DocumentCode :
1609413
Title :
Economic load flow using Lagrange neural network
Author :
Mohatram, Mohammad ; Tewari, Peeyush ; Latanath, Nutan
Author_Institution :
Waljat Coll. of Appl. Sci., Muscat, Oman
fYear :
2011
Firstpage :
1
Lastpage :
7
Abstract :
This paper proposed an artificial neural network (ANN) approach based on Lagrangian multiplier method (Lagrangian ANN) to solve the problem of economic load flow in a power system. Operational requirements and transmission losses are also taken care by the proposed approach. Power plant operating costs are represented by exponential cost functions. Simulation on a test example with six generating units shows that the proposed method can efficiently and accurately solve the problem of economic load flow.
Keywords :
load flow; neural nets; power generation economics; power generation scheduling; power system analysis computing; Lagrange neural network; Lagrangian multiplier; artificial neural network; economic load flow; exponential cost functions; power plant operating costs; transmission loss; Artificial neural networks; Biological system modeling; Convergence; Economics; Fuels; Load flow; Mathematical model; Lagrangian ANN; economic generation scheduling; exponentia l cost function; load flow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Communications and Photonics Conference (SIECPC), 2011 Saudi International
Conference_Location :
Riyadh
Print_ISBN :
978-1-4577-0068-2
Electronic_ISBN :
978-1-4577-0067-5
Type :
conf
DOI :
10.1109/SIECPC.2011.5876896
Filename :
5876896
Link To Document :
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