Influence of Modified Bio-Coals on Carbonization and Bio-Coke Reactivity

Substitution of coal in coking coal blend with bio-coal is a potential way to reduce fossil CO2 emissions from iron and steelmaking. The current study aims to explore possible means to counteract negative influence from bio-coal in cokemaking. Washing and kaolin coating of bio-coals were conducted to remove or bind part of the compounds in the bio-coal ash that catalyzes the gasification of coke with CO2. To further explore how the increase in coke reactivity is related to more reactive carbon in bio-coal or catalytic oxides in bio-coal ash, ash was produced from a corresponding amount of bio-coal and added to the coking coal blend for carbonization. The reaction behavior of coals and bio-coals under carbonization conditions was studied in a thermogravimetric analyzer equipped with a mass spectrometer during carbonization. The impact of the bio-coal addition on the fluidity of the coking coal blend was studied in optical dilatometer tests for coking coal blends with and without the addition of bio-coal or bio-coal ash. The result shows that the washing of bio-coal will result in lower or even negative dilatation. The washing of bio-coals containing a higher amount of catalytic components will reduce the negative effect on bio-coke reactivity, especially with acetic acid washing when the start of gasification temperature is less lowered. The addition of bio-coal coated with 5% kaolin do not significantly lower the dilatation-relative reference coking coal blend. The reactivity of bio-cokes containing bio-coal coated with kaolin-containing potassium oxide was higher in comparison to bio-coke containing the original bio-coal. The addition of ash from 5% of torrefied bio-coals has a moderate effect on lowering the start of gasification temperature, which indicates that the reactive carbon originating from bio-coal has a larger impact.

Research on a soft-measurement model of gasification temperature based on recurrent neural network

Gasification temperature measurement is one of the most challenging tasks in an entrained-flow gasifier and often requires indirect calculation using the soft-sensor method, a parameter prediction method using other parameters that are more easily measurable and using correlation equations that are widely accepted in the gasification field for the temperature data. Machine learning is a non-linear prediction method that can adequately act as a soft sensor. Furthermore, the recurrent neural network (RNN) has the function of memorization, which makes it capable of learning how to deal with temporal order. In this paper, the oxygen–coal ratio, CH4 content and CO2 content determined through the process analysis of a 3000-t/d coal-water slurry gasifier are used as input parameters for the soft sensor of the gasification temperature. The RNN model and back propagation (BP) neural network model are then established with training-set data from gasification results. Compared with prediction set data from the gasification results, the RNN model is found to be much better than the BP neural network based on important indexes such as the mean square error (MSE), mean absolute error (MAE) and standard deviation (SD). The results show that the MSE of the prediction set of the RNN model is 6.25°C, the MAE is 10.33°C and the SD is 3.88°C, respectively. The overall accuracy, the average accuracy and the stability effects are well within the accepted ranges for the results as such.

Simulation of biomass and municipal solid waste pellet gasification using Aspen Plus

The work deals with the simulation of biomass and municipal solid waste pellet gasification using Aspen Plus software. The effects of key parameters on the composition of the emitted gas are discussed, including gasification temperature, moisture content, and equivalence ratio. The sensitivity analysis was studied with the Aspen Plus Software, which includes FORTRAN modules. The simulation is validated using experimental results, which revealed that it was roughly correct. Using air as the gasification agent, the sensitivity analysis findings confirm higher temperatures promote syngas production with increased hydrogen and energy content. The simulation results demonstrated that CO2 concentration (3.95%) increases from 450°C to 600°C and then decreased drastically near 0.225kmol/hr. at 900°C. As the gasification temperature rises from 450°C to 900°C, the CO concentration rises and the H2: CO ratio falls. At 900°C, increasing the gasification temperature results in a product gas with more H2 (65%) and CO (12.43%), resulting in a higher calorific value, whereas the contents of CH4, CO2, and H2O followed an inverse correlation. CH4 decreased with temperature because of the formation of exothermic methane reactions. When the gasification process reaches 800°C, all components except CO2 become steady, and gasification reactions were achieved. The equivalence ratio (ER) ranged from 0.2 to 0.3. The gas produced by a gasifier is highly dependent on the ER value. The ER determines the gas quality, and it must be less than 1 to ensure that it gasifies the fuel rather than burnt. Moisture content was 10wt. %, this is an essential parameter for the optimum conditions during the gasification process. Moisture content determines the gas characteristics at the exit phase. The model predictions and calculated values are in good agreement.

Carbon–CO2 Gasification to CO by Microwave Heating

Renewable energies such as solar or wind energy are highly unreliable, owing to uncertain energy intensity and discontinuity. This shortcoming could be overcome by converting renewable energies to a form such as chemical fuel storage. In the present study, we created an energy conversion system that uses microwave heating and a carbon receptor to transform CO2, a greenhouse gas, into CO chemical fuel. The parametric investigation found that increasing the gasification temperature and feed gas temperature decreased the gas feed rate. In addition, the use of a carbon or charcoal receptor enhanced CO2 conversion and heating values. Under ideal operating circumstances, CO2 conversion was 83%, indicating that steady functioning was maintained consistently.

Effect of Woody Biomass Gasification Process Conditions on the Composition of the Producer Gas

Using woody biomass in thermochemical gasification can be a viable alternative for producing renewable energy. The type of biomass and the process parameters influence the producer gas composition and quality. This paper presents research on the composition of the producer gas from the gasification of three woody biomass species: spruce, alder, and pine. The experiments were conducted in a drop-tube reactor at temperatures of 750, 850, and 950 °C, using air as the gasifying agent, with equivalence ratios of 0.38 and 0.19. Gas chromatography with a thermal conductivity detector was used to determine the composition of the producer gas, while the production of total organic compounds was detected using Fourier-transform infrared spectroscopy. All three wood species exhibited very similar producer gas composition. The highest concentration of combustible gases was recorded at 950 °C, with an average of 4.1, 20.5, and 4.6 vol% for H2, CO, and CH4, respectively, and a LHV ranging from 4.3–5.1 MJ/m3. The results were in accordance with other gasification studies of woody species. Higher temperatures enhanced the composition of the producer gas by promoting endothermic and exothermic gasification reactions, increasing gas production while lowering solid and tar yields. The highest concentrations of combustible gases were observed with an equivalence ratio of 0.38. Continuous TOC measurement allowed understanding the evolution of the gasification process and the relation between a higher production of TOC and CO as the gasification temperature raised.

Bioethanol Production via Herbaceous and Agricultural Biomass Gasification Integrated with Syngas Fermentation

In this paper, a simulation model based on the non-stoichiometric equilibrium method via ASPEN Plus was established to analyze the gasification performance of 20 herbaceous and agricultural biomasses (H&ABs) linked with syngas fermentation and product purification units for ethanol production. The established simulation model does not consider the gasification system as a black box; it focuses the important processes in gasification such as drying, pyrolysis, gasification, and connection with bioethanol production plants. The results for the 20 H&AB options suggest that the specific mass flow rate of bioethanol from 1 kg of biomass input to the unit is in the range of 99–250 g/kg, and between them, the system fed by hazelnut shell biomass remarkably outranked other alternatives by 241 g/kg production due to the high beneficial results gained from the performance analysis. Additionally, a sensitivity analysis was performed by changing operating conditions such as gasification temperature and air-to-fuel ratio. The modeling results are given and discussed. The established model could be a useful approach to evaluate the impacts of a huge numbers of biomasses and operating parameters on bioethanol output.

Environmental and thermodynamic performance assessment of biomass gasification process for hydrogen production in a downdraft gasifier

Gasification is one of the most efficient techniques for sustainable hydrogen production from biomass. In this study, a comparative performance analysis of the gasification process using various types of biomass materials was undertaken via thermodynamic approach. Air, steam, and air/steam as the traditional gasifying agents were applied to provide an opportunity to choose the most proper agent in the process. This paper also evaluates the environmental impacts of the process in terms of CO2 emission by using Aspen Energy Analyzer. The effects of agent to biomass molar ratio, agent inlet temperature, moisture content of biomass material, and gasification temperature were estimated based on the producer gas compositions, hydrogen yield and heating values. The results indicate that the highest hydrogen yield (0.074 g H2/g biomass) was obtained in the steam gasification of plastic, while air gasification of paper generates the lowest one. It was also observed that manure is the most beneficial from environmental perspectives, while tire and plastic have the highest contribution to CO2 emission and consequently global warming. The higher values of hydrogen production and LHV of produced gas are associated respectively with using steam, air/steam, and air as the gasification agents. The lowest value of CO2 emission is obtained for air, air/steam, and steam as the gasifying agents, respectively.

Simulation of a Downdraft Gasifier for Production of Syngas from Different Biomass Feedstocks

In the evaluation of gasification processes, estimating the composition of the fuel gas for different conditions is fundamental to identify the best operating conditions. In this way, modeling and simulation of gasification provide an analysis of the process performance, allowing for resource and time savings in pilot-scale process operation, as it predicts the behavior and analyzes the effects of different variables on the process. Thus, the focus of this work was the modeling and simulation of biomass gasification processes using the UniSim Design chemical process software, in order to satisfactorily reproduce the operation behavior of a downdraft gasifier. The study was performed for two residual biomasses (forest and agricultural) in order to predict the produced syngas composition. The reactors simulated gasification by minimizing the free energy of Gibbs. The main operating parameters considered were the equivalence ratio (ER), steam to biomass ratio (SBR), and gasification temperature (independent variables). In the simulations, a sensitivity analysis was carried out, where the effects of these parameters on the composition of syngas, flow of syngas, and heating value (dependent variables) were studied, in order to maximize these three variables in the process with the choice of the best parameters of operation. The model is able to predict the performance of the gasifier and it is qualified to analyze the behavior of the independent parameters in the gasification results. With a temperature between 850 and 950 °C, SBR up to 0.2, and ER between 0.3 and 0.5, the best operating conditions are obtained for maximizing the composition of the syngas in CO and H2.

H2-Rich and Tar-Free Downstream Gasification Reaction of EFB by Using the Malaysian Dolomite as a Secondary Catalyst

In this study, Malaysian dolomites as secondary catalysts are placed at the downstream of the fluidized-bed gasifier. Three types of Malaysian dolomites with different elemental ratios of CaO-MgO content denoted as P1, P2, and P3 are investigated with EFB gasification reaction at different cracking temperatures (700–900 °C). The performance of the catalysts with a variation of catalyst to biomass weight ratio (C/B) (0.05 to 0.30 w/w) is evaluated. The findings showed that the total gas yield increased by 20%, hydrogen increased by 66%, along with an almost 99% reduction in tar content with P1 catalyst with the following reaction conditions: gasification temperature of 850 °C, equivalence ratio (ER) of 0.25, and cracking temperature of 900 °C. Malaysia dolomite could be a secondary catalyst to provide a better alternative, tar-free hydrogen-rich gas with the possibility of regeneration and re-use.

Performance analysis of power generation by wood and woody biomass gasification in a downdraft gasifier

An equilibrium simulation model was developed by applying Aspen Plus to evaluate the performance of 28 wood and woody biomass (W&WB) gasification in a downdraft gasifier integrated with power production unit. The developed simulation model does not focus the gasification process as a closed box, it considers important processes in gasification like drying, pyrolysis, combustion, gasification and integrated with power production plant (combustion chamber plus gas turbine). The results for the 28 W&WB alternatives show that the net power produced from 1-ton feedstock entering to the gasification system is between the interval [0-400 kW/ton] and among them, gasification system derived from Tamarack bark biomass significantly outranks all other systems by producing 363 kW/ton, owing to the favorable results obtained in the performance analysis. Moreover, effect of various operating parameters such as gasification temperature and air to fuel ratio (AFR) on the system performance was carried out. Finally, the developed model is applied as an effective tool to assess the impact of so many biomasses and operating parameters on output power.