variational mode decomposition and an improved two-step method |
| DOI：10.19783/j.cnki.pspc.250641 |
| Key Words:wideband oscillation dynamic estimation whale optimization algorithm successive variational mode decomposition multi-synchrosqueezing transform |
| Author Name | Affiliation | | CHEN Tianfu1 | 1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
2. Department of
Electrical Engineering, Fuzhou University Zhicheng College, Fuzhou 350002, China | | GAO Wei1,2 | 1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
2. Department of
Electrical Engineering, Fuzhou University Zhicheng College, Fuzhou 350002, China | | GUO Moufa1,2 | 1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
2. Department of
Electrical Engineering, Fuzhou University Zhicheng College, Fuzhou 350002, China | | YANG Gengjie1 | 1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
2. Department of
Electrical Engineering, Fuzhou University Zhicheng College, Fuzhou 350002, China |
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| Abstract:The high penetration of renewable energy integration has exacerbated wideband oscillation problems in power systems, potentially leading to consequences such as generator tripping. The wideband and multimodal characteristics of such oscillations result in signal aliasing and non-stationarity, posing significant challenges to accurate frequency estimation. Real-time and precise frequency estimation is crucial for suppressing frequency oscillations. To address this problem, this paper proposes a dynamic frequency estimation method for wideband oscillation signals based on successive variational mode decomposition (SVMD) and an improved two-step (ITS) approach. First, the whale optimization algorithm (WOA) is introduced to adaptively determine the maximum penalty factor of SVMD, and the oscillation signal is then decomposed via SVMD into intrinsic mode functions (IMFs), effectively avoiding reliance on prior knowledge. Second, by integrating the two-step (TS) method with multi-synchrosqueezing transform (MSST), the resolution and noise immunity of frequency estimation are enhanced through phase demodulation and time-frequency spectrum refinement. Experimental results demonstrate that the IMFs decomposed by the proposed method closely resemble the oscillation components of the original signal. Furthermore, the accuracy of dynamic frequency estimation is significantly improved compared to traditional methods such as TS and Hilbert Transform, enabling effective dynamic tracking of the instantaneous frequency of oscillation signals in both simulated and measured data. |
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