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“Assessing the future of second-generation bioethanol by 2030 : a techno-economic assessment integrating technology learning curves”. Vasilakou K, Nimmegeers P, Thomassen G, Billen P, Van Passel S, Applied energy 344, 121263 (2023). http://doi.org/10.1016/J.APENERGY.2023.121263
Abstract: Lignocellulosic biomass is the most abundant source of renewable biomass and is seen as a high-potential replacement for petroleum-based resources. The conversion technologies to advanced biofuels are still at a low maturity level, thus allowing for future cost reductions through technological learning. This fact is barely considered in state-of-the-art techno-economic assessments and a structured approach to account for technological learning in techno-economic assessments is needed. In this study, a framework for techno-economic assessments of advanced biofuels, integrating learning curves, is proposed. As a validation of this framework, the economic feasibility of the valorization of corn stover for the production of second-generation bioethanol in Belgium is studied. Process flowsheet simulations in Aspen Plus are developed, with an emphasis on the comparison of four different pretreatment technologies and two plant capacities at 156 dry kt biomass/y and 667 dry kt/y. The dilute acid pretreatment model of the large-scale biorefinery required the lowest minimum learning rate to reach an economically feasible biorefinery by 2030, being 3.9%, almost half as the one calculated for the smaller scale plant. This learning rate seems to be achievable based on learning rates commonly estimated in literature. We conclude that there is a potential for advanced ethanol production in Belgium under the current state of technology for large-scale biorefineries, which require additional biomass imports, when accounting for future cost reductions through learning
Keywords: A1 Journal article; Economics; Engineering sciences. Technology; Engineering Management (ENM); Intelligence in PRocesses, Advanced Catalysts and Solvents (iPRACS)
DOI: 10.1016/J.APENERGY.2023.121263
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“A Pareto aggregation approach for environmental-economic multi-objective optimization applied on a second-generation bioethanol production model”. Vasilakou K, Billen P, Van Passel S, Nimmegeers P, Energy conversion and management 303, 118184 (2024). http://doi.org/10.1016/J.ENCONMAN.2024.118184
Abstract: Multi-objective optimization is an important decision-making tool for energy processes, as multiple targets need to be achieved. These objectives are usually conflicting since a single solution cannot be optimal for all objectives, resulting in a set of Pareto-optimal solutions. Multiple indicators might be available to describe a sustainability objective, such as the environmental impact which is commonly evaluated by performing a life cycle assessment. In this study, Pareto aggregation is proposed as a method which employs a novel multi-objective optimization-based approach as an alternative to the classically used aggregation in life cycle assessment. This method identifies conflicting environmental indicators and performs an aggregation among those that require a trade-off. An environmental-economic optimization of a second-generation bioethanol plant is used to illustrate and evaluate the proposed method. Process parameters from a biochemical conversion pathway flowsheet simulation model are chosen as optimization variables. To reduce the computational time, surrogate models, based on artificial neural networks, are used. Out of the eighteen ReCiPe Midpoint environmental indicators, five were identified as conflicting, resulting in an aggregated environmental objective, which was then traded off with the economic objective function, chosen as the levelized cost of ethanol. Comparison with the widely used single-score EcoIndicator99 showed that the Pareto aggregation method can reduce most of the environmental indicators by up to 6.5%. This research provides an insight on non-redundant objective functions, aiming at reducing the dimensionality of multi-objective optimization problems, while taking into consideration decision-makers’ preferences.
Keywords: A1 Journal article; Economics; Engineering sciences. Technology; Engineering Management (ENM); Intelligence in PRocesses, Advanced Catalysts and Solvents (iPRACS)
DOI: 10.1016/J.ENCONMAN.2024.118184
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“Investigating the technical and economic potential of solid-state fungal pretreatment at nonsterile conditions for sugar production from poplar wood”. Wittner N, Vasilakou K, Broos W, Vlaeminck SE, Nimmegeers P, Cornet I, Industrial and engineering chemistry research , 1 (2023). http://doi.org/10.1021/ACS.IECR.3C02316
Abstract: Pretreatment is crucial for the conversion of lignocellulose to biofuels. Unlike conventional chemical/physicochemical methods, fungal pretreatment uses white-rot fungi and mild reaction conditions. However, challenges, including substrate sterilization, long duration, and low sugar yields associated with this method, contribute to lower techno-economic performance, an aspect that has rarely been investigated. This study aimed to evaluate the feasibility of fungal pretreatment of nonsterilized poplar wood. Various factors, including inoculum types, fermentation supplements, and cultivation methods, were investigated to optimize the process. A techno-economic assessment of the optimized processes was performed at a full biorefinery scale. The scenario using nonsterilized wood as a substrate, precolonized wood as an inoculum, and a 4 week pretreatment showed a 14.5% reduction in sugar production costs (€2.15/kg) compared to using sterilized wood. Although the evaluation of nonsterilized wood pretreatment showed promising cost reductions, fungal pretreatment remained more expensive than conventional methods due to the significant capital investment required.
Keywords: A1 Journal article; Economics; Engineering sciences. Technology; Engineering Management (ENM); Sustainable Energy, Air and Water Technology (DuEL); Biochemical Wastewater Valorization & Engineering (BioWaVE); Intelligence in PRocesses, Advanced Catalysts and Solvents (iPRACS)
Impact Factor: 4.2
DOI: 10.1021/ACS.IECR.3C02316
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“Geospatial environmental techno-economic assessment of pretreatment technologies for bioethanol production”. Vasilakou K, Nimmegeers P, Billen P, Van Passel S, Renewable and sustainable energy reviews 187, 113743 (2023). http://doi.org/10.1016/J.RSER.2023.113743
Abstract: Second-generation biofuels, starting from lignocellulosic biomass, are considered as a renewable alternative for fossil fuels with lower environmental impact and potentially higher supply and energy security. The economic and environmental performance of second-generation bioethanol production from corn stover in the European Union (EU) is studied, starting in Belgium as base case. A comparative environmental techno-economic assessment has been conducted, with process simulations in Aspen Plus and corn stover availability data in thirteen EU countries to calculate minimum ethanol selling prices (MESP) and Greenhouse gas emissions (GHGe). In this analysis, the emphasis is on the comparison of different pretreatment technologies, namely (i) dilute acid, (ii) alkaline, (iii) steam explosion and (iv) liquid hot water. Dilute acid showed the best economic and environmental performance for the base case scenario. Within the EU, Hungary and Romania presented the lowest MESP for the steam explosion model at 0.39 and 0.43 EUR/L respectively. Poland showed the lowest GHGe, at 0.46 kg CO2eq/L for the alkaline model, mainly due to the avoided product allocation on electricity and its high carbon intensity in the electricity generation sector. The second lowest GHGe were obtained in France for the dilute acid model and are attributed to its low agricultural emissions intensity. This study identifies a location-dependence of the economic and environmental performance of pretreatment technologies, which can be extrapolated from the EU to other large regions around the world and should be taken into consideration by decision-makers.
Keywords: A1 Journal article; Economics; Engineering sciences. Technology; Engineering Management (ENM); Intelligence in PRocesses, Advanced Catalysts and Solvents (iPRACS)
DOI: 10.1016/J.RSER.2023.113743
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