Application of neural networks as an auxiliary technique in the modelling of power station

Ghamami, Khayam and Hu, Eric 2004, Application of neural networks as an auxiliary technique in the modelling of power station, in AUPEC 2004 : Australasian Universities Power Engineering Conference Brisbane, Australia, University of Queensland, School of Information Technology & Electrical Engineering, Brisbane, Qld, pp. 1-6.

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Title Application of neural networks as an auxiliary technique in the modelling of power station
Author(s) Ghamami, Khayam
Hu, Eric
Conference name AUPEC : Australasian Universities Power Engineering Conference (2004 : Brisbane, Australia)
Conference location Brisbane, Australia
Conference dates 26-29 September 2004
Title of proceedings AUPEC 2004 : Australasian Universities Power Engineering Conference Brisbane, Australia
Editor(s) Walker, Geoffrey
Publication date 2004
Start page 1
End page 6
Publisher University of Queensland, School of Information Technology & Electrical Engineering
Place of publication Brisbane, Qld
Summary Artificial neural network (NN) is an alternative way (to conventional physical or chemical based modeling technique) to solve complex ill-defined problems. Neural networks trained from historical data are able to handle nonlinear problems and to find the relationship between input data and output data when there is no obvious one between them. Neural Networks has been successfully used in control, robotic, pattern recognition, forecasting areas. This paper presents an application of neural networks in finding some key factors eg. heat loss factor in power station modeling process. In the conventional modeling of power station, these factors such as heat loss are normally determined by experience or “rule of thumb”. To get an accurate estimation of these factors special experiment needs to be carried out and is a very time consuming process. In this paper the neural networks (technique) is used to assist this difficult conventional modeling process. The historical data from a real running brown coal power station in Victoria has been used to train the neural network model and the outcomes of the trained NN model will be used to determine the factors in the conventional energy modeling of the power stations that is under the development as a part of an on-going ARC Linkage project aiming to detail modeling the internal energy flows in the power station.
ISBN 1864997753
9781864997750
Language eng
Field of Research 091399 Mechanical Engineering not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30005423

Document type: Conference Paper
Collection: School of Engineering and Technology
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