DocumentCode
2158599
Title
Application of artificial neural network to economic load dispatch
Author
Nanda, J. ; Sachan, A. ; Pradhan, L. ; Kothari, M.L. ; Rao, A. Koteswara ; Lai, L.L. ; Prasad, Mata
Author_Institution
IIT, Delhi, India
Volume
2
fYear
1997
fDate
11-14 Nov 1997
Firstpage
707
Abstract
This paper provides a maiden attempt to explore the feasibility of using a multilayer feedforward neural network using the backpropagation and resilient propagation algorithms to solve the economic load dispatch problem for IEEE 14 and IEEE 30 bus systems. The effect of several important parameters such as the number of hidden units, type of activation function, normalisation, the learning rate parameter, the optimum number of training patterns, etc., in training the neural network has been clearly brought out
Keywords
power system control; IEEE 14 bus system; IEEE 30 bus system; activation function; backpropagation; computer simulation; control design; control simulation; economic load dispatch; hidden units; learning rate parameter; multilayer feedforward neural network; normalisation; power systems; resilient propagation; training patterns;
fLanguage
English
Publisher
iet
Conference_Titel
Advances in Power System Control, Operation and Management, 1997. APSCOM-97. Fourth International Conference on (Conf. Publ. No. 450)
Print_ISBN
0-85296-912-0
Type
conf
DOI
10.1049/cp:19971920
Filename
724934
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