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

A new neural network approach to economic emission load dispatch

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

3 Author(s)
Xian Wang ; Shanghai Univ., China ; Yu-Zeng Li ; Shao-Hua Zhang

An artificial neural network method is developed for the solution of economic emission load dispatch (EELD) problems with thermal generation. The proposed method can overcome numerical difficulty caused by conventional neural networks with network parameters, and the states of the dynamic system described by the new neural network converge globally to the optimal solution of the EELD problem whenever its initial points are located inside or outside the feasible region of the problem. The application and validity of the proposed algorithm are demonstrated with a sample system with three generators.

Published in:

Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on  (Volume:1 )

Date of Conference:

2002

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.