LAPSE:2018.0945
Published Article
LAPSE:2018.0945
Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition
Silvano Vergura, Roberto Zivieri, Mario Carpentieri
November 27, 2018
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.
Keywords
coherence degree, Empirical Mode Decomposition, Hilbert-Huang Transform, periodicity degree, Smart Grids, Wavelet Transform
Suggested Citation
Vergura S, Zivieri R, Carpentieri M. Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition. (2018). LAPSE:2018.0945
Author Affiliations
Vergura S: Department of Electrical and Information Engineering, Politecnico di Bari, via E. Orabona 4, Bari I-70125, Italy [ORCID]
Zivieri R: 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 Fer [ORCID]
Carpentieri M: Department of Electrical and Information Engineering, Politecnico di Bari, via E. Orabona 4, Bari I-70125, Italy
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Journal Name
Energies
Volume
9
Issue
3
Article Number
E211
Year
2016
Publication Date
2016-03-17
Published Version
ISSN
1996-1073
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Original Submission
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PII: en9030211, Publication Type: Journal Article
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LAPSE:2018.0945
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doi:10.3390/en9030211
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Nov 27, 2018
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Nov 27, 2018
 
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Calvin Tsay
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