Simulation and Multi-Objective Optimization of an Integrated Process for Hydrogen Production from Refinery Off-Gas

Dongliang Wang, Xiao Feng (China University of Petroleum-Beijing)

Hydrogen production from internal refinery sources such as refinery off-gas (ROG) is one of the most cost-effective solutions to a refinery’s hydrogen supply. To maximize the value of such resource, this paper proposes an integrated hydrogen production process based of coupled feed of ROG and natural gas. A rigorous process model is developed and simulated using the commercial process simulator Aspen Plus. To simultaneously maximize hydrogen and steam production, a non-dominated sorting genetic algorithm-II (NSGA-II) is employed to solve the constrained multi-objective optimization problem. A modular framework of the process simulator and multi-objective genetic algorithm is also developed to obtain sets of Pareto-optimal operating conditions, making it easier to optimize the integrated hydrogen production process. The optimization results reveal that the performance of the integrated process can be significantly improved.


Pareto set for simultaneous maximization of steam and hydrogen production.