基于广义变分模态分解的低频及超低频振荡模态辨识  

Low Frequency Oscillation and Ultra-low Frequency Oscillation Modes Identification Based on Generalized Variational Mode Decompostion

作　　者：孙方亮 张虹[2] 张作有 SUN Fangliang;ZHANG Hong;ZHANG Zuoyou(State Grid Anshan Power Supply Company,Anshan 114000,Liaoling,China;Northeast Electric Power University,Jilin 132000,Jilin,China)

机构地区：[1]国网鞍山供电公司,辽宁鞍山114000 [2]东北电力大学,吉林吉林132000

出　　处：《电力大数据》2024年第5期27-36,共10页Power Systems and Big Data

基　　金：吉林省科技发展计划重点科技研发资助项目(20240302094GX)。

摘　　要：随着水电渗透率以及电网互联规模不断扩大,在水电高占比电网中出现了低频及超低频振荡现象,表现为强非线性非平稳特征,增加了振荡参数辨识的难度。针对变分模态分解(variational mode decomposition,VMD)中模态分解数K无法自适应确定以及处理时变振荡易产生模态混叠的问题,提出基于广义变分模态分解(generalized variational mode decompostion,GVMD)算法,结合Teager-Kaiser能量算子(Teager-Kaiser energy operator,TKEO)对低频及超低频振荡进行快速模态参数辨识。首先GVMD根据小波时频分析得到模态分解数K,通过广义傅里叶变换使各个模态在时频面界定清晰,从而使分解精度和可靠性大幅提升。然后对信号进行GVMD分解处理,再利用TKEO法快速完成振荡参数辨识。最后通过自合成信号、EPRI-36系统仿真和实测电网信号仿真验证了所提方法的有效性和可行性。With the continuous expansion of hydropower penetration and grid interconnection scale,low-frequency and ultra-low frequency oscillations appear in power grids with high proportion of hydropower,which shows strong nonlinear and non-stationary characteristics,and consequently increases the difficulty of oscillation parameter identification.Aiming at the problem that the mode decomposition number K in variational mode decomposition(VMD)cannot be adaptively determined and that mode aliasing is easy to occur when dealing with time-varying oscillations,a generalized variational mode decomposition(GVMD)algorithm combined with Teager-Kaiser Energy Operator(TKEO)is proposed for fast modal parameter identification of low-frequency and ultra-low-frequency oscillations.Firstly,the modal decomposition number K is obtained through wavelet time-frequency analysis,and each mode is clearly defined in the time-frequency plane through generalized Fourier transform,so that the decomposition accuracy and reliability are greatly improved.Then,after the signal is decomposed by GVMD,the TKEO method is used to quickly complete the identification of oscillation parameters.Finally,the effectiveness and feasibility of the proposed method are verified by self-synthesized signal,EPRI-36 system simulation and measured power grid signal simulation.

关 键 词：水电高占比 超低频振荡 广义变分模态分解 Teager-Kaiser能量算子 模态辨识 

分 类 号：TM712[电气工程—电力系统及自动化]