Cart (Loading....) | Create Account
Close category search window
 

Ensemble-Kalman-Filter-Based Power System Harmonic Estimation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ray, P.K. ; Dept. of Electr. Eng., NIT Rourkela, Rourkela, India ; Subudhi, B.

The growing use of power-electronics-based components and nonlinear loads is increasing the presence of harmonics in power system signals. In this scenario, proper estimation of such harmonics is intended to maintain power quality and improved operation of the system. It is also desirable that the estimation technique should be computationally efficient while being accurate. From this viewpoint, this paper proposes a nonlinear state estimation technique based on ensemble Kalman filtering for estimation of harmonics, interharmonics, and subharmonics, all using a single framework and at a time, from distorted power system signal. The proposed technique is computationally efficient compared to conventional Kalman filtering leading to less computational cost and hardware requirement. It is observed from both simulation and experimental studies that the proposed ensemble Kalman filter (KF) approach to estimation of harmonics, interharmonics, and subharmonics in a distorted power system signal exhibits superior estimation performance in terms of tracking time and accuracy as compared to performances of some of the existing techniques such as recursive least square, recursive least mean square, and KF algorithms. The proposed technique is also found to be robust and gives accurate estimates even in the presence of amplitude variations in the measured signal.

Published in:

Instrumentation and Measurement, IEEE Transactions on  (Volume:61 ,  Issue: 12 )

Date of Publication:

Dec. 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.