Identification of electromechanical oscillatory modes based on variational mode decomposition

被引:48
|
作者
Arrieta Paternina, Mario R. [1 ]
Tripathy, Rajesh Kumar [2 ]
Zamora-Mendez, Alejandro [3 ]
Dotta, Daniel [4 ]
机构
[1] Natl Autonomous Univ Mexico UNAM, Mexico City 04510, DF, Mexico
[2] Birla Inst Technol & Sci BITS Pilani, Hyderabad 500078, India
[3] Michoacan Univ St Nicholas Hidalgo UMSNH, Morelia 58030, Mich, Mexico
[4] Univ Estadual Campinas, BR-13083852 Campinas, SP, Brazil
基金
巴西圣保罗研究基金会;
关键词
Variational mode decomposition; Electromechanical modes; Power oscillations; Signal decomposition; Hilbert transform;
D O I
10.1016/j.epsr.2018.10.014
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper introduces Variational Mode Decomposition (VMD) to identify electromechanical oscillatory modes in power systems. The identification process is based on the time-frequency analysis of nonlinear signals which arise after a large disturbance. VMD provides signal decomposition to convert the oscillatory power signal into mono-component signals or modes. This analysis is accomplished by an optimal and recursive statement in time frequency, yielding the modes and reconstructed signal estimates, and providing information on their instantaneous modal characteristics such as amplitude, frequency, damping and energy, via Hilbert transform. The results demonstrate the applicability of the proposition in both theoretical and a real wide-area monitoring system.
引用
收藏
页码:71 / 85
页数:15
相关论文
共 50 条
  • [1] Dominant Electromechanical Oscillation Mode Identification using Modified Variational Mode Decomposition
    Rahul S
    Sunitha R
    [J]. Arabian Journal for Science and Engineering, 2021, 46 : 10007 - 10021
  • [2] Dominant Electromechanical Oscillation Mode Identification using Modified Variational Mode Decomposition
    Rahul, S.
    Sunitha, R.
    [J]. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2021, 46 (10) : 10007 - 10021
  • [3] Extracting Modes From Electromechanical Oscillation Signals for Power System Based on Adaptive Variational Mode Decomposition
    Wang L.
    Cai G.
    Yang D.
    Sun Z.
    [J]. Dianwang Jishu/Power System Technology, 2019, 43 (04): : 1387 - 1395
  • [4] Modal parameter identification based on variational mode decomposition
    Zhao Y.
    Dou Y.
    Zhang M.
    [J]. Zhendong yu Chongji/Journal of Vibration and Shock, 2020, 39 (02): : 115 - 122
  • [5] Structural system identification based on variational mode decomposition
    Bagheri, Abdollah
    Ozbulut, Osman E.
    Harris, Devin K.
    [J]. JOURNAL OF SOUND AND VIBRATION, 2018, 417 : 182 - 197
  • [6] Electromechanical Modes Identification Based on an Iterative Eigenvalue Decomposition of the Hankel Matrix
    Zamora-Mendez, Alejandro
    de Luna, Rodrigo D. Reyes
    de la O Serna, Jose Antonio
    Chow, Joe H.
    Paternina, Mario R. Arrieta
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2023, 38 (01) : 155 - 167
  • [7] Early chatter identification based on an optimized variational mode decomposition
    Yang, Kai
    Wang, Guofeng
    Dong, Yi
    Zhang, Quanbiao
    Sang, Lingling
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2019, 115 : 238 - 254
  • [8] Channel identification with Improved Variational Mode Decomposition
    Baldini, Gianmarco
    Bonavitacola, Fausto
    [J]. PHYSICAL COMMUNICATION, 2022, 55
  • [9] Variational mode decomposition based modal parameter identification in civil engineering
    Zhang, Mingjie
    Xu, Fuyou
    [J]. FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING, 2019, 13 (05) : 1082 - 1094
  • [10] Radiometric identification using variational mode decomposition
    Baldini, Gianmarco
    Steri, Gary
    Giuliani, Raimondo
    Dimc, Franc
    [J]. COMPUTERS & ELECTRICAL ENGINEERING, 2019, 76 : 364 - 378