Title :
Modeling of the Combustion Optimizing Based on RBF Neural Networks
Author :
Chen, Lei ; Xie, Youcheng ; Shen, Zhongli ; Fu, Huilin
Author_Institution :
Coll. of Energy & Power Eng., Changsha Univ. of Sci. & Technol., Changsha
Abstract :
A combustion optimizing model based on RBF neural networks is set up, and the optimizations of providing coal volume and real generating electricity power are actualized. At the same time, the simulation model is established by MATLAB. The simulation research is processed. The simulation result indicates: in the stabilization state, if the boiler load, power plant coal character (the distinctness of coal heat glowing volume), combustion supplying air volume or combustion inducing air volume changes, the combustion optimizing model based on RBF neural networks can find the optimum values of providing coal volume and real generating electricity power. This result lays a strong base for optimal control and on-line prediction of the boiler.
Keywords :
boilers; coal; optimal control; power plants; radial basis function networks; MATLAB; RBF neural networks; boiler load; coal heat glowing volume; combustion inducing air volume; combustion optimizing model; combustion supplying air volume; online prediction; optimal control; power plant coal character; real generating electricity power; Biological neural networks; Boilers; Brain modeling; Character generation; Combustion; Educational institutions; Mathematical model; Neural networks; Power engineering and energy; Power generation; Combustion; Optimizion; RBF neural networks;
Conference_Titel :
Computing, Communication, Control, and Management, 2008. CCCM '08. ISECS International Colloquium on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3290-5
DOI :
10.1109/CCCM.2008.327