Application of the Variational Mode Decomposition for Power Quality Analysis


Harmonics and interharmonics in power systems distort the grid voltage, deteriorate the quality and stability of the power grid. Therefore, rapid and accurate harmonic separation from the grid voltage is crucial to power system. In this article, a variational mode decomposition-based method is proposed to separate harmonics and interharmonics in the grid voltage. The method decomposes the voltage signal into fundamental, harmonic, interharmonic components through the frequency spectrum. An empirical mode decomposition (EMD) and an ensemble empirical mode decomposition (EEMD) can be combined with the independent component analysis (ICA) to analyze the harmonics and intherharmonics. By comparing EMD-ICA, EEMD-ICA methods, the proposed method has several advantages: (1) a higher correlation coefficient of all the components is found; (2) it requires much less time to accomplish signal separation; (3) amplitude, frequency, and phase angle are all retained by this method. The results obtained from both synthetic and real-life signals demonstrate the good performance of the proposed method.

Publication DOI:
Divisions: College of Engineering & Physical Sciences
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Electric Power Components and Systems on 12 Feb 2019, available online at: Funding: The authors gratefully acknowledge the support of the Foundation of Liaoning Province Education Administration (grant number L201609), the Doctoral Start-up Foundation of Liaoning Province (grant number 20170520191) and the Royal Society U.K
Uncontrolled Keywords: EEMD-ICA,EMD-ICA,harmonics,interharmonics,power system,variational mode decomposition (VMD),Energy Engineering and Power Technology,Mechanical Engineering,Electrical and Electronic Engineering
Publication ISSN: 1532-5016
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.tan ... 08.2018.1563960 (Publisher URL)
PURE Output Type: Article
Published Date: 2019-02-12
Accepted Date: 2018-12-01
Authors: Cai, Kewei
Cao, Wenping (ORCID Profile 0000-0002-8133-3020)
Liu, Zheng
Wang, Wei
Li, Guofeng



Version: Accepted Version

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