DocumentCode
3696518
Title
Economic Dispatch using Improved Hopfield Neural Network
Author
S. Surender Reddy;James A. Momoh
Author_Institution
Department of Railroad &
fYear
2015
Firstpage
1
Lastpage
5
Abstract
This paper presents an Improved Hopfield Neural Network (IHNN) to solve the Economic Dispatch (ED) problem. In this paper, an attempt has been made to implement Artificial Neural Networks (ANN) for Economic Load Dispatch problem. In this ED model, the transmission system and active power constraints are included. The proposed IHNN model has fast convergence and moves efficiently towards feasible equilibrium points. The ED using proposed IHNN has been tested on 3, 6 and 20 generating units. The results obtained with Improved HNN are compared with those of the results obtained by Lambda iteration method and Particle Swarm Optimization. The findings confirmed the robustness, proficiency and fast convergence of the proposed approach over other existing techniques.
Keywords
"Generators","Hopfield neural networks","Economics","Fuels","Propagation losses","Power generation"
Publisher
ieee
Conference_Titel
North American Power Symposium (NAPS), 2015
Type
conf
DOI
10.1109/NAPS.2015.7335246
Filename
7335246
Link To Document