Conference Agenda

The increasing recognition of hydrogen as both a clean energy source and a vital chemical feedstock has amplified interest in sustainable hydrogen production. Among the various production methods, Steam Methane Reforming (SMR) based on furnace heating is widely regarded as an economic solution for large-scale hydrogen production. However, it requires significant heat energy, which results in a large amount of CO₂ emissions. To address these challenges, Wismann et al. ¹, in collaboration with Haldor Topsoe, developed an innovative Electric Heating Steam Methane Reformer (EH-SMR), providing a promising eco-friendly alternative to the conventional fossil fuel-based furnace heating technology. While several studies, including those by Song et al. ², Mehanovic et al. ³, and Do et al. ⁴ have explored the process design and techno-economic evaluation of hydrogen production, via electric heating reformers, most focus on the EH-SMR process itself, with limited consideration for system-wide energy integration or decarbonization through introducing renewable energy.

This study extends the scope of electrified hydrogen production by systematically evaluating not only the electrification of the SMR process, but also its integration with renewable energy systems. When renewable energy sources, such as solar and wind, are integrated to hydrogen plants, intermittent nature in energy production should be systematically considered, due to their dependence on weather conditions. To ensure a reliable energy supply for the electrified hydrogen plant, battery storage systems are introduced to store any surplus energy or supplement energy in deficit. To effectively manage these fluctuations, a system-wide optimization approach is employed to integrate renewable energy systems, ensuring reliable energy supply and high energy efficiency.

In this contribution, a process modelling and simulation framework is developed for an electrified hydrogen plant, subject to renewable energy integration. Case studies examine the configurational and operational changes when the electrified SMR hydrogen plant is integrated with renewable energy systems. A techno-economic assessment for these case studies is to estimate the Cost of Hydrogen (COH) and CO₂ avoidance cost (CAC), which enhances our understanding on the economic feasibility of renewable-based electrification for hydrogen production. The results of this study provide conceptual guidelines for the clean and sustainable production of hydrogen through renewable-powered electrification, contributing to the decarbonization of the hydrogen industry and the global energy transition.

References

1. S. T. Wismann, J. S. Engbæk, S. B. Vendelbo, F. B. Bendixen, W. L. Eriksen, K. Aasberg-Petersen, C. Frandsen, I. Chorkendorff and P. M. Mortensen, Science, 2019, 364, 756-759.

2. H. Song, Y. Liu, H. Bian, M. Shen and X. Lin, Energy Conversion and Management, 2022, 258, 115513.

3. D. Mehanovic, A. Al-Haiek, P. Leclerc, D. Rancourt, L. Fréchette and M. Picard, Energy Conversion and Management, 2023, 276, 116549.

4. T. N. Do, H. Kwon, M. Park, C. Kim, Y. T. Kim and J. Kim, Energy Conversion and Management, 2023, 279, 116758.

Abstract

To achieve low-carbon hydrogen production, a novel protonic membrane reformer (PMR) has been developed that uses electricity to convert and separate natural gas into pure hydrogen, while generating a CO2-rich retentate gas [1,2]. This syngas composition enables efficient low temperature-based carbon capture, achieving high CO2 capture rates with reduced complexity and cost [3,4]. Thus, the PMR system produces hydrogen with a low carbon intensity, which can be further reduced with low-carbon electricity.

For process intensification, the integration of PMR with CO2 liquefaction offers several potential configurations that optimise energy efficiency and maximise hydrogen and CO2 recovery. This is mainly related to handling of impurities in the retentate such as unconverted methane and carbon monoxide. Earlier studies have focussed on a single configuration of this hybrid system where a water gas shift reactor is used to convert the carbon monoxide and the other impurities are handled by purging a slip stream from the liquefaction unit [5]. This study therefore extends earlier work by proposing and analysing several hybrid configurations that explore different approaches to integrating hydrogen production and CO2 capture.

The focus of this work is on the management of the residual gas from the CO2 liquefaction process, which has a significant impact on system performance. In particular, (1) the residual gas may contain significant amounts of hydrogen, which directly affects the hydrogen recovery rate, and (2) its flow rate affects both power consumption and capital cost when recycled to the PMR for further hydrogen recovery. Through a comparative analysis, this study aims to identify the optimal configuration that balances energy efficiency, hydrogen and CO2 recovery and economic viability.

Reference

[1] Malerød-Fjeld H, Clark D, Yuste-Tirados I, Zanón R, Catalán-Martinez D, Beeaff D, et al. Thermo-electrochemical production of compressed hydrogen from methane with near-zero energy loss. Nature Energy 2017;2:923–31. https://doi.org/10.1038/s41560-017-0029-4.

[2] Clark D, Malerød-Fjeld H, Budd M, Yuste-Tirados I, Beeaff D, Aamodt S, et al. Single-step hydrogen production from NH3, CH4, and biogas in stacked proton ceramic reactors. Science 2022;376:390–3. https://doi.org/10.1126/science.abj3951.

[3] Berstad D, Anantharaman R, Nekså P. Low-temperature CO2 capture technologies – Applications and potential. International Journal of Refrigeration 2013;36:1403–16. https://doi.org/10.1016/j.ijrefrig.2013.03.017.

[4] Kim D, Berstad D, Anantharaman R, Straus J, Peters TA, Gundersen T. Low Temperature Applications for CO2 Capture in Hydrogen Production. Computer Aided Chemical Engineering 2020;48:445–50. https://doi.org/10.1016/B978-0-12-823377-1.50075-6.

[5] Kim D, Liu Z, Anantharaman R, Riboldi L, Odsæter L, Berstad D, et al. Design of a novel hybrid process for membrane assisted clean hydrogen production with CO2 capture through liquefaction. Computer Aided Chemical Engineering 2022;49:127–32. https://doi.org/10.1016/B978-0-323-85159-6.50021-X.

Two classes of technology that can mitigate CO₂ emissions are carbon capture and storage (CCS) and renewable energy generation from sources such as solar and wind. These two technologies have been primarily developed independently. However, their hybridization can offer complementary benefits and lower the cost of greenhouse gas abatement.

Concentrated solar power (CSP) with thermal energy storage (TES) is a promising strategy to deliver cost-effective, reliable, and dispatchable renewable power. Among various TES technologies, thermochemical energy storage (TCES) is especially appealing for the next generation CSP plants because of their high energy density and ability to deliver heat at a high temperature (> 1000 °C). A recent material screening study concluded that due to the low energy density of TCES materials, even the most economically favorable reaction system leads to more than 50% higher LCOE than the monthly average electricity retail price [1].

Accordingly, we propose a novel process that integrates a redox-based TCES system with energy-dense fossil-fuel power plant and CSP. In contrast to the CSP-TCES process, where TCES is used only for energy storage, we propose utilizing the redox system for energy storage and as a source of oxygen for fuel combustion. The integrated process is referred to as CSP-TCES-CCS.

The CSP-TCES-CCS process operates as follows. During the day, the heliostats focus sunlight on the receiver, where photons are absorbed, and heat transfer fluid (HTF) is heated. The flow of HTF is split such that one fraction drives the forward endothermic reaction (M_xO_z ↔ M_xO_y + (z-y)/2 O₂), and the other heats the working fluid. The oxygen released due to the forward endothermic reaction is stored and used for fuel combustion during the night or winter months. The exhaust from fuel combustion mainly contains CO₂ and H₂O, which are cooled and separated using a flash column. The CO₂ stream is then compressed and stored. The reverse exothermic reaction to oxidize the reduced metal oxide occurs in the presence of air. Thus, during the night operation, energy is obtained by reversible exothermic reaction and combusting fuel.

We extend the stochastic programming-based optimization model developed by Bajaj et al. [1] to obtain the optimal design, operating conditions, and system performance of the CSP-TCES-CCS plant. The objective of the optimization model is to minimize the levelized cost of electricity (LCOE). The constraints of the model include mass and energy balances and sizing and performance of the plant components. Our results indicate that the LCOE of the CSP-TCES-CCS process, using natural gas as a fuel and Mn₂O₃/Mn₃O₄ as the redox system, is up to 20% lower than the CSP-TCES process. We note that the energy density of natural gas is more than 100 times that of the Mn₂O₃/Mn₃O₄ system. While the CSP-TCES-CCS process incurs additional costs for storing and compressing gases compared to CSP-TCES, it requires less Mn₂O₃/Mn₃O₄, resulting in lower material and storage tank costs.

References

[1] Bajaj et al. (2024). RSC Sustainability, 2(4), 943-960.

Membrane processes have the potential to dramatically reduce energy consumption and footprint of carbon capture. Such potential depends on the selected material. Material properties determine the membrane area and the energy required for a given separation, which in turn define the economic and environmental impact of the process.

Therefore, we need to optimize process configuration while taking into account the economic and environmental implications of the materials selected.

We propose a novel design strategy that allows to identify the optimal operating conditions in the presence of a wide range of materials, and to assess seamlessly the economic and environmental impact of the proposed combinations of material and process. This method allows for a fast screening of multiple materials and can drive material selection depending on the application.

To this end, we developed a highly-efficient surrogate model for the technical design of membrane processes. The proposed model takes inputs relevant to the case study, material properties and operating conditions, and return representative outputs which are the basis for economic and environmental impact calculations. By integrating the model into an optimization routine based on evolutionary genetic algorithm, we are able to build Pareto fronts for the key technical outputs, i.e., specific energy consumption and specific membrane area, and for given targets of CO₂ recovery and purity.

This work focuses on the development of the surrogate model for membrane process starting from the detailed first-principle model presented in previous works.^1,2

We followed a surrogate-based optimization approach that has been proposed so far only for adsorption process modelling.³ Such approach consists in performing a design of experiment where the decision variables are sampled via Latin Hypercube Sampling (LHS) in order to cover the entire design space and in building a dataset by running the detailed model for all sets of decision variables. Such dataset is used to train a feedforward multilayer perceptrons neural network, which is then able to predict the outputs in the whole design space. This approach is particularly suitable to membrane process modelling, because the short time required by the detailed model for each evaluation allows to build comprehensive datasets, not biased towards a specific operating region.

The surrogate model is able to produce Pareto fronts for a given material and case study in very short timeframes, thus is particularly suitable to perform highly efficient optimization of membrane process design and fast material screening.

1. Micari, M. & Agrawal, K. V. Optimization of High-Performance Membrane Processes for Post-Combustion Carbon Capture. Comput. Aided Chem. Eng. 53, 997–1002 (2024).

2. Micari, M., Dakhchoune, M. & Agrawal, K. V. Techno-economic assessment of postcombustion carbon capture using high-performance nanoporous single-layer graphene membranes. J. Memb. Sci. 624, 119103 (2021).

3. Yan, Y. et al. Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS)-a state-of-the-art review. Energy Environ. Sci. 14, 6122–6157 (2021).

As 2025 approaches, substantial global transformations are essential to align with the climate objectives set for 2030 and 2050 under the Paris Agreement. Several solutions exist to reduce CO₂ emissions, even when emissions are unavoidable due to the chemical reactions intrinsic to certain industrial processes. For example, in sectors such as glass, lime, and steel production, the raw materials inherently produce CO₂ as part of their decomposition or transformation, regardless of whether fossil or renewable energy sources are used. In these cases, emissions are a direct consequence of the material processing, not solely energy consumption. From this perspective, CO₂ capture technologies offer a crucial solution for these sectors, enabling them to contribute meaningfully to global carbon reduction while maintaining long-term competitiveness in a Net Zero Emissions future.

Among the various technologies for CO₂ mitigation, the absorption-regeneration process using amine solvents, particularly MEA (Monoethanolamine), remains the benchmark. Despite its widespread use, challenges persist in accurately predicting and managing key factors such as MEA degradation and the formation of degradation by-products during the absorption-regeneration cycle. These degradation issues present significant hurdles to effective solvent management, process efficiency, and reclamation.

This study presents a detailed analysis of CO₂ capture processes modelled in Aspen Plus, focusing on the absorption-regeneration process with MEA while accounting for both thermal and oxidative degradations. The analysis covers five industrial cases, representing the glass, lime, phosphorous, and steel sectors, with inlet CO₂ concentrations ranging from 7 to 25 vol-%, and capture capacities varying between 25 and 200 kt/year. The thermal degradation model is based on the work of Lucas Braakhuis [1], while oxidative degradation is modelled using data from Grégoire Léonard [2].

By integrating these degradation kinetics into the CO₂ absorption-regeneration process, this study provides a comprehensive assessment of the energy requirements for CO₂ capture, the emissions of degradation products, and the loss of MEA's reactivity in forming carbamates. The study specifically focuses on the 30%-wt. aqueous MEA solvent and ensures the captured CO₂ is purified to 99.8%-wt, and compressed to 35 bar, aligning with Fluxys' guidelines for future CO₂ transport in Belgium.

The processes are compared to simplified models to evaluate the impact of solvent degradation on key parameters such as energy consumption (GJ/t of captured CO₂), emissions of MEA and NH₃, and the need for fresh solvent and water supplies. Preliminary results indicate a loss of MEA between 0.159 and 0.540 kg/ton of CO₂ captured at a 90% capture rate, which aligns with the range of 0.1 to 0.8 kg/ton reported by Neerup in a recent study [3].

[1] L. Braakhuis, “Development of Solvent Degradation Models for Amine-Based CO2 Capture,” Norwegian University of Science and Technology, Trondheim, 2024.

[2] G. Léonard, “Optimal design of a CO2 capture unit with assessment of solvent degradation," Université de Liège, Liège, 2013.

[3] R. Neerup et al., “Solvent degradation and emissions from a CO2 capture pilot at a waste-to-energy plant,” J. Environ. Chem. Eng., vol. 11, no. 6, p. 111411, Dec. 2023, doi: 10.1016/j.jece.2023.111411.

Direct Air Capture (DAC) technology has gained significant attention as a promising solution for mitigating CO₂ emissions and meeting climate goals. However, the current challenges of high energy demand, capital costs, and scalability present critical challenges to the widespread deployment of DAC systems. One potential solution to these challenges is the integration of DAC with Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings. Such an integration presents an opportunity to enhance indoor air quality while simultaneously capturing CO₂, potentially lowering the energy consumption and capital investment associated with standalone DAC systems. This study investigates the techno-economic performance of a DAC-HVAC integrated system compared to a standalone DAC system. An important focus in this study is scaling up lab-scale adsorbent filters and using experimental data on sorbent efficiency and stability to model the techno-economic feasibility of a full-scale system within an Air Handling Unit (AHU) of buildings. The adsorbent filter used in this study is 3D-printed and consists of amine-functionalized SBA-15, a mesoporous silica material known for its high CO₂ adsorption capacity. Previous studies by the authors have demonstrated the stability and performance of amine-functionalized SBA-15, providing key data for modelling the system's energy requirements. The economic analysis covers capital expenditures, as well as variable and fixed operating expenditures for both the DAC-HVAC integrated system and the standalone DAC system. Various economic metrics, such as the levelized cost of CO₂ capture, internal rate of return, discounted payback period, benefit-cost ratio, and break-even point, are evaluated to provide a comprehensive comparison. Moreover, a detailed sensitivity analysis is conducted to explore the influence of key variables, including discount rates, electricity prices, and CO₂ selling prices, on the overall economic performance of the systems. An important consideration in the study is the trade-off between the thickness of the filter and its impact on both pressure drop and blower power requirements, as well as filter replacement costs. The pressure drop across the filter can vary between 1600 Pa/m and 2100 Pa/m, depending on airflow velocity, influenced by the configuration of the two parallel filters. Thicker filters may reduce the need for frequent replacements but increase blower energy consumption due to higher pressure drops. The optimization of filter thickness, therefore, plays a crucial role in minimizing operational costs. The results demonstrate economic advantages of integrating DAC with HVAC systems, including lower energy consumption and capital costs compared to standalone DAC systems, as well as improvements in indoor air quality. For a specific filter thickness, blower power ranges from 18 kW for DAC-HVAC to 71 kW for standalone DAC. The levelized cost of capture for the DAC-HVAC system is approximately 130 $/t CO₂, with an estimated payback period of 3 years. This study's detailed techno-economic comparison highlights the cost savings and enhanced system efficiency of DAC-HVAC integration, as well as the potential for scaling up DAC technologies and incorporating them into existing building infrastructure.