基于AVMD-ITKEO算法的次/超同步振荡辨识  

An AVMD-ITKEO Method Based Identification of Subsynchronous/Supsynchronous Oscillation

作　　者：张浙波 林玮 杨磊 刘树[5] 张彬[5] 常富杰 ZHANG Zhebo;LIN Wei;YANG Lei;LIU Shu;ZHANG Bin;CHANG Fujie

机构地区：[1]浙江浙能技术研究院有限公司,浙江杭州311121 [2]浙江省火力发电高效节能与污染物控制技术研究重点实验室,浙江杭州311121 [3]浙江浙能嘉兴海上风力发电有限公司,浙江嘉兴314200 [4]浙江大学电气工程学院,浙江杭州310027 [5]北京四方继保自动化股份有限公司,北京100085

出　　处：《电力系统装备》2024年第6期79-83,共5页Electric Power System Equipment

基　　金：浙江省自然科学基金项目(LY23E070002);浙能集团科技项目(ZNKJ-2022-078)。

摘　　要：针对大规模风电系统中可能出现的次/超同步振荡问题,文章提出了一种改进Teager-Kaiser能量算子算法和自适应变分模态分解算法,通过将这两种算法相结合实现了次/超同步振荡模态参数的准确辨识。首先,通过改进的万有引力算法最小化包络信息熵,求解最优模态分量数与惩罚因子;然后,进行变分模态分解以获得各主导模态;之后,再通过改进的Teager-Kaiser算法辨识各主导模态的参数;最后,通过辨识模拟信号和实际电网数据并与其他算法进行对比,验证了文章所提振荡参数辨识算法的有效性和优越性。In order to solve the potential problem of subsynchronous/supsynchronous oscillation(SSO)caused by large-scale wind power systems,an improved Teager-Kaiser energy oper-ator(ITKEO)algorithm combined with adaptive variational mode decomposition(VMD)is proposed to achieve the accurate identification of the parameters of SSO.Firstly,an improved gravitation search algorithm was used to minimize the envelope information entropy for obtaining the optimal modal component number and penalty factor,then the VMD was used to obtain the intrinsic mode function(IMF).Then,the parameters of each IMF are identified by the ITKEO algorithm.Finally,the validity and superiority of the proposed method are tested and verified by identifying the analog signal and the actual network data and comparing with other algorithms.

关 键 词：风电系统 次/超同步振荡 自适应变分模态分解 最小包络信息熵 改进Teager-Kaiser能量算子 

分 类 号：TM712[电气工程—电力系统及自动化]