Title :
The neural network control application in a power plant boiler
Author :
Li, Jianyong ; Ososanya, Esther T. ; Smoak, Robert A.
Abstract :
Two neural networks are used in the control of power plant boiler throttle pressure and megawatt load, where one network acts as an emulator, and the other as a controller. The learning scheme is a two-phase procedure in which the first involves training the emulator in mapping the plant dynamics and the second to train a controller network to learn the desired performance using a backpropagation algorithm and minimize plant output error cost function. This example illustrates the potential application of neural network technique in the power plant control area
Keywords :
backpropagation; boilers; controllers; load regulation; neurocontrollers; power control; power station control; power station load; pressure control; thermal power stations; backpropagation algorithm; controller; emulator; learning scheme; megawatt load control; neural network control; output error cost function minimisation; plant dynamics mapping; power plant boiler; throttle pressure control; training; two-phase procedure; Artificial neural networks; Biological neural networks; Boilers; Control systems; Multi-layer neural network; Neural networks; Power generation; Power system interconnection; Pressure control; Turbines;
Conference_Titel :
Southeastcon '96. Bringing Together Education, Science and Technology., Proceedings of the IEEE
Conference_Location :
Tampa, FL
Print_ISBN :
0-7803-3088-9
DOI :
10.1109/SECON.1996.510126
