Production & Supply Chain

Ambitious decarbonization pathways to limit the global temperature rise to well below 2 ◦C will require largescale CO2 removal from the atmosphere. One promising avenue for achieving this goal is hydrogen production from biomass with CO2 capture. The present study investigates the techno-economic prospects of a novel biomass-to-hydrogen process configuration based on the gas switching integrated gasification (GSIG) concept. GSIG applies the gas switching combustion principle to indirectly combust off-gas fuel from the pressure swing adsorption unit in tubular reactors integrated into the gasifier to improve efficiency and CO2 capture. In this study these efficiency gains facilitated a 5% reduction in the levelized cost of hydrogen (LCOH) relative to conventional O2-blown fluidized bed gasification with pre-combustion CO2 capture even though the larger and more complex gasifier cancelled out the capital cost savings from avoiding the air separation and CO2 capture units. The economic assessment also demonstrated that advanced gas treatment using a tar cracker instead of a direct water wash can further reduce the LCOH by 12% and that the CO2 prices in excess of 100 €/ton consistent with ambitious decarbonization pathways will make this negative-emission technology economically highly attractive. Based on these results further research into the GSIG concept to facilitate more efficient utilization of limited biomass resources can be recommended.

An investigation was conducted to determine the effects of operating parameters for various electrode types on hydrogen gas production through electrolysis as well as to evaluate the efficiency of the polymer electrolyte membrane (PEM) electrolyzer. Deionized (DI) water was fed to a single-cell PEM electrolyzer with an active area of 36 cm2 . Parameters such as power supply (50–500 mA/cm2 ) feed water flow rate (0.5–5 mL/min) water temperature (25−80 ◦C) and type of anode electrocatalyst (0.5 mg/cm2 PtC [60%] 1.5 mg/cm2 IrRuOx with 1.5 mg/cm2 PtB 3.0 mg/cm2 IrRuOx and 3.0 mg/cm2 PtB) were varied. The effects of these parameter changes were then analyzed in terms of the polarization curve hydrogen flowrate power consumption voltaic efficiency and energy efficiency. The best electrolysis performance was observed at a DI water feed flowrate of 2 mL/min and a cell temperature of 70 ◦C using a membrane electrode assembly that has a 3.0 mg/cm2 IrRuOx catalyst at the anode side. This improved performance of the PEM electrolyzer is due to the reduction in activation as well as ohmic losses. Furthermore the energy consumption was optimal when the current density was about 200 mA/cm2 with voltaic and energy efficiencies of 85% and 67.5% respectively. This result indicates low electrical energy consumption which can lower the operating cost and increase the performance of PEM electrolyzers. Therefore the optimal operating parameters are crucial to ensure the ideal performance and durability of the PEM electrolyzer as well as lower its operating costs.

The production and application of hydrogen an environmentally friendly energy source have been attracting increasing interest of late. Although steam methane reforming (SMR) method is used to produce hydrogen it is difficult to build a high-fidelity model because the existing equation-oriented theoretical model cannot be used to clearly understand the heat-transfer phenomenon of a complicated reforming reactor. Herein we developed an artificial neural network (ANN)-based data-driven model using 485710 actual operation datasets for optimizing the SMR process. Data preprocessing including outlier removal and noise filtering was performed to improve the data quality. A model with high accuracy (average R2 = 0.9987) was developed which can predict six variables through hyperparameter tuning of a neural network model as follows: syngas flow rate; CO CO2 CH4 and H2 compositions; and steam temperature. During optimization the search spaces for nine operating variables namely the natural gas flow rate for the feed and fuel hydrogen flow rate for desulfurization water flow rate and temperature air flow rate SMR inlet temperature and pressure and low-temperature shift (LTS) inlet temperature were defined and applied to the developed model for predicting the thermal efficiencies for 387420489 cases. Subsequently five constraints were established to consider the feasibility of the process and the decision variables with the highest process thermal efficiency were determined. The process operating conditions showed a thermal efficiency of 85.6%.

The electrification of final energy uses is a key strategy to reach the desired scenario with zero greenhouse gas emissions. Many of them can be electrified with more or less difficulty but there is a part that is difficult to electrify at a competitive cost: heavy road transport maritime and air transport and some industrial processes are some examples. For this reason the possibility of using other energy vectors rather than electricity should be explored. Hydrogen can be considered a real alternative especially considering that this transition should not be carried out immediately because initially the electrification would be carried out in those energy uses that are considered most feasible for this conversion. The Canary Islands’ government is making considerable efforts to promote a carbon-free energy mix starting with renewable energy for electricity generation. Still in the early–mid 2030s it will be necessary to substitute heavy transport fossil fuel. For this purpose HOMER software was used to analyze the feasibility of hydrogen production using surplus electricity produced by the future electricity system. The results of previous research on the optimal generation MIX for Grand Canary Island based exclusively on renewable sources were used. This previous research considers three possible scenarios where electricity surplus is in the range of 2.3–4.9 TWh/year. Several optimized scenarios using demand-side management techniques were also studied. Therefore based on the electricity surpluses of these scenarios the optimization of hydrogen production and storage systems was carried out always covering at least the final hydrogen demand of the island. As a result it is concluded that it would be possible to produce 3.5 × 104 to 7.68 × 104 t of H2/year. In these scenarios 3.15 × 105 to 6.91 × 105 t of water per year would be required and there could be a potential production of 2.8 × 105 to 6.14 × 105 t of O2 per year.

A combined ultra-short-term wind power prediction strategy with high robustness based on least squares support vector machine (LSSVM) has been proposed in order to solve the wind abandonment caused by wind power randomness and realize efficient hydrogen production under wide power fluctuation. Firstly the original wind power data is decomposed into sub-modes with different bandwidth by variational modal decomposition (VMD) which reduces the influence of random noise and mode mixing significantly. Then dragonfly algorithm (DA) is introduced to optimize LSSVM kernel function and the combined ultra-short-term wind power prediction strategy which meets the time resolution and accuracy requirements of electrolytic cell control has been established finally. This model is validated by a wind power hydrogen production demonstration project output in the middle east of China. The superior prediction accuracy for high volatility wind power data is verified and the algorithm provides theoretical basis to improve the control of wind power hydrogen production system

The gasification technology of refuse-derived fuels (RDF) can represent a future alternative to the global hydrogen production and a pathway for the development of the circular economy. The paper presents an innovative way of utilizing RDF through their oxygen/steam co-gasification with bituminous coal to hydrogen rich gas. Five different RDF samples (RDF1÷RDF5) were investigated. The in-depth analyses of the co-gasification of bituminous coal blends with different amounts of RDF (10 15 and 20%w/w) under various temperature conditions were conducted with the application of Hierarchical Clustering Analysis (HCA). The results of the research study revealed a decrease in the total gas yield as well as in the hydrogen yield observed with the increase in the RDF fraction in the fuel blend. The lowest hydrogen yield and the highest carbon conversion were noted for the co-gasification tests of coal blends with 20%w/w for all the studied RDFs. The SEM-EDS (Scanning Electron Microscopy with Energy Dispersive Spectroscopy) and WDXRF (Wavelength Dispersive X-ray Fluorescence) results showed a significantly higher H2 yield in RDF2 co-gasification with coal in comparison with all the remaining RDFs due to the higher concentration of calcium in the sample. The molecular structure analysis of polymers using Fourier transform infrared spectroscopy (FTIR) demonstrated that the most prevalent synthetic polymers in RDF2 are polyethylene terephthalate and polyvinyl chloride characterized by the lowest thermal stability compared to polyethylene and polypropylene.

Catalytic decomposition of methane (CDM) is a novel technology for turquoise hydrogen production with solid carbon as the by-product instead of CO2. A computational fluid dynamics model was developed to simulate the CDM process in a 3D fixed bed reactor accounting for the impact of carbon deposition on catalytic activity. The model was validated with experimental data and demonstrated its capability to predict hydrogen concentration and catalyst deactivation time under varying operating temperatures and methane flow rates. The catalyst lifespan was characterized by the maximum carbon yield (i.e. gC/gcat) which is a crucial indicator for determining the cost of hydrogen generation. Parametric studies were performed to analyse the effect of inlet gas composition and operating pressure on CDM performance. Various CH4/H2 ratios were simulated to improve the methane conversion efficiency generating a higher amount of hydrogen while increasing the maximum carbon yield up to 49.5 gC/gcat. Additionally higher operating pressure resulted in higher methane decomposition rates which reflects the nature of the chemical kinetics.

Photocatalysts lead vitally to water purifications and decarbonise environment each by wastewater treatment and hydrogen (H2 ) production as a renewable energy source from waterphotolysis. This work deals with the photocatalytic degradation of ciprofloxacin (CIP) and H2 production by novel silver-nanoparticle (AgNPs) based ternary-nanocomposites of thiolated reducegraphene oxide graphitic carbon nitride (AgNPs-S-rGO2%@g-C3N4 ) material. Herein the optimised balanced ratio of thiolated reduce-graphene oxide in prepared ternary-nanocomposites played matchlessly to enhance activity by increasing the charge carriers’ movements via slowing down charge-recombination ratios. Reduced graphene oxide (rGO) >2 wt.% or < 10 nm. Therefore AgNPs-S-rGO2%@g-C3N4 has 3772.5 µmolg−1 h −1 H2 production which is 6.43-fold higher than g-C3N4 having cyclic stability of 96% even after four consecutive cycles. The proposed mechanism for AgNPs-S-rGO2%@g-C3N4 revealed that the photo-excited electrons in the conduction-band of g-C3N4 react with the adhered water moieties to generate H2 .

Biomass gasification is a versatile thermochemical process that can be used for direct energy applications and the production of advanced liquid and gaseous energy carriers. In the present work the results are presented concerning the H2 production at a high purity grade from biomass feedstocks via steam/oxygen gasification. The data demonstrating such a process chain were collected at an innovative gasification prototype plant coupled to a portable purification system (PPS). The overall integration was designed for gas conditioning and purification to hydrogen. By using almond shells as the biomass feedstock from a product gas with an average and stable composition of 40%-v H2 21%-v CO 35%-v CO2 2.5%-v CH4 the PPS unit provided a hydrogen stream with a final concentration of 99.99%-v and a gas yield of 66.4%.

Solar-to-hydrogen plants are predominantly based on steam electrolysis. Steam electrolysis requires water electricity and heat. The excess electric energy is generally converted into hydrogen via an electrolyser. The use of waste heat in hydrogen generation process promises energy efficiency improvement and production fluctuation reductions. This work investigates the techno-economic performance of the proposed system which recovers the waste heat from molten carbonate fuel cell and uses solar energy to produce steam. Comparison of thermally assisted solar system with corresponding solar system is done. The fuel cell provides 80% of the required thermal energy. The solar PV array provides the required electricity. The thermally assisted solar-to-hydrogen system annual energy efficiency (38.5 %) is higher than that of solar- to- hydrogen system. The investment cost of the proposed system is 2.4 % higher than that using only solar parabolic trough collector for the same required amount of heat. The advantage is that the fuel cell simultaneously produces electricity and heat. The recovery of waste heat allows getting an annual overall efficiency of 63.2 % for the molten carbonate fuel cell. It yields 2152 MWh of electricity per year. The 1 MW electrolysers annually generates 74 tonnes of hydrogen.