Method based on independent component analysis for harmonic extraction from power system signals

Ferreira, Danton Diego; Nagata, Erick A.; Ferreira, Sindynara; Seixas, J. M.; Duque, Carlos A.; Marques, Charles Henrique Dias; Guedes, Juan Diego Silva; Cerqueira, A. S.

doi:10.1016/j.epsr.2014.09.001

Cited by 23 publications

(15 citation statements)

References 9 publications

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“…But both techniques are limited in a fixed window length and come with heavy computation. Alternative algorithms are discrete wavelet transform , empirical mode decomposition (EMD) , and single channel independent component analysis . In , the authors managed to use different time‐frequency‐domain and time‐domain techniques to decompose voltage or current signals into several harmonics and disturbances and analyze each of them one by one.…”

Section: Introductionmentioning

confidence: 99%

“…How to separate out independent sources from a single time series has been the focus of researchers. The selection of proper number of filter banks in and or the delay dimension in and Euclidean embedding dimension in are similar approaches to generate multidimensional data for standard independent component analysis. The delay dimension or the Euclidean embedding dimension is the number of multiple signals that is generated from a single measured power signal.…”

Section: Introductionmentioning

confidence: 99%

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A time-domain statistical approach for harmonics separation and analysis

Shu

Liu

et al. 2016

Int. Trans. Electr. Energ. Syst.

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The paper proposes a novel time-domain statistical method to separate and analyze harmonics based on single channel analysis and principal component analysis. The proposed method separates the fundamental wave and harmonics to provide specific time-domain information. Two identification methods are proposed to estimate the number of harmonics within the power system signal, even with high noise. This paper validates the effectiveness of the proposed method through mathematical deduction and studies the selection of Euclidean embedding dimension. The robustness of the proposed method is tested on several simulated synthetic signals and a real-world signal. Simulation results show that the proposed method can detect harmonics with small amplitude in the presence of noise and has better separated waveform and less execution time than wavelet-packet transform and empirical mode decomposition. It is also shown that the proposed method can detect sudden voltage changes and separate disturbances.On the basis of this complex exponential model, the next section discusses a time-domain statistical way to separate harmonics and recover their time-domain waveform. C. HE ET AL.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A time-domain statistical approach for harmonics separation and analysis

Shu

Liu

et al. 2016

Int. Trans. Electr. Energ. Syst.

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“…Regarding ICA applications for PQ analysis, authors in , , and developed ICA‐based methods to estimate harmonic components from voltage signals in which promising results have been reported. ICA is a statistical signal‐processing technique that separates a multivariate signal into additive independent component sources.…”

Section: Introductionmentioning

confidence: 99%

Extracting the transient events from power system signals by independent component analysis

Ferreira

Seixas

Cerqueira

et al. 2015

Int. Trans. Electr. Energ. Syst.

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Summary This paper presents a method for extracting transient events from the power system signal based on independent component analysis. The extraction of transients is important to diagnose the system in terms of power quality, because the computation of power quality indices from the extracted events is more efficient and easier to be carried out. Furthermore, the proposed method can be applied as a preprocessing tool for transient characterization in disturbance detection, classification, and identification systems. Both qualitative and quantitative analyses demonstrate the efficiency and the advantages of the proposed method in comparison with other approaches commonly used for the same purpose. Copyright © 2015 John Wiley & Sons, Ltd.

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“…Apparently, the interharmonics are due to the difference between the generator-side and the grid-side frequencies of the full-power converter. Ferreira et al [9] proposed a technique of independent component analysis for extracting harmonics from electrical signals; the method is tested using real power signals and non-linear loads to demonstrate adequacy for real-case applications. On the other hand, several studies are dedicated to analyzing the power consumption estimation in public or residential buildings through the use of acquired data by common commercial equipment in diverse time periods for: days, weeks, or even a year.…”

Section: Introductionmentioning

confidence: 99%

Power Consumption Analysis of Electrical Installations at Healthcare Facility

et al. 2017

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This paper presents a methodology for power consumption estimation considering harmonic and interharmonic content and then it is compared to the power consumption estimation commonly done by commercial equipment based on the fundamental frequency, and how they can underestimate the power consumption considering power quality disturbances (PQD). For this purpose, data of electrical activity at the electrical distribution boards in a healthcare facility is acquired for a long time period with proprietary equipment. An analysis in the acquired current and voltage signals is done, in order to compare the power consumption centered in the fundamental frequency with the generalized definition of power consumption. The results obtained from the comparison in the power consumption estimation show differences between 4% and 10% of underestimated power consumption. Thus, it is demonstrated that the presence of harmonic and interharmonic content provokes a significant underestimation of power consumption using only the power consumption centered at the fundamental frequency.

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Method based on independent component analysis for harmonic extraction from power system signals

Cited by 23 publications

References 9 publications

A time-domain statistical approach for harmonics separation and analysis

A time-domain statistical approach for harmonics separation and analysis

Extracting the transient events from power system signals by independent component analysis

Power Consumption Analysis of Electrical Installations at Healthcare Facility

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