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

Neural-networks for predicting the operation of an under-frequency load shedding system

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)
Kottick, D. ; Res. & Dev. Div., Israel Electr. Corp. Ltd., Haifa, Israel ; Or, O.

Dynamic security assessment is of special importance to island power systems. The CPU time required in order to apply conventional methods for those calculations does not allow real-time application. The fast calculation time is, therefore, an important advantage of artificial neural networks compared to other methods. This paper presents two neural network models that were designed to calculate the minimal frequency and the load shedding system operation during a forced outage of a generating unit. The minimal frequency and the extent of the load shedding are strong indications of the severity of the fault. Hence, it is a significant part of the dynamic security assessment procedure

Published in:

Power Systems, IEEE Transactions on  (Volume:11 ,  Issue: 3 )

Date of Publication:

Aug 1996

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.