Title :
Sectional optimization of oxygen content in flue gas based on PSO
Author :
Liwen Yang ; Jingcheng Wang ; Yuanhao Shi
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
fDate :
May 31 2014-June 2 2014
Abstract :
The optimization of the oxygen content in flue gas has a great impact on the safe and economic operation of boiler combustion system. With the model of BP neural network, the optimization of the oxygen content in flue gas is operated based on PSO, while the optimization settings are different under different load segments. The efficiency of the algorithm is proved by validation results of historical data.
Keywords :
backpropagation; boilers; combustion; flue gases; neural nets; particle swarm optimisation; power engineering computing; BP neural network; PSO; boiler combustion system; flue gas; oxygen content optimization; sectional optimization; Coal; Electronic mail; MATLAB; Mathematical model; Neural networks; Optimization; Oxygen; BP neural network; Oxygen content in flue gas; PSO;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852472
