DocumentCode :
3099141
Title :
Using Neural Network for Solving of On-Line Economic Dispatch Problem
Author :
Mohammadi, Amir ; Varahram, Mohammad Hadi
Author_Institution :
Sci. & Res. Branch, Islamic Azad Univ., Tehran
fYear :
2006
fDate :
Nov. 28 2006-Dec. 1 2006
Firstpage :
87
Lastpage :
87
Abstract :
In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and lambda iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for convergence is considerably smaller compared to classical methods.
Keywords :
Hopfield neural nets; power engineering computing; power generation dispatch; power generation economics; Hopfield neural network; iteration method; neural network; online economic dispatch problem; Cost function; Fuel economy; Hopfield neural networks; Neural networks; Neurons; Power generation; Power generation economics; Power system economics; Power systems; Propagation losses;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7695-2731-0
Type :
conf
DOI :
10.1109/CIMCA.2006.228
Filename :
4052725
Link To Document :
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