Modeling approach to coal gasification using hybrid neural networks

Coal gasification was carried out in a bench-scale fluidized bed gasifier. The gasifier operated at atmospheric pressure with steam as fluidizing medium. The background of this study was the gas-steam cogeneration system. A hybrid neural network model was synthesized to predict the gas production rates. The model consists of a first principle partial model and a neural network parameter estimator. The model was trained with the experimental gasification data of Jincheng anthracite coal. The model has a good performance of process simulation. A parameter called 'fraction of active char' was proposed in the model. Neural network performed identification of this parameter and obtained its variation with temperature, with respect to Jincheng anthracite.

Modeling approach to coal gasification using hybrid neural networks Academic Article