To solve the problems occurred during the combustion modeling of domestic power plants

such as frequent fluctuations of coal quality and unit load

limited measurement accuracy

various change in running equipments combination

an asymmetric neural network modeling method for utility boilers' combustion was proposed.In this method

the boiler model's structure is designed according to the actual physical relationship by removing the weak link.So the model naturally embodies the boilers' combustion laws and realizes single network modeling under conditions with different burner output distributions.Thus

this method greatly increases the training efficiency and sharply reduces the demand for the number of samples.Moreover

comparative training was carried out for classical symmetric neural network model and asymmetric neural network model.The results show that

the proposed method is more effective than the classical one.It was used to optimize the combustion control of an actual 660 MW unit

and the results show the boiler efficiency was increased by 0.25%.