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Biomass gasification process has been predicted and optimized based on process temperature, pressure, and gasifying agent ratios by integrating Aspen Plus simulation with the high-dimensional model representation (HDMR) method. Results show that temperature and biomass to air ratio (BMR) have significant effects on gasification process. HDMR models demonstrated high performance in predicting H2, net heat (NH), higher heating value (HHV), and lower heating value (LHV) with coefficients of determination 0.96, 0.97, 0.99, and 0.99, respectively. HDMR-based single-objective optimization has maximum outputs for H2, HHV, and LHV (0.369 of mole fractions, 340 kJ/mol, and 305 kJ/mol, respectively) but NH would be negative at these conditions, which indicates that process is not energy-efficient. The optimal solution was determined by the multiobjective which produced 0.24 mole fraction of H2, 158.17 kJ/mol of HHV, 142.48 kJ/mol of LHV, and 442.37 kJ/s NH at 765°C, 0.59 BMR, and 1 bar. Therefore, these parameters can provide an optimal solution for increasing gasification yield, keeping process energy-efficient. [ABSTRACT FROM AUTHOR]

A novel co-valorization process integrating plasma gasification and Fischer-Tropsch synthesis is designed for converting medical waste (MW) and biomass waste (BMW) into mixed e-fuels where the additional required hydrogen is supplied by solar-based electrolysis. Optimization and comprehensive assessments have been conducted for three scenarios with different ratios of BMW. Operations optimization based on genetic algorithm (GA) has led to a remarkable enhancement in the quality of syngas, with a more than 10% increase in H 2 mole fraction. Techno-economic analysis reveals the net present values (NPVs) of three scenarios are −2.56 MM$, 3.38 MM$ and 40.1 MM$ with internal rates of return of 3.4 %, 9.5 % and 14.0 %. By improving the subside of MW treatment, the economic viabilities of all scenarios have been enhanced significantly with higher positive NPVs. Environmental assessment shows ∼2.5 kg eqCO 2 /kg waste and ∼0.1 g eqCO 2 per MJ fuel have been generated across the system boundary and the operation of the designed process has been identified to be the largest source of emissions. These findings underscore the potential of our integrated approach to efficiently convert MW and BMW into valuable e-fuels while maintaining a focus on environmental sustainability. [Display omitted] • Co-valorization process was designed for converting wastes into mixed e-fuel. • Plasma gasification and Fischer-Tropsch synthesis were integrated. • Scenarios with different blending ration were analyzed. • The H 2 fraction in syngas has been improved by over 10% via optimization. • Economic and environmental assessments were performed. [ABSTRACT FROM AUTHOR]

An innovative valorization process for biomass waste treatment has been developed in this study. The basic simulation process developed considering experimental studies, and it has been optimized by application of a pattern search algorithm to obtain the optimum output of energy efficiency, economic performance, and process safety index (PSI). Mainly, three different scenarios have been analyzed based on the sustainability index (SI). These SI has been determined through energy, economy, safety, and electric power potential. According to the results of the SI, the optimized processes are more sustainable (SI = 0.517 to 0.563) in all scenarios as compared to the basic process (SI = 0.503). Similarly, the economic analysis in terms of internal rate of return (%) of the basic process varies from 37 to 2% when the process efficiency dropped from 100 to 80%, and it varies from 44 to 6% for the optimized process without any subsidy. The optimized process has a potential of 2788–4044 kW of electric power generation from thermal energy of the process while it is only 2302 kW for basic scenario. Therefore, the optimized process has better energy, economic, electric power, and safety performances, thus it is more sustainable as compared with the basic process. [Display omitted] • Integration of pyrolysis and gasification for biomass valorization. • Pattern search algorithm application for valorization process optimization. • A novel sustainability index has been proposed. • Electricity potential from optimized process thermal energy is 2788–4044 kW. • Energy efficiency of the processes varies from 46% to 66%. [ABSTRACT FROM AUTHOR]

A novel configuration of a tri-generation process for poultry litter valorization, including gasification, solid oxide fuel cell (SOFC), and combined heat and power system was examined in this research. Multi-level factorial, design of experiment methodology has been adopted to extract the simulation data from Aspen Plus simulation model by changing one parameter at a time. Extreme gradient boosting has been applied on the factorial design data to predict and optimize the parametric yield of this model. Results of gasification process sensitivity analysis show that pressure has no significant effect on output yield, but it has a negative effect on SOFC voltage. While gasification process temperature operating condition around 600 °C and 0.25–0.33 biomass to air ratio (BMR) can generate optimum hydrogen yield in syngas. Coefficient of determinant (R2) for Extreme Gradient Booster (XGB) model is greater than 0.97 for all dependent variables. According to XGB results, BMR is the most contributing factor which affects the output of this study. Exergy efficiency of this tri-generation process is 34.6% more than the gasification process. Therefore, based on the findings of this model, it is concluded that this tri-generation process could be the better possible solution for poultry litter valorization. • 34.6% more exergy efficiency by tri-generation of poultry litter valorization. • Gasification process prediction by Extreme Gradient Boosting prediction model. • Optimum yield of H 2 at 600 °C and 0.25–0.33 biomass to air ratio. • Multilevel factorial design of experiment for gasification process optimization. • Solid Oxide Fuel Cell current and voltage calculations and prediction model. [ABSTRACT FROM AUTHOR]

In this work, a co-gasification process of sewage sludge and the poultry litter for hydrogen production was developed which involves gasification, water gas shift reaction, acid gas absorption and combustion for power generation. Based on the situations in Hong Kong, the complete processing system was simulated and optimized by developing a composite sustainability objective. The single objective was obtained by the fuzzy method after collecting the decision-making preferences on product yield, economic cost, safety index, environmental impacts, and exergy efficiency. Optimization results showed the exergy efficiency was 30.75%, and the gas turbine operation was most hazardous. The total life cycle greenhouse gas emission was estimated to be 832.58 tons/day with a hydrogen yield of about 47.92 tons/day according to the systematic analysis. Moreover, a subsidy of 115.65 $/ton waste can achieve a relatively attractive profit for the waste-to-H 2 process, which was validated by an IRR value of 10% and a positive NPV value in 20 years. The economic sensitivity analysis was finished by testing the influence of some key factors. It was indicated that the subsidy fees, H 2 market price, and total equipment cost were relatively more important in the financial profit for this process. [Display omitted] • A systematic waste co-valorisation process for H 2 production is proposed based on the gasification conversion. • Process optimization is finished by stochastic optimization with a constructed sustainability objetive. • Total life cycle GHG emission was 832.58 tons/day with a H 2 yield of about 47.92 tons/day. • The subsidy fees, H 2 market price, and total equipment cost is quite influential to the project economics. • A subsidy of 115.65 $/ton waste should be supported for good economic profit. [ABSTRACT FROM AUTHOR]