Methanol steam reforming performance optimisation of cylindrical microreactor for hydrogen production utilising error backpropagation and genetic algorithm

Abstract

To optimise methanol steam reforming performance of cylindrical microreactor for hydrogen production, an error backpropagation algorithm was used to build a mathematical model for reaction performance of different microreactors for hydrogen production. Additionally, a genetic algorithm (GA) was utilised to process the computational model to obtain the optimum reaction parameters. The reliability of optimum reaction parameters of cylindrical microreactor for hydrogen production was verified by experiments. Firstly, take platemicroreactor as an example, the porosity of porous copper fiber sintered sheet (PCFSS), reaction temperature of methanol steam reforming for hydrogen production, injection velocity of the methanol and water mixture, and catalyst loading of PCFSS were considered as input data, whereas methanol conversion was used as output data. The computational model for specific testing system was gained by utilising input and output data from specific testing system to train the mathematical model for different microreactors, combining with matrix laboratory (MATLAB) neural network toolbox and designed MATLAB program. The Emax of 5% for plate microreactor and Emax of 3.2% for cylindrical microreactor verified the good predictive ability and reliability of the computational model for plate and cylindrical microreactor, indicating the reliability and universal applicability of the mathematical model for different microreactors. Secondly, the effects and mechanisms of PPI, reaction temperature, injection velocity, and catalyst loading on methanol conversion were studied, relying on the computational model. Finally, the optimum reaction parameters were acquired using GA, MATLAB neural network toolbox and designed MATLAB program. The validity of the optimum reaction parameters of cylindrical microreactor for hydrogen production was confirmed by experiments. This study provides a feasible method for methanol steam reforming performance optimisation for hydrogen production.