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

Wide area power grid health state diagnosis and early warning system based on fault power flow fingerprint identification and MAS technology

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

7 Author(s)
Peng Ge ; Dept. of Electr. Eng., Southeast Univ., Nanjing ; Qian Guo ; Haina Zhou ; Xinran Li
more authors

The stability and security of the power grid is deteriorated due to the recent large-scale power grid interconnection and the power marketing. The stability character of the power grid becomes complex more and more. The new theory and technique need to be applied to diagnose the real-time state of the power grid in order to ensure the safe and economical operation of the power grid. The power flow fingerprint character during the normal and fault state is analyzed and the power grid health diagnosis repository with the Self-learning ability is constituted. The diagnosis method adaptable for the wide area power grid health state diagnosis is put forward in the paper. The power flow character is extracted using AFIS technology, and the intelligent matching arithmetic is used to diagnose the power grid health state, so the power grid health state factor and the uncertain probability distributing between the failure and symptom is present. The early warning and decision support architecture is constructed based on the Power Flow Fingerprint Identification and MAS Technology. The health diagnosis results can be integrated with the other intelligent diagnosis results and can alarm the dispatcher using the technology of visualization. The application of power flow fingerprint identification technique to diagnose the health state of the power grid can eliminate the potential fault in the power grid and prevent the happening of the paroxysmal accident.

Published in:

Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on

Date of Conference:

6-9 April 2008

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.