Title :
Harmonic estimation in a power system using hybrid H∞-Adaline algorithm
Author :
Sahoo, H.K. ; Dash, P.K. ; Rath, N.P. ; Sahu, B.N.
Author_Institution :
Silicon Inst. of Technol., Bhubaneswar, India
Abstract :
Accurate computation of harmonics is really a challenging problem in power system. Many algorithms have been proposed for harmonic estimation. In this paper a novel hybrid approach is proposed to estimate the amplitudes and phases of fundamental, third and fifth harmonics of three different types of distorted power signals in presence of white noise. A robust estimator known as H∞ filter is used for amplitude estimation, which is based upon state space modeling of the signals and an adaptive linear combiner called ´Adaline´ based on the neural network, which is very simple and faster is used for phase estimation. The simulation results are compared with that of extended Kalman filter to show the tracking capability of the proposed algorithm.
Keywords :
Kalman filters; neural nets; nonlinear filters; power filters; power system analysis computing; power system harmonics; H∞ filter; adaptive linear combiner; amplitude estimation; extended Kalman filter; harmonic estimation; hybrid H∞-adaline algorithm; neural network; phase estimation; power system; robust estimator; Adaline; Extended Kalman Filter; H∞ Filter; Neural Network; White Gaussian noise;
Conference_Titel :
TENCON 2009 - 2009 IEEE Region 10 Conference
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-4546-2
Electronic_ISBN :
978-1-4244-4547-9
DOI :
10.1109/TENCON.2009.5396254