Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition
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...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2016-03-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/9/3/211 |
| _version_ | 1828113898248601600 |
|---|---|
| author | Silvano Vergura Roberto Zivieri Mario Carpentieri |
| author_facet | Silvano Vergura Roberto Zivieri Mario Carpentieri |
| author_sort | Silvano Vergura |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T12:16:16Z |
| format | Article |
| id | doaj.art-84f713b1a802470b8eda876e8ba06acc |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T12:16:16Z |
| publishDate | 2016-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-84f713b1a802470b8eda876e8ba06acc2022-12-22T04:24:18ZengMDPI AGEnergies1996-10732016-03-019321110.3390/en9030211en9030211Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode DecompositionSilvano Vergura0Roberto Zivieri1Mario Carpentieri2Department of Electrical and Information Engineering, Politecnico di Bari, via E. Orabona 4, Bari I-70125, ItalyDepartment of Electrical and Information Engineering, Politecnico di Bari, via E. Orabona 4, Bari I-70125, ItalyDepartment of Electrical and Information Engineering, Politecnico di Bari, via E. Orabona 4, Bari I-70125, ItalyThe 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.http://www.mdpi.com/1996-1073/9/3/211coherence degreeperiodicity degreeWavelet TransformEmpirical Mode DecompositionHilbert-Huang TransformSmart Grids |
| spellingShingle | Silvano Vergura Roberto Zivieri Mario Carpentieri Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition Energies coherence degree periodicity degree Wavelet Transform Empirical Mode Decomposition Hilbert-Huang Transform Smart Grids |
| title | Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition |
| title_full | Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition |
| title_fullStr | Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition |
| title_full_unstemmed | Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition |
| title_short | Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition |
| title_sort | indices to study the electrical power signals in active and passive distribution lines a combined analysis with empirical mode decomposition |
| topic | coherence degree periodicity degree Wavelet Transform Empirical Mode Decomposition Hilbert-Huang Transform Smart Grids |
| url | http://www.mdpi.com/1996-1073/9/3/211 |
| work_keys_str_mv | AT silvanovergura indicestostudytheelectricalpowersignalsinactiveandpassivedistributionlinesacombinedanalysiswithempiricalmodedecomposition AT robertozivieri indicestostudytheelectricalpowersignalsinactiveandpassivedistributionlinesacombinedanalysiswithempiricalmodedecomposition AT mariocarpentieri indicestostudytheelectricalpowersignalsinactiveandpassivedistributionlinesacombinedanalysiswithempiricalmodedecomposition |