Title :
Application of Volterra-series algorithm for power system harmonic estimation
Author :
Singh, S.K. ; Goswami, Arup K. ; Sinha, N.
Author_Institution :
Electr. Eng. Dept., Nat. Inst. of Technol., Silchar, India
Abstract :
The increasing trend for use of nonlinear loads in power system results in generation of more harmonics and hence deterioration of power quality. This calls for accurate estimation of harmonics in power system so that more effective compensation measures are designed. However, accurate computation of all the harmonics is a challenging problem in power system. Even though many algorithms have been proposed for harmonic estimation to improve the power quality performance, but till date it remains a challenge. In this paper two nonlinear adaptive filtering algorithms called Volterra Least Mean Square (VLMS) and Volterra Recursive Least Square (VRLS) are applied for the first time for estimating harmonic parameters. These approaches have been considered to estimate the amplitudes, phases and frequency in case of time varying power signals containing harmonics in the presence of White Gaussian Noise in MATLAB simulating environment. Also comparison results with VLMS and VRLS algorithms are presented to show the effectiveness of the proposed VRLS algorithm.
Keywords :
AWGN; adaptive filters; least mean squares methods; nonlinear filters; power supply quality; power system harmonics; power system parameter estimation; Matlab simulating environment; VLMS algorithms; VRLS algorithms; Volterra least mean square algorithm; Volterra recursive least square algorithm; Volterra-Series algorithm; amplitude estimation; compensation measures; frequency estimation; nonlinear adaptive filtering algorithms; nonlinear loads; phase estimation; power quality performance; power signals; power system harmonic parameter estimation; white Gaussian noise; Adaptive filters; Estimation; Frequency estimation; Harmonic analysis; Noise; Power harmonic filters; Extended Least Mean Square (ELMS); Forgetting Factor Recursive Least Square (FFRLS); Least Mean Square (LMS); Recursive Least Square (RLS); Volterra Least Mean Square (VLMS); Volterra Recursive Least Square (VRLS);
Conference_Titel :
Automation, Control, Energy and Systems (ACES), 2014 First International Conference on
Conference_Location :
Hooghy
Print_ISBN :
978-1-4799-3893-3
DOI :
10.1109/ACES.2014.6807998