الگوریتم حداقل الگوریتم میانگین مربع بر اساس محدودیت متغیر برای برآورد پارامتر هارمونیکی سیستم قدرت

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.