The Study of Optimizing Circulating Fluidized Bed Boiler Operational Parameters Based on Neural Network and Genetic Algorithm

Author(s):  
Xia Hengyan ◽  
Wang Lingmei ◽  
Cheng Huahua
2013 ◽  
Vol 706-708 ◽  
pp. 859-863
Author(s):  
Lin Lin Cui ◽  
Hua Lai ◽  
Xiao Qian Yu ◽  
Ming Jie Qi

According to the multivariable coupling、 large time delay, non-linearity and time-varying and other difficulties of circulating fluidized bed boiler combustion system, a kind of control technology based on neural network to circulating fluidized bed boiler combustion system was presented. Actual parameter data of a paper mill in Kunming and neural network control principle were used in the establishment of a circulating fluidized bed boiler combustion system mathematical model and modified BP neural network algorithm training. Results of MATLAB simulation show that boiler combustion system control precision was effectively improved and good effects in production and application were got.


2014 ◽  
Vol 614 ◽  
pp. 580-583
Author(s):  
De Gong Chang ◽  
Yun Peng Ju

BP neural network can predict and establish a relationship between the parameters of boiler operation. Because this method has certain errors, so this paper presents a optimization method based on genetic algorithm. The method uses the genetic algorithm to optimize the key parameters of boiler operation and search out the maximum boiler efficiency taking advantages of genetic algorithm's global search function. According to optimization results obtained, the staff can adjust the parameters of the boiler and achieve the purpose of optimizing.


2019 ◽  
Vol 92 (6) ◽  
pp. 1800-1806 ◽  
Author(s):  
Michał Wichliński ◽  
Grzegorz Wielgosz ◽  
Rafał Kobyłecki

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