Applied Energy, Vol.235, 164-176, 2019
Thermo-economic optimization of hydrogen production in a membrane-SMR integrated to ITM-oxy-combustion plant using genetic algorithm
Hydrogen is a clean source of fuel. It is mostly produced from fossil fuel with high global warming potentials. This has necessitated the incorporation of carbon capture and storage techniques (CCS) into modem hydrogen plant designs. In this work, a technical and economic analysis of a novel hydrogen production plant was carried out and it is presented and discussed in this article. The proposed plant comprises a membrane-based steam methane reformer (SMR) integrated to an ion transport membrane (ITM) oxy-combustion unit. The plant operating parameters are optimized for minimum annualized cost of hydrogen production (ACH) using genetic algorithm. The operating parameters optimized are namely; the combustor exit temperature (CET), reformer pressure (RP), hydrogen permeation factor and auxiliary fuel factor. The sensitivity analysis of the natural gas cost and the capacity factor on the ACH and the year of return (YOR) on investment were also carried out. The ACH of 12.13/GJ H-2 and overall plant efficiency of 59.44% were obtained at the following optimized operating conditions: RP of 18.97 bar, hydrogen permeation factor of 0.9, auxiliary fuel factor of 0.57 and constrained CET of 1500 K. Results further revealed the existence of similar ACH (with max. deviation of 2.5% from the lowest ACH) and overall system efficiency (with max. deviation of 0.5% from the highest overall system efficiency) at another two different sets of optimum operating conditions at CET of 1400 K and 1300 K. Finally, it was proven that the ACH from the novel plant proposed and presented in this work is lower than those obtained from various plant designs and feed stocks in literature. This indicated that hydrogen production from the integrated membrane-SMR-ITM-Oxy-combustion plant that is proposed and optimized in this work is promising.
Keywords:Hydrogen and power production;Ion transport membrane;Steam-methane reforming;Genetic Algorithm-Optimization