.png){kind=icon}
返回
Variable Constraint based Least Mean Square algorithm for power system harmonic parameter estimation
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ijepes.2015.04.018.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper presents the maiden application of a novel signal processing algorithm called Variable Constraint based Least Mean Square (VCLMS) for power system harmonic parameter estimation. The amplitude, phase and frequency of a power signal containing harmonics, sub-harmonics, inter-harmonics are estimated using this algorithm in the presence of white Gaussian noise under simulating environment. Four Least Mean Square (LMS) based algorithms, reported in the literature are considered for judging the comparative performance with the proposed algorithm. These algorithms are applied and tested for both stationary as well as dynamic signals containing harmonics. Practical validation is made with the experimentation of the algorithms with real time data obtained from a solar connected inverter system used for supplying electrical energy during power cut at National Institute of Technology (NIT) Silchar through a power quality analyzer and estimation are performed in MATLAB simulation. Comparison of the results amongst LMS, Normalized LMS, Complex Normalized LMS, Variable Leaky LMS and VCLMS algorithms reveals that proposed VCLMS algorithm is the best in terms of accuracy and computational time. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Variable Constraint based Least Mean
Square
Harmonics
Power quality
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
I
IF:
5
论文数:
1.1W
被引数:
3.1W
机构
引用论文
分享收藏Late Weichselian and Holocene environments of lake Endletvatn, Andøya, northern Norway: as evidenced primarily by chemostratigraphical data.png)
Boreas
BoreasIF0
PREAI
分享收藏
查看更多内容