A new hybrid process for hydrogen (H2) production that including membrane separation, electrochemical hydrogen pump (EHP) and steam methane reforming (SMR) was proposed. Firstly, the combination of two different membranes (PEO-CA) is applied to upgrade the biogas and capture CO2. Secondly, to avoid the toxic effect of CO on the EHP catalyst and, more importantly, to improve the H2 purity, the reforming reaction module is supplemented with water gas shift after the SMR. Finally, EHP is used to achieve high purity hydrogen. Simultaneously, the heat and power integration are considered to improve system efficiency. Sensitivity analysis, maximal information coefficient method and response surface methodology are applied to establish the correlation between objectives and parameters. Then, the second generation multi-objective non-dominated genetic algorithm (NSGA-II) is utilized to achieve minimum levelized cost of hydrogen (LCoH) and carbon emission per unit of hydrogen (ECO2). The optimized LCoH is 2.72 $/kgH2, and the ECO2 is 3.24 kgCO2e. Multi-stage membrane carbon capture process enhances CH4 conversion in SMR. The application of EHP reduces energy consumption and enhances hydrogen yield compared to PSA. The innovative use of membrane is hybridized with EHP to achieve the system intensification. The new hybrid process has a significant advantage in terms of ECO2 (37.45% reduction), although the price is higher compared to conventional biogas-to-hydrogen processes. Thus the new process is a promising low-carbon hydrogen production process from biogas.

In this work, a novel process of polymer membrane coupled with electrochemical hydrogen pump (EHP) was proposed to achieve efficient hydrogen production from hydrogen-doped natural gas (HDNG), and was simulated by UniSim Design. A hydrogen separation unit of two-stage polymer membrane was used for achieving hydrogen enrichment from low H 2 concentration HDNG. Due to the hydrogen upgrade, EHP was operated at a H 2 concentration much higher than HDNG, resulting in low energy consumption. Benefiting from the synergy between hydrogen upgrade and purification, the coupling process brought substantial effect while improving the hydrogen purity and recovery rate and reducing the hydrogen separation cost. The real natural gas components were considered into HDNG to ensure the effectiveness of process simulation. An optimization strategy considering both product yield and production cost was proposed to achieve the trade-off between hydrogen recovery rate and separation cost. However, the impact of process parameters on the objectives is nonlinear and difficult to describe with mathematical expressions. Therefore, an agent model of the proposed process was established based on back propagation neural network (BPNN), and multi-objective optimization of H 2 recovery rate and total annual cost (TAC) of hydrogen separation unit was achieved using non-dominated sorting genetic algorithm-II (NSGA-II). Investigations with HDNG under various operating conditions (feed pressure of 8 - 40 bar and feed H 2 concentration of 5 - 25 mol%) were performed, which proved that 90 % overall H 2 recovery rate and 99.99 mol% H 2 purity of hydrogen product can be achieved at low cost, with the lowest hydrogen separation cost of 1.00 $/kg H 2 achievable at 40 bar feed pressure and 25 mol% feed H 2 concentration. In summary, this coupling process can provide engineering solutions for efficient hydrogen production from HDNG and promote the development of green hydrogen.

In this work, two methanol-reforming gas fuel cell systems coupled with an electrochemical hydrogen pump (EHP), namely, EHP pre-coupling and post-coupling fuel cell systems were proposed to achieve performance enhancement. A back propagation neural network surrogate model was established for the two systems to accurately describe system behavior, and a second-generation multi-objective non-dominated genetic algorithm was utilized for addressing the multi-objective optimization problem encompassing net output power, carbon mass-specific emission and the levelized cost of electricity. The linear non-weighted multi-attribute preference and technique for order preference by similarity to ideal solution multi-attribute decision-making methods were employed to select the optimal solutions. The optimized EHP pre-coupling fuel cell system exhibited lower carbon emissions (0.69 kgCO2/(kW & sdot;h)) and higher net output power (126.02 kW) compared to previous studies. While the EHP post-coupling system achieves a lower levelized cost of electricity (0.36 USD/(kW & sdot;h)), and stronger system stability (total efficiency reduction less 1 %). Both EHP-coupling systems offer viable process enhancements for fuel cell systems.

In this work, a pseudo-2D model including electrode reactionandmembrane separation of the high-temperature electrochemical hydrogenpump (HT-EHP) was proposed to separate a CO-containing hydrogen mixture.Rigorous kinetics of electrochemical reaction and competitive adsorptionwas introduced to reach accurate performance prediction. The simulatedpolarization curves of three different feed gases, namely, no-CO andnarrow and wide CO content ranges, at different temperatures wereconsistent with the experimental data (R (2) >= 0.90). Compared to previous work, the accuracy of the developedpseudo-2D model has been improved by 78.8% and 62.2%, respectively,under two feedstock conditions. Quantitative analysis of current densityand catalyst coverage was achieved under various process conditions,demonstrating the applicability of HT-EHP pseudo-2D model. Feasiblesuggestions for the optimization design of HT-EHP were provided byanalyzing the relationship between equipment scale, feed flow rate,current density and hydrogen recovery rate. Thus, the developed pseudo-2Dmodel can be beneficial in the design and optimization of the HT-EHPsystem, and HT-EHP as an efficient membrane based technology is promisingfor the separation of CO-containing hydrogen mixtures in the future.

As a by-product of the coking industry, coke oven gas (COG) is often burned as fuel gas. However, COG contains a large amount of hydrogen. If hydrogen is recovered, the economic and environmental benefits of the coking industry can be improved. In this work, a novel automotive fuel cell hydrogen production process coupled with membrane separation (PRISM & REG; Membrane Separator, polyimide hollow fiber membrane), pressure swing adsorption (PSA) and methane steam reforming (SMR) is proposed. The process uses membrane separation and PSA to produce high-purity hydrogen for fuel cells. The methane-rich membrane residue gas is used as the feed gas of the reforming reactor. The hydrogen-containing gas at the outlet of the reactor enters the membrane separator to further improve the hydrogen yield. In addition, based on the principle of temperature gradient utilization, the high-temperature gas at the outlet of the reactor is used as the heat source for the system. Through a synergy of separation and reaction, the process supports the low-cost and efficient production of fuel cell hydrogen from COG. The proposed process was established using UniSim Design. The key variables were determined by sensitivity analysis, and the response surface methodology based on Box-Behnken design (BBD) method was further used to optimize the key variables. The optimal operating variables are as follows: the area of the third hydrogen membrane (HM3) is 3000 m2, the reaction temperature is 917 K and the molar ratio of steam to methane (S/C) is 1.12. The cost of the hydrogen production process is 1.56 $/kg, which means it has good prospects for use in industrial applications.& COPY; 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Due to the low boiling point of helium, the nitrogen-rich off gas of the nitrogen rejection unit (NRU) in the liquefied natural gas (LNG) plant usually contains a small amount of CH4, approximately 1-4% He, and associated gases, such as H-2. However, it is difficult to separate hydrogen and helium. Here, we propose two different integrated processes coupled with membrane separation, pressure swing adsorption (PSA), and the electrochemical hydrogen pump (EHP) based on different sequences of hydrogen gas removal. Both processes use membrane separation and PSA in order to recover and purify helium, and the EHP is used to remove hydrogen. The processes were strictly simulated using UniSim Design, and an economic assessment was conducted. The results of the economic assessment show that flowsheet #2 was more cost-effective due to the significant reduction in the capacity of the compressor and PSA because of the pre-removal of hydrogen. Additionally, using the response surface methodology (RSM), a Box-Behnken design experiment was conducted, and an accurate and reliable quadratic response surface regression model was fitted through variance analysis. The optimized operating parameters for the integrated process were determined as follows: the membrane area of M101 was 966.6 m(2), the permeate pressure of M101 was 100 kPa, and the membrane area of M102 was 41.2 m(2). The maximum recovery fraction was 90.66%, and the minimum cost of helium production was 2.21 $/kg. Thus, proposed flowsheet #2 has prospects and value for industrial application.

Petrochemical tail gases have various components and many separation methods, thus there are many possible design schemes, making it difficult to determine the optimal scheme. In this work, a graphic synthesis method was used to design a hybrid multi-input refinery gas separation process consisting of membranes, pressure swing adsorption (PSA), shallow condensation (SC), and distillation units for the production of valuable products which include H2, C2, LPG, and C5+. Ten refinery gases with different compositions were visualized and represented with vector couples in a triangular coordinate system. Firstly, according to the characteristics of the refinery gases, the feeds located in the same region of the triangular coordinate system were merged to simplify the number of input streams, then ten original input streams were combined into two mixed streams. Secondly, the optimal separation sequence was determined by using the unit selection rules of a graphic synthesis method. Thirdly, the process was simulated in UniSim Design and the process parameters were determined by sensitivity analysis. Finally, economic assessments were carried out, which led to an annual gross product profit of USD 38.62 × 106 and a payback period of less than 4 months.

In this work, a partial element stage cut electrochemical hydrogen pump (EHP) model for multiple H2-contaning gases separation and hydrogen compression which embed real factors (anode impurity diffusion, hydrogen back-diffusion and anode catalyst deactivation) was established to study EHP performance accurately under full hydrogen concentration. The accuracy and reliability of proposed model were verified from four aspects (current density distribution, polarization curve, hydrogen recovery and purity) under different feedstock systems and wide pressure range. The model has good applicability and accuracy (R^2≥0.96, simulation and experiment results comparison). Simulation results show that high hydrogen back-diffusion ratio can cause low energy efficiency under high cathode pressure and low feedstock hydrogen content. The variation law of hydrogen purity under multi-operating conditions was studied, which shows dual-effect (PEM and GDL resistance) can affect hydrogen purity prominently through current density under low feedstock hydrogen content and applied potential.

In this work, the models of desulfurization and denitrification are added to solve the problem of SO2 and NOX standardized discharge. The design and optimization strategy of steam power system (SPS) considering contaminant emissions reduction technology is proposed to achieve the trade-off between economic and environmental goals. Detailed superstructure networks of desulfurization based on wet limestone flue gas desulfurization and denitrification based on selective catalytic reduction were established and embedded in the SPS model. Then, based on this combined superstructure model, a mathematical formulation of multiple objective mixed integer nonlinear programming describing the SPS coupled with desulfurization and denitrification was established. The steam flow rate, outlet enthalpy, the consumption of the turbine power of the direct drive equipment and the electricity generated by the turbine, the flow rate and efficiency of desulfurization and denitrification are chosen as the optimization variables. The operating conditions and equipment parameters of the global system are optimized. Finally, the second-generation non-dominated sorting genetic algorithm (NSGA-II) was applied to obtain the Pareto optimization curve, exploring trade-offs between economic and environmental goals. Two case studies are used to assess the applicability and performance of the optimization formulation and solution algorithm.