DocumentCode :
1773549
Title :
Power system harmonics estimation using LMS, LMF and LMS/LMF
Author :
Alhaj, Hussam M. M. ; Nor, N.M. ; Asirvadam, Vijanth S. ; Abdullah, Mohd Faris
Author_Institution :
Electr. & Electron. Dept., Univ. Teknol. PETRONAS, Tronoh, Malaysia
fYear :
2014
fDate :
3-5 June 2014
Firstpage :
1
Lastpage :
5
Abstract :
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.
Keywords :
least mean squares methods; power electronics; power system harmonics; LMF; LMS; harmonic pollution; least mean fourth; least mean square; online control; power electronics devices; power system equipments; power system harmonics estimation; power system network; signal to noise ratio; Estimation; Harmonic analysis; Least squares approximations; Power harmonic filters; Signal to noise ratio; LMF; LMS; LMS/LMF; power system harmonic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent and Advanced Systems (ICIAS), 2014 5th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4799-4654-9
Type :
conf
DOI :
10.1109/ICIAS.2014.6869521
Filename :
6869521
Link To Document :
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