IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v9y2016i3p211-d65977.html
   My bibliography  Save this article

Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition

Author

Listed:
  • Silvano Vergura

    (Department of Electrical and Information Engineering, Politecnico di Bari, via E. Orabona 4, Bari I-70125, Italy)

  • Roberto Zivieri

    (Department of Electrical and Information Engineering, Politecnico di Bari, via E. Orabona 4, Bari I-70125, Italy
    Department of Physics and Earth Sciences and Consorzio Nazionale Interuniversitario per le Scienze Fisiche Unit of Ferrara, University of Ferrara, via Saragat 1, Ferrara I-44122, Italy
    These authors contributed equally to this work.)

  • Mario Carpentieri

    (Department of Electrical and Information Engineering, Politecnico di Bari, via E. Orabona 4, Bari I-70125, Italy
    These authors contributed equally to this work.)

Abstract

The broad diffusion of renewable energy-based technologies has introduced several open issues in the design and operation of smart grids (SGs) when distributed generators (DGs) inject a large amount of power into the grid. In this paper, a theoretical investigation on active and reactive power data is performed for one active line characterized by several photovoltaic (PV) plants with a great amount of injectable power and two passive lines, one of them having a small peak power PV plant and the other one having no PV power. The frequencies calculated via the empirical mode decomposition (EMD) method based on the Hilbert-Huang transform (HHT) are compared to the ones obtained via the fast Fourier transform (FFT) and the wavelet transform (WT), showing a wider spectrum of significant modes mainly due to the non-periodical behavior of the power signals. The results obtained according to the HHT-EMD analysis are corroborated by the calculation of three new indices that are computed starting from the electrical signal itself and not from the Hilbert spectrum. These indices give the quantitative deviation from the periodicity and the coherence degree of the power signals, which typically deviate from the stationary regime and have a nonlinear behavior in terms of amplitude and phase. This information allows to extract intrinsic features of power lines belonging to SGs and this is useful for their optimal operation and planning.

Suggested Citation

  • Silvano Vergura & Roberto Zivieri & Mario Carpentieri, 2016. "Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition," Energies, MDPI, vol. 9(3), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:3:p:211-:d:65977
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/9/3/211/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/9/3/211/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vito Puliafito & Silvano Vergura & Mario Carpentieri, 2017. "Fourier, Wavelet, and Hilbert-Huang Transforms for Studying Electrical Users in the Time and Frequency Domain," Energies, MDPI, vol. 10(2), pages 1-14, February.
    2. Cui, Jia & Yu, Renzhe & Zhao, Dongbo & Yang, Junyou & Ge, Weichun & Zhou, Xiaoming, 2019. "Intelligent load pattern modeling and denoising using improved variational mode decomposition for various calendar periods," Applied Energy, Elsevier, vol. 247(C), pages 480-491.
    3. Misael Lopez-Ramirez & Luis Ledesma-Carrillo & Eduardo Cabal-Yepez & Carlos Rodriguez-Donate & Homero Miranda-Vidales & Arturo Garcia-Perez, 2016. "EMD-Based Feature Extraction for Power Quality Disturbance Classification Using Moments," Energies, MDPI, vol. 9(7), pages 1-15, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:9:y:2016:i:3:p:211-:d:65977. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.