Power system harmonics estimation using LMS, LMF and LMS/LMF

Recently, in the world wide the use of power electronics devices increases sharply. As a result, harmonic pollution becomes a vital problem than before. Harmonics rotate in the power system network and interfere with the system equipments, disturbing their normal operation which can deteriorate the...

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Main Authors: Alhaj, H.M.M., Nor, N.M., Asirvadam, V.S., Abdullah, M.F.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.32164 /
Published: IEEE Computer Society 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906330415&doi=10.1109%2fICIAS.2014.6869521&partnerID=40&md5=6d75e9fa8103d98948018eaf07ddb0c4
http://eprints.utp.edu.my/32164/
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spelling utp-eprints.321642022-03-29T05:00:34Z Power system harmonics estimation using LMS, LMF and LMS/LMF Alhaj, H.M.M. Nor, N.M. Asirvadam, V.S. Abdullah, M.F. Recently, in the world wide the use of power electronics devices increases sharply. As a result, harmonic pollution becomes a vital problem than before. Harmonics rotate in the power system network and interfere with the system equipments, disturbing their normal operation which can deteriorate the quality of the delivered power. Therefore, efficient method with low computational time is a critical tool to estimate and quantify the harmonic that can be used in online control and mitigation of harmonics. Least Mean Square (LMS) is simple and popular algorithm that has been applied in many applications, but, noise can affect its performance. This paper presents and compare the performance of Least Mean Square (LMS), Least Mean Fourth (LMF) and a combined (LMS/LMF) in estimation harmonic component for the signal corrupted with noise contain low signal to noise ratio (SNR). The results show that LMF and LMS/LMF have better steady state performance as compared to LMS. © 2014 IEEE. IEEE Computer Society 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906330415&doi=10.1109%2fICIAS.2014.6869521&partnerID=40&md5=6d75e9fa8103d98948018eaf07ddb0c4 Alhaj, H.M.M. and Nor, N.M. and Asirvadam, V.S. and Abdullah, M.F. (2014) Power system harmonics estimation using LMS, LMF and LMS/LMF. In: UNSPECIFIED. http://eprints.utp.edu.my/32164/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Recently, in the world wide the use of power electronics devices increases sharply. As a result, harmonic pollution becomes a vital problem than before. Harmonics rotate in the power system network and interfere with the system equipments, disturbing their normal operation which can deteriorate the quality of the delivered power. Therefore, efficient method with low computational time is a critical tool to estimate and quantify the harmonic that can be used in online control and mitigation of harmonics. Least Mean Square (LMS) is simple and popular algorithm that has been applied in many applications, but, noise can affect its performance. This paper presents and compare the performance of Least Mean Square (LMS), Least Mean Fourth (LMF) and a combined (LMS/LMF) in estimation harmonic component for the signal corrupted with noise contain low signal to noise ratio (SNR). The results show that LMF and LMS/LMF have better steady state performance as compared to LMS. © 2014 IEEE.
format Conference or Workshop Item
author Alhaj, H.M.M.
Nor, N.M.
Asirvadam, V.S.
Abdullah, M.F.
spellingShingle Alhaj, H.M.M.
Nor, N.M.
Asirvadam, V.S.
Abdullah, M.F.
Power system harmonics estimation using LMS, LMF and LMS/LMF
author_sort Alhaj, H.M.M.
title Power system harmonics estimation using LMS, LMF and LMS/LMF
title_short Power system harmonics estimation using LMS, LMF and LMS/LMF
title_full Power system harmonics estimation using LMS, LMF and LMS/LMF
title_fullStr Power system harmonics estimation using LMS, LMF and LMS/LMF
title_full_unstemmed Power system harmonics estimation using LMS, LMF and LMS/LMF
title_sort power system harmonics estimation using lms, lmf and lms/lmf
publisher IEEE Computer Society
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906330415&doi=10.1109%2fICIAS.2014.6869521&partnerID=40&md5=6d75e9fa8103d98948018eaf07ddb0c4
http://eprints.utp.edu.my/32164/
_version_ 1741197695443271680
score 11.62408

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