Neural network-based modeling of a thermal power plant feedwater pump

• Published in: 12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) pp. 85 - 88
• Main Authors: Nikolic, Ivan R., Petkovski, Vesna N., Kvascev, Goran S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-11-2014
• Subjects: Artificial neural networks; Data models; Educational institutions; Mathematical model; Neural network; nonlinear systems; Power generation; system modeling; Training
• ISBN: 9781479958870; 1479958875
• DOI: 10.1109/NEUREL.2014.7011467

Obtaining an accurate model of a real-world system using linear systems theory can prove to be a complex task due to the nonlinear characteristics that systems exhibit. Neural networks have the ability to reproduce the complex nonlinear relations which makes them a useful tool in system identification and modeling. The purpose of this paper is to obtain the model of a thermal power plant feedwater pump in order to test various control approaches. The neural network used in this paper is a multi-layer feed-forward network. The comparison of the results obtained by using this approach with the results obtained from a mathematical model confirms that the neural network-based model is a better approximation of the observed system.