DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning

DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning

Present investigation focuses design & simulation study of a three phase three wire DSTATCOM deploying a conjugate gradient back propagation (CGBP) based icosϕ neural network technique. It is used for various tasks such as source current harmonic reduction, load balancing and power factor correc...

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Main Authors: Mrutyunjaya Mangaraj, Anup Kumar Panda
Format: Article
Language:English
Published: Elsevier 2018-12-01
Series:Ain Shams Engineering Journal
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447916301605
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spelling doaj-f27304f4c6724aad99063fa53fc6a7e92021-06-02T13:59:19ZengElsevierAin Shams Engineering Journal2090-44792018-12-019415351546DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioningMrutyunjaya Mangaraj0Anup Kumar Panda1Corresponding author.; Department of Electrical Engineering, National Institute of Technology, Rourkela 769008, IndiaDepartment of Electrical Engineering, National Institute of Technology, Rourkela 769008, IndiaPresent investigation focuses design & simulation study of a three phase three wire DSTATCOM deploying a conjugate gradient back propagation (CGBP) based icosϕ neural network technique. It is used for various tasks such as source current harmonic reduction, load balancing and power factor correction under various loading which further reduces the DC link voltage of the inverter. The proposed technique is implemented by mathematical analysis with suitable learning rate and updating weight using MATLAB/Simulink. It predicts the computation of fundamental weighting factor of active and reactive component of the load current for the generation of reference source current smoothly. It’s design capability is reflected under to prove the effectiveness of the DSTATCOM. The simulation waveforms are presented and verified using both MATLAB & real-time digital simulator (RTDS). It shows the better performance and maintains the power quality norm as per IEEE-519 by keeping THD of source current well below 5%. Keywords: CGBP based icosϕ neural network, DSTATCOM, MATLAB, RTDShttp://www.sciencedirect.com/science/article/pii/S2090447916301605
collection DOAJ
language English
format Article
sources DOAJ
author Mrutyunjaya Mangaraj
Anup Kumar Panda
spellingShingle Mrutyunjaya Mangaraj
Anup Kumar Panda
DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning
Ain Shams Engineering Journal
author_facet Mrutyunjaya Mangaraj
Anup Kumar Panda
author_sort Mrutyunjaya Mangaraj
title DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning
title_short DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning
title_full DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning
title_fullStr DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning
title_full_unstemmed DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning
title_sort dstatcom deploying cgbp based icosϕ neural network technique for power conditioning
publisher Elsevier
series Ain Shams Engineering Journal
issn 2090-4479
publishDate 2018-12-01
description Present investigation focuses design & simulation study of a three phase three wire DSTATCOM deploying a conjugate gradient back propagation (CGBP) based icosϕ neural network technique. It is used for various tasks such as source current harmonic reduction, load balancing and power factor correction under various loading which further reduces the DC link voltage of the inverter. The proposed technique is implemented by mathematical analysis with suitable learning rate and updating weight using MATLAB/Simulink. It predicts the computation of fundamental weighting factor of active and reactive component of the load current for the generation of reference source current smoothly. It’s design capability is reflected under to prove the effectiveness of the DSTATCOM. The simulation waveforms are presented and verified using both MATLAB & real-time digital simulator (RTDS). It shows the better performance and maintains the power quality norm as per IEEE-519 by keeping THD of source current well below 5%. Keywords: CGBP based icosϕ neural network, DSTATCOM, MATLAB, RTDS
url http://www.sciencedirect.com/science/article/pii/S2090447916301605
work_keys_str_mv AT mrutyunjayamangaraj dstatcomdeployingcgbpbasedicosphneuralnetworktechniqueforpowerconditioning
AT anupkumarpanda dstatcomdeployingcgbpbasedicosphneuralnetworktechniqueforpowerconditioning
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