A cascaded neural network and its application to modelling power plant pollutant emission

Author

Li, Kang ; Thompson, Stephen

Author_Institution

Dept. of Mech. & Manuf. Eng., Queen´´s Univ., Belfast, UK

Volume

2

fYear

2000

fDate

2000

Firstpage

992

Abstract

Pollutant emission in power generation plant, especially NOx emission, has attracted much attention in the last ten years. For an operating plant, development of an advanced control system is essential for pollutant emission reduction. System modelling is an important stage in emission control. In this paper, a cascading neural network is used to model the NOx emission in a coal-fired power generation plant. This type of neural network has more connections than that found in the layered feedforward neural network. Algorithm for training this type of neural network is suggested and then it is used to build a NOx emission model for a coal-fired power generation plant. Simulation results show the merits of this type of neural network

Keywords

air pollution control; cascade control; learning (artificial intelligence); neurocontrollers; power generation control; power plants; steam power stations; NOx emission; advanced control system; cascaded neural network; coal-fired power generation plant; emission control; pollutant emission reduction; power generation plant; power plant pollutant emission modelling; training; Air pollution; Artificial neural networks; Environmentally friendly manufacturing techniques; Feedforward neural networks; Function approximation; Neural networks; Nitrogen; Power engineering and energy; Power generation; Power system modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on

Conference_Location

Hefei

Print_ISBN

0-7803-5995-X

Type

conf

DOI

10.1109/WCICA.2000.863383

Filename

863383