By Topic

ANN-based hybrid state estimation and enhanced visualization of power systems

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
$33 $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)
Amit Kumar ; Department of Electrical Engineering, Indian Institute of Technology, Kanpur, U.P., 208016 India ; S. Chakrabarti

The paper presents an artificial neural network (ANN)-based hybrid state estimator for estimating the states of a power system in the presence of conventional asynchronous as well as synchronous phasor measurements. Case studies on test systems show promising results for the ANN-based estimator. The paper also presents methodologies to enhance the visualization of the power system during the intervals between successive outputs of the conventional state estimator. The ANN-based state estimators trained with measurements from phasor measurement units (PMUs) are shown to be useful for enhancing the visualization of the power system during such intervals.

Published in:

Innovative Smart Grid Technologies - India (ISGT India), 2011 IEEE PES

Date of Conference:

1-3 Dec. 2011