A multi-objective optimization of the integrated copper-chlorine cycle for hydrogen production

Abstract

This paper considers a multi-objective optimization study performed on an integrated copper-chlorine cycle for hydrogen production developed and built at the Ontario Tech. University using genetic algorithm. The system is thermodynamically modeled in the Aspen-plus software considering all components in the cycle. A varied range of steam-to-copper ratios is selected for this study and four different cases are considered based on various steam input temperatures. The objective of this study is to maximize the rate of hydrogen production and overall system exergy efficiency, hence minimizing overall cost of cycle operation. The results of the multi-objective optimization study are presented in the form of the Pareto frontier solutions for identification of the optimal points. A comparison of the optimization results with Aspen-plus simulations is also presented for validation purposes. For all the cases considered, the optimal trade-off point results in steam-to-copper ratios ranging from 15.7 to 16.9. The steam input temperature is found to have a significant influence on the exergy efficiency and overall operating cost. The highest exergy efficiency is reported as 17.8% at a steam input temperature of 300 °C, while the minimum exergy efficiency is obtained to be 6.5% at a steam input temperature of 25 °C.