Direct neural method for harmonic currents estimation using adaptive linear element

•The developed algorithms are implemented in Dspace board.•The neural method can estimate the harmonic terms individually.•The direct neural method can be applied for three-phase and single-phase loads.•The extracted harmonic current by direct neural method is identical to the real harmonic current....

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Published inElectric power systems research Vol. 152; pp. 61 - 70
Main Authors Merabet, L., Saad, S., Abdeslam, D. Ould, Merckle, J.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.11.2017
Elsevier Science Ltd
Elsevier
Subjects
Online AccessGet full text
ISSN0378-7796
1873-2046
1873-2046
DOI10.1016/j.epsr.2017.06.018

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Abstract •The developed algorithms are implemented in Dspace board.•The neural method can estimate the harmonic terms individually.•The direct neural method can be applied for three-phase and single-phase loads.•The extracted harmonic current by direct neural method is identical to the real harmonic current. The use of nonlinear loads has increased in power systems consequently the harmonic currents have also increased causing detrimental effects to the supply system and user equipment. The aim of the present paper is to identify harmonics in order to obtain a perfect compensation by active power filter (APF). A study of harmonic currents identification by two different methods is conducted in this work. The instantaneous power (PQ) theory method requires two low-pass filters for the extraction of direct power components from total power components. However the direct neural method based on ADALINE neural network method estimates total harmonic current as well as harmonic components separately. Moreover, the identification of each component separately enables the selective compensation of harmonics by the active filter if the objective is to minimize the cost. The method is easy to implement in real time compared to PQ method. In present paper two algorithms based on conventional PQ method and direct neural method were developed in order to identify the harmonic currents. These developed algorithms are confirmed by experimental tests by implementing these techniques in a dSPACE controller in order to show their effectiveness. The obtained results are compared, discussed and analyzed.
AbstractList •The developed algorithms are implemented in Dspace board.•The neural method can estimate the harmonic terms individually.•The direct neural method can be applied for three-phase and single-phase loads.•The extracted harmonic current by direct neural method is identical to the real harmonic current. The use of nonlinear loads has increased in power systems consequently the harmonic currents have also increased causing detrimental effects to the supply system and user equipment. The aim of the present paper is to identify harmonics in order to obtain a perfect compensation by active power filter (APF). A study of harmonic currents identification by two different methods is conducted in this work. The instantaneous power (PQ) theory method requires two low-pass filters for the extraction of direct power components from total power components. However the direct neural method based on ADALINE neural network method estimates total harmonic current as well as harmonic components separately. Moreover, the identification of each component separately enables the selective compensation of harmonics by the active filter if the objective is to minimize the cost. The method is easy to implement in real time compared to PQ method. In present paper two algorithms based on conventional PQ method and direct neural method were developed in order to identify the harmonic currents. These developed algorithms are confirmed by experimental tests by implementing these techniques in a dSPACE controller in order to show their effectiveness. The obtained results are compared, discussed and analyzed.
The use of nonlinear loads has increased in power systems consequently the harmonic currents have alsoincreased causing detrimental effects to the supply system and user equipment. The aim of the presentpaper is to identify harmonics in order to obtain a perfect compensation by active power filter (APF).A study of harmonic currents identification by two different methods is conducted in this work. Theinstantaneous power (PQ) theory method requires two low-pass filters for the extraction of direct powercomponents from total power components. However the direct neural method based on ADALINE neuralnetwork method estimates total harmonic current as well as harmonic components separately. Moreover,the identification of each component separately enables the selective compensation of harmonics by theactive filter if the objective is to minimize the cost. The method is easy to implement in real time comparedto PQ method.In present paper two algorithms based on conventional PQ method and direct neural method weredeveloped in order to identify the harmonic currents. These developed algorithms are confirmed byexperimental tests by implementing these techniques in a dSPACE controller in order to show theireffectiveness. The obtained results are compared, discussed and analyzed.
The use of nonlinear loads has increased in power systems consequently the harmonic currents have also increased causing detrimental effects to the supply system and user equipment. The aim of the present paper is to identify harmonics in order to obtain a perfect compensation by active power filter (APF). A study of harmonic currents identification by two different methods is conducted in this work. The instantaneous power (PQ) theory method requires two low-pass filters for the extraction of direct power components from total power components. However the direct neural method based on ADALINE neural network method estimates total harmonic current as well as harmonic components separately. Moreover, the identification of each component separately enables the selective compensation of harmonics by the active filter if the objective is to minimize the cost. The method is easy to implement in real time compared to PQ method. In present paper two algorithms based on conventional PQ method and direct neural method were developed in order to identify the harmonic currents. These developed algorithms are confirmed by experimental tests by implementing these techniques in a dSPACE controller in order to show their effectiveness. The obtained results are compared, discussed and analyzed.
Author Merckle, J.
Saad, S.
Abdeslam, D. Ould
Merabet, L.
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Keywords ADALINE neural network
Active power filter
Harmonics currents
LMS algorithm
p–q theory
Power systems
Fourier series
Language English
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Snippet •The developed algorithms are implemented in Dspace board.•The neural method can estimate the harmonic terms individually.•The direct neural method can be...
The use of nonlinear loads has increased in power systems consequently the harmonic currents have also increased causing detrimental effects to the supply...
The use of nonlinear loads has increased in power systems consequently the harmonic currents have alsoincreased causing detrimental effects to the supply...
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SubjectTerms Active power filter
ADALINE neural network
Algorithms
Compensation
Electric power
Engineering Sciences
Fourier series
Harmonics
Harmonics currents
Identification methods
LMS algorithm
Load
Low pass filters
Neural networks
Power supply
Power systems
p–q theory
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Title Direct neural method for harmonic currents estimation using adaptive linear element
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