Fourier, Wavelet, and Hilbert-Huang Transforms for Studying Electrical Users in the Time and Frequency Domain

Vito Puliafito, Silvano Vergura and Mario Carpentieri
Additional contact information
Vito Puliafito: Department of Engineering, University of Messina, I-98166 Messina, Italy
Silvano Vergura: Department of Electrical and Information Engineering, Polytechnic University of Bari, via E. Orabona 4, I-70125 Bari, Italy
Mario Carpentieri: Department of Electrical and Information Engineering, Polytechnic University of Bari, via E. Orabona 4, I-70125 Bari, Italy

Energies, 2017, vol. 10, issue 2, 1-14

Abstract: The analysis of electrical signals is a pressing requirement for the optimal design of power distribution. In this context, this paper illustrates how to use a variety of numerical tools, such as the Fourier, wavelet, and Hilbert-Huang transforms, to obtain information relating to the active and reactive power absorbed by different types of users. In particular, the Fourier spectrum gives the most important frequency components of the electrical signals, and the wavelet analysis highlights the non-stationarity of those frequency contributions, whereas the Hilbert-Huang transform, by means of the Empirical Mode Decomposition, provides a more complete spectrum of frequencies.

Keywords: non-stationary signal; time-frequency analysis; power quality; wavelet; Hilbert-Huang transform (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/2/188/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/2/188/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:10:y:2017:i:2:p:188-:d:89743

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().