TY  - CONF
SN  - 9781479946549
TI  - Power system harmonics estimation using LMS, LMF and LMS/LMF
ID  - scholars4971
A1  - Alhaj, H.M.M.
A1  - Nor, N.M.
A1  - Asirvadam, V.S.
A1  - Abdullah, M.F.
Y1  - 2014///
KW  - Electric power distribution; Power electronics; Signal to noise ratio
KW  -  Least mean square (LMS); LMF; LMS; LMS/LMF; Low signal-to-noise ratio; Power electronics devices; Power system harmonics; Steady state performance
KW  -  Harmonic analysis
N1  - cited By 25; Conference of 2014 5th International Conference on Intelligent and Advanced Systems, ICIAS 2014 ; Conference Date: 3 June 2014 Through 5 June 2014; Conference Code:107042
PB  - IEEE Computer Society
N2  - 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.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906330415&doi=10.1109%2fICIAS.2014.6869521&partnerID=40&md5=6d75e9fa8103d98948018eaf07ddb0c4
CY  - Kuala Lumpur
AV  - none
ER  -