Cai Dongsheng, Sun Feiyu, Li Linlin, Hu Weihao, Huang Qi
College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Sichuan 610059, China.
College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Sichuan 610059, China.
ISA Trans. 2024 Jul;150:166-180. doi: 10.1016/j.isatra.2024.05.001. Epub 2024 May 13.
As the penetration of renewable energy increases to a large scale and power electronic devices become widespread, power systems are becoming prone to synchronous oscillations (SO). This event has a major impact on the stability of the power grid. The recent research has been mainly concentrated on identifying the parameters of sub-synchronous oscillation. Sub/Super synchronous oscillations (Sub/Sup-SO) simultaneously occur, increasing the difficulty in accurately identify the parameters of SO. This work presents a novel method for parameter identification that effectively handles the Sub/Sup-SO components by utilizing the Rife-Vincent window and discrete Fourier transform (DFT) simultaneously. To mitigate the impact of spectral leakage and the fence effect of DFT, we integrate the tri-spectral interpolation algorithm with the Rife-Vincent window. We use the instantaneous data of the phasor measurement unit (PMU) to identify Sub/Sup-SO-related parameters (Sub/Sup-SO damping ratio, frequency, amplitude and phase). First, the spectrum of the Sub/Sup-SO signals is analyzed after incorporating the Rife-Vincent window, and the characteristics of the Sub/Sup-SO signal are determined. Then, the signal spectrum is identified using a three-point interpolation algorithm, and the damping ratio, amplitude, frequency, and phase of the Sub/Sup-SO signals are obtained. In addition, we consider the identification accuracy of the algorithm under various complex conditions, such as the effect of Sub/Sup-SO parameter variations on parameter identification in the presence of a non-nominal frequency and noise. The proposed algorithm accurately identifies the parameters of multiple Sub/Sup-SO components and two Sub-SO components that are in close proximity. Testing with synthetic and real data demonstrates that the proposed algorithm outperforms existing methods in terms of identification accuracy, identification bandwidth, and adaptability.
随着可再生能源大规模渗透以及电力电子设备广泛应用，电力系统越来越容易出现同步振荡（SO）。这一现象对电网稳定性有重大影响。近期研究主要集中在识别次同步振荡的参数。次同步/超同步振荡（Sub/Sup-SO）同时出现，增加了准确识别同步振荡参数的难度。本文提出一种新颖的参数识别方法，通过同时利用瑞夫-文森特窗和离散傅里叶变换（DFT）有效处理Sub/Sup-SO分量。为减轻DFT的频谱泄漏和栅栏效应的影响，我们将三谱插值算法与瑞夫-文森特窗相结合。我们使用相量测量单元（PMU）的瞬时数据来识别与Sub/Sup-SO相关的参数（Sub/Sup-SO阻尼比、频率、幅值和相位）。首先，在加入瑞夫-文森特窗后分析Sub/Sup-SO信号的频谱，确定Sub/Sup-SO信号的特征。然后，使用三点插值算法识别信号频谱，得到Sub/Sup-SO信号的阻尼比、幅值、频率和相位。此外，我们考虑了算法在各种复杂条件下的识别精度，例如在非额定频率和噪声存在时Sub/Sup-SO参数变化对参数识别的影响。所提算法能准确识别多个Sub/Sup-SO分量以及两个相邻的次同步振荡分量的参数。通过合成数据和实际数据测试表明，所提算法在识别精度、识别带宽和适应性方面优于现有方法。
