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Adaptive Harmonic Detection of Active Power Filter based on Improved VMD
ID：556 View Protection：ATTENDEE Updated Time：2022-05-22 09:40:26 Hits：377 Poster Presentation

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Abstract
Harmonic detection accuracy is the key factor affecting the performance of active power filter (APF). As an effective harmonic detection method, any complex signal can be adaptively decomposed into several intrinsic mode functions (IMFs) with a certain bandwidth by Variational Mode Decomposition (VMD). Aiming at the problems that VMD will be affected under the background of strong noise and the parameters are difficult to determine, an adaptive harmonic detection method based on twice VMD is proposed in this paper. Firstly, the proposed method uses VMD with a fixed decomposition layer K of 2 for denoising. Secondly, the VMD parameters are optimized from the perspective of IMF energy, and the second VMD decomposition is performed on the denoised signal. The simulation results show that, compared with EMD, EEMD and VMD, the proposed method can not only effectively reduce the fundamental extraction error, but also be suitable for aperiodic and non-stationary signals. It shows that the harmonic detection accuracy of APF can be effectively improved by this method
 
Keywords
Active power filter (APF); variational mode decomposition (VMD); decomposition level; energy loss
Speaker
WenjieHuang
Huaqiao University

Wenjie Huang was born in Fujian, China. He received the B.S. degree in College of Marine Engineering, Jimei University, Fujian, China, in 2020. He is currently working toward the M.S. degree in College of Information Science and Engineering, Huaqiao University, Fujian, China. He has worked on the electric drive and power conversion technology.

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Important Date

  • Conference Date

    May 27

    2022

    to

    May 29

    2022

  • Feb 28 2022

    Draft paper submission deadline

  • May 29 2022

    Registration deadline

  • Jun 22 2022

    Contribution Submission Deadline

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IEEE Beijing Section
China Electrotechnical Society
Southeast University
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IEEE Nanjing Section
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