M. Ramdin
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39 records found
1
Large-Scale Hydrogen Liquefaction: Cryogenic Cooling and Boil-off Gas Recovery
Process Modeling and Techno-Economic Analysis of Catalytic Plate-Fin Heat Exchangers and Ejector-Driven Cycles
For the cryogenic cooling stage, the helium-neon refrigerant is modeled with an improved equation of state (SAFT-VRQ-Mie) and residual entropy scaling. This replaces the dilute-gas correlations used in earlier studies. The revised thermal conductivity diverges from those correlations by a factor of two at 30 K and underpredicts the measured mixture property by 20-22%. Because the cold-side heat transfer scales as the two-thirds power of conductivity, this increases the required heat exchanger length by about 30% to 7.8 m, and the updated ortho-para conversion kinetics push it to the 8.2 m single-unit manufacturing limit.
For the LH2 storage stage, validated two-phase models show that the loading process dominates the boil-off losses and vents about 2.3% of each delivered load. A one-dimensional ejector model then shows that this BOG, together with the separator flash vapor, can be entrained and returned to the cycle in a single pass. This raises the net liquid product from 86 to 104 tonnes per day. In the adapted cycle, the binding constraint is the downstream PFHX and not the ejector. At the original 75 bar feed pressure, the heat exchanger exceeds the 8.2 m single-unit limit. Only when lowering the feed pressure to 40 bar, which also removes one feed-compression stage, it becomes buildable as a single unit at 8.19 m.
A techno-economic analysis of the isolated cryogenic section quantifies the cost of this recovery. Capital cost rises by 24% and specific energy consumption by 56%. The specific liquefaction cost increases from 0.432 to 0.593 USD per kilogram, an increase of 37.4% that holds across all tested cost assumptions. Ejector-based BOG recovery is therefore technically feasible and increases liquid yield, but it is not economically justified within the cryogenic boundary on its own. ...
For the cryogenic cooling stage, the helium-neon refrigerant is modeled with an improved equation of state (SAFT-VRQ-Mie) and residual entropy scaling. This replaces the dilute-gas correlations used in earlier studies. The revised thermal conductivity diverges from those correlations by a factor of two at 30 K and underpredicts the measured mixture property by 20-22%. Because the cold-side heat transfer scales as the two-thirds power of conductivity, this increases the required heat exchanger length by about 30% to 7.8 m, and the updated ortho-para conversion kinetics push it to the 8.2 m single-unit manufacturing limit.
For the LH2 storage stage, validated two-phase models show that the loading process dominates the boil-off losses and vents about 2.3% of each delivered load. A one-dimensional ejector model then shows that this BOG, together with the separator flash vapor, can be entrained and returned to the cycle in a single pass. This raises the net liquid product from 86 to 104 tonnes per day. In the adapted cycle, the binding constraint is the downstream PFHX and not the ejector. At the original 75 bar feed pressure, the heat exchanger exceeds the 8.2 m single-unit limit. Only when lowering the feed pressure to 40 bar, which also removes one feed-compression stage, it becomes buildable as a single unit at 8.19 m.
A techno-economic analysis of the isolated cryogenic section quantifies the cost of this recovery. Capital cost rises by 24% and specific energy consumption by 56%. The specific liquefaction cost increases from 0.432 to 0.593 USD per kilogram, an increase of 37.4% that holds across all tested cost assumptions. Ejector-based BOG recovery is therefore technically feasible and increases liquid yield, but it is not economically justified within the cryogenic boundary on its own.
A simulation model was developed in Python, incorporating hourly wind and solar generation data, electrolyser operation with on/off stack control, battery charging and discharging, and system degradation over a 20-year lifetime. Multiple system scenarios were evaluated by varying installed capacities, battery sizes, and minimum stack operation rules. Economic performance was assessed using key indicators, including hydrogen sales price, levelised cost of hydrogen (LCOH), net present value (NPV), internal rate of return (IRR), and payback time. Additionally, stack and battery replacement costs were considered. Results show that the cost-optimal system for the chosen location, De Koog, is dominated by wind-only systems, with the electrolyser operating at a capacity factor of 0.659. Inclusion of a small battery provides
minor operational flexibility, increasing annual hydrogen production slightly from 22.98 to 22.99 million kg, but has a negligible effect on hydrogen sales price (7.442–7.444 €/kg), NPV, LCOH, IRR, or payback time. From year 8 onwards, stack replacement costs remain constant, as stacks are replaced annually and battery replacement is scheduled after 13.5 years, leading to only a limited and predictable increase in total system costs. Electrolyser stack granularity affects operational efficiency: smaller stacks reduce curtailment without storage but slightly limit battery utilisation when included.
The findings indicate that the economic performance of green hydrogen production is primarily driven by the balance between renewable generation and electrolyser operation. In particular, the renewable to-electrolyser capacity ratio plays a key role, while battery storage has only a minor influence in the cost-optimal configuration. For the analysed Dutch coastal site, the lowest hydrogen production costs are achieved with a moderately oversized wind capacity, an electrolyser operating at an intermediate capacity factor, and minimal battery integration. However, the optimal capacity ratio and the economic value of battery storage are strongly location-specific and depend on local resource conditions and system design assumptions. This study provides a comprehensive techno-economic assessment of hybrid renewable energy system design, offering practical guidelines for optimising component sizing to achieve cost-efficient green hydrogen production in the Netherlands and supporting the transition to a low-carbon energy system. ...
A simulation model was developed in Python, incorporating hourly wind and solar generation data, electrolyser operation with on/off stack control, battery charging and discharging, and system degradation over a 20-year lifetime. Multiple system scenarios were evaluated by varying installed capacities, battery sizes, and minimum stack operation rules. Economic performance was assessed using key indicators, including hydrogen sales price, levelised cost of hydrogen (LCOH), net present value (NPV), internal rate of return (IRR), and payback time. Additionally, stack and battery replacement costs were considered. Results show that the cost-optimal system for the chosen location, De Koog, is dominated by wind-only systems, with the electrolyser operating at a capacity factor of 0.659. Inclusion of a small battery provides
minor operational flexibility, increasing annual hydrogen production slightly from 22.98 to 22.99 million kg, but has a negligible effect on hydrogen sales price (7.442–7.444 €/kg), NPV, LCOH, IRR, or payback time. From year 8 onwards, stack replacement costs remain constant, as stacks are replaced annually and battery replacement is scheduled after 13.5 years, leading to only a limited and predictable increase in total system costs. Electrolyser stack granularity affects operational efficiency: smaller stacks reduce curtailment without storage but slightly limit battery utilisation when included.
The findings indicate that the economic performance of green hydrogen production is primarily driven by the balance between renewable generation and electrolyser operation. In particular, the renewable to-electrolyser capacity ratio plays a key role, while battery storage has only a minor influence in the cost-optimal configuration. For the analysed Dutch coastal site, the lowest hydrogen production costs are achieved with a moderately oversized wind capacity, an electrolyser operating at an intermediate capacity factor, and minimal battery integration. However, the optimal capacity ratio and the economic value of battery storage are strongly location-specific and depend on local resource conditions and system design assumptions. This study provides a comprehensive techno-economic assessment of hybrid renewable energy system design, offering practical guidelines for optimising component sizing to achieve cost-efficient green hydrogen production in the Netherlands and supporting the transition to a low-carbon energy system.
Optimizing Electrolytic Hydrogen Production Costs
Building a Dynamic Levelized Cost of Hydrogen Model
This thesis develops a techno-economic LCOH framework that incorporates hourly electricity prices, renewable generation profiles, and operational constraints of an alkaline electrolyzer. A bottom-up modeling approach is applied, aggregating hourly operating decisions into discounted lifetime costs. A daily dispatch optimization algorithm is introduced to determine the operation of the electrolyzer based on electricity prices, expected hydrogen revenues, and solar availability, while accounting for start-up penalties, efficiency degradation, and stack replacement.
The framework is applied to a case study of a 1.2 MW alkaline electrolyzer coupled with a large solar field in the Netherlands using historical market data. The results indicate that price-responsive operation can reduce LCOH relative to continuous operation, primarily by avoiding periods of high electricity prices, although this leads to lower overall hydrogen production volumes. Compared with purely solar-following operation, cost reductions are achieved at the expense of higher carbon emissions as a result of increased reliance on grid electricity.
Overall, the study shows that incorporating electricity price dynamics and operational constraints can materially affect LCOH estimates and provides a more transparent basis for evaluating grid-connected electrolytic hydrogen production under volatile electricity markets. ...
This thesis develops a techno-economic LCOH framework that incorporates hourly electricity prices, renewable generation profiles, and operational constraints of an alkaline electrolyzer. A bottom-up modeling approach is applied, aggregating hourly operating decisions into discounted lifetime costs. A daily dispatch optimization algorithm is introduced to determine the operation of the electrolyzer based on electricity prices, expected hydrogen revenues, and solar availability, while accounting for start-up penalties, efficiency degradation, and stack replacement.
The framework is applied to a case study of a 1.2 MW alkaline electrolyzer coupled with a large solar field in the Netherlands using historical market data. The results indicate that price-responsive operation can reduce LCOH relative to continuous operation, primarily by avoiding periods of high electricity prices, although this leads to lower overall hydrogen production volumes. Compared with purely solar-following operation, cost reductions are achieved at the expense of higher carbon emissions as a result of increased reliance on grid electricity.
Overall, the study shows that incorporating electricity price dynamics and operational constraints can materially affect LCOH estimates and provides a more transparent basis for evaluating grid-connected electrolytic hydrogen production under volatile electricity markets.
Geothermal Energy for Heat and Power Production in South Holland
A Techno-Economic Assessment
This thesis provides a techno-economic assessment of medium-depth geothermal energy systems in South Holland, the Netherlands, evaluating their potential to meet local heat and electricity demands sustainably and with a profit. Two case studies were analyzed in this thesis. The first investigated a geothermal district heating system for the TU Delft campus, incorporating a large-scale heat pump to increase heat extraction from the reservoir. The second examined a combined heat and power (CHP) system for the Royal IHC facilities in Kinderdijk, based on an Organic Rankine Cycle (ORC). The work relied on thermodynamic modeling together with subsurface and economic simulations to select working fluids, size the main components, and assess economic indicators such as Levelized Costs of Heat/Electricity (LCOH/LCOE), Net Present Value (NPV), payback times, and internal rate of return (IRR).
The findings reveal a sharp difference in feasibility between the two cases. The geothermal heat pump project in Delft proved to be promising for district heating applications, whereas the ORC-based power generation system proved to be both technically and economically unviable under the assessed conditions, mainly due to the low temperature of the geothermal brine and the small scale of the project. A subsequent evaluation of a heat pump alternative for the Kinderdijk site indicated limited economic competitiveness under the current market price assumptions for heating.
Overall, the work suggests that the viability of geothermal projects is highly dependent on the quality of the geothermal resource, the scale of implementation, and the end-use requirements. Integrating heat pumps with medium-depth hydrothermal resources appears as a technically promising and financially attractive strategy for decarbonizing district heating networks, whereas low-temperature ORC systems for power generation remain unsuitable in regions with insufficient subsurface temperatures. The study shows the importance of site-specific assessments in ensuring the successful deployment of geothermal energy systems. ...
This thesis provides a techno-economic assessment of medium-depth geothermal energy systems in South Holland, the Netherlands, evaluating their potential to meet local heat and electricity demands sustainably and with a profit. Two case studies were analyzed in this thesis. The first investigated a geothermal district heating system for the TU Delft campus, incorporating a large-scale heat pump to increase heat extraction from the reservoir. The second examined a combined heat and power (CHP) system for the Royal IHC facilities in Kinderdijk, based on an Organic Rankine Cycle (ORC). The work relied on thermodynamic modeling together with subsurface and economic simulations to select working fluids, size the main components, and assess economic indicators such as Levelized Costs of Heat/Electricity (LCOH/LCOE), Net Present Value (NPV), payback times, and internal rate of return (IRR).
The findings reveal a sharp difference in feasibility between the two cases. The geothermal heat pump project in Delft proved to be promising for district heating applications, whereas the ORC-based power generation system proved to be both technically and economically unviable under the assessed conditions, mainly due to the low temperature of the geothermal brine and the small scale of the project. A subsequent evaluation of a heat pump alternative for the Kinderdijk site indicated limited economic competitiveness under the current market price assumptions for heating.
Overall, the work suggests that the viability of geothermal projects is highly dependent on the quality of the geothermal resource, the scale of implementation, and the end-use requirements. Integrating heat pumps with medium-depth hydrothermal resources appears as a technically promising and financially attractive strategy for decarbonizing district heating networks, whereas low-temperature ORC systems for power generation remain unsuitable in regions with insufficient subsurface temperatures. The study shows the importance of site-specific assessments in ensuring the successful deployment of geothermal energy systems.
Large-Scale H2 Liquefaction: Ortho-Para Conversion in a Conceptual Brayton Cycle
Process Modeling, Viability, and Techno-Economic Analysis
While conceptual models offer pathways to higher efficiency, they often lack the detailed technical and economic analysis needed to validate their feasibility, particularly for systems based on the Brayton cycle.
This thesis presents a comprehensive framework for the process modeling, viability assessment, and techno-economic analysis of a large-scale hydrogen liquefaction plant based on a conceptual Brayton cycle. A central contribution is the detailed modeling of the critical ortho-para hydrogen conversion, which was simulated within a catalytic Plate-Fin Heat Exchanger (PFHX) using a specialized Python-based model integrated with a full-plant Aspen HYSYS simulation. The study also addresses the effective management of excess cold hydrogen gas; an initial investigation into using an ejector for recirculation was conducted, but this approach was ultimately discarded as it did not yield economic improvements. A final, optimized hybrid Brayton-Claude cycle featuring an efficient cold gas recirculation loop was developed, enabling a plant capacity of 86 tonnes per day (TPD).
The techno-economic analysis of the final design was performed using the Aspen Process Economic Analyzer (APEA). In the baseline scenario, assuming an electricity price of 0.1 €/kW h, the plant achieved a Specific Liquefaction Cost (SLC) of 1.51 €/kgLH2 and a Specific Energy Consumption (SEC) of 6.983 kWh/kgLH2 in the baseline scenario.
Moreover, sensitivity analyses show a further reduction in SLC and SEC in the scenario using power recovery from the turbines: 1.49 €/kgLH2 and 6.723 kWh/kgLH2 respectively. Additionally, electricity price is the dominant factor influencing plant economics, with the long-term cost target of below 1.00 €/kgLH2 being achievable at an electricity price of 0.035 €/kW h. Future projections, which account for reduced design allowances as the technology matures to a ”Proven Process,” suggest a potential SLC reduction of 4.64%.
In summary, this thesis establishes a robust techno-economic framework for Brayton-cycle based liquefaction, demonstrating its viability while highlighting the critical interplay between advanced process modeling, component efficiency, and energy costs in achieving a competitive large-scale liquid hydrogen supply chain. ...
While conceptual models offer pathways to higher efficiency, they often lack the detailed technical and economic analysis needed to validate their feasibility, particularly for systems based on the Brayton cycle.
This thesis presents a comprehensive framework for the process modeling, viability assessment, and techno-economic analysis of a large-scale hydrogen liquefaction plant based on a conceptual Brayton cycle. A central contribution is the detailed modeling of the critical ortho-para hydrogen conversion, which was simulated within a catalytic Plate-Fin Heat Exchanger (PFHX) using a specialized Python-based model integrated with a full-plant Aspen HYSYS simulation. The study also addresses the effective management of excess cold hydrogen gas; an initial investigation into using an ejector for recirculation was conducted, but this approach was ultimately discarded as it did not yield economic improvements. A final, optimized hybrid Brayton-Claude cycle featuring an efficient cold gas recirculation loop was developed, enabling a plant capacity of 86 tonnes per day (TPD).
The techno-economic analysis of the final design was performed using the Aspen Process Economic Analyzer (APEA). In the baseline scenario, assuming an electricity price of 0.1 €/kW h, the plant achieved a Specific Liquefaction Cost (SLC) of 1.51 €/kgLH2 and a Specific Energy Consumption (SEC) of 6.983 kWh/kgLH2 in the baseline scenario.
Moreover, sensitivity analyses show a further reduction in SLC and SEC in the scenario using power recovery from the turbines: 1.49 €/kgLH2 and 6.723 kWh/kgLH2 respectively. Additionally, electricity price is the dominant factor influencing plant economics, with the long-term cost target of below 1.00 €/kgLH2 being achievable at an electricity price of 0.035 €/kW h. Future projections, which account for reduced design allowances as the technology matures to a ”Proven Process,” suggest a potential SLC reduction of 4.64%.
In summary, this thesis establishes a robust techno-economic framework for Brayton-cycle based liquefaction, demonstrating its viability while highlighting the critical interplay between advanced process modeling, component efficiency, and energy costs in achieving a competitive large-scale liquid hydrogen supply chain.
Multi-Objective Optimization of Precooling Stage in Hydrogen Liquefaction
A Process Modelling Approach to Harmonize Technical and Economic Trade-Offs
However, most of the study of the hydrogen precooling omits economic analysis, refrigerant freeze-out discussion, and employs a portion of a non-environmentally sustainable substance as the refrigerant. This study focused on addressing the gap by conducting multi-objective optimization (MOO) on specific energy consumption (SEC) and levelized precooling cost (LPC) to find out the optimal trade-off between the technical and economic competitiveness of the precooling stage, while ensuring the freeze-out risk in the streams was avoided and using environmentally friendly mixed refrigerant (MR) mixtures.
Two cycles, namely single mixed refrigerant (SMR) and dual mixed refrigerant (DMR), are modeled in Aspen HYSYS V12, where the configurations are defined based on freeze-out consideration. Nine MR mixtures for SMR and DMR are defined based on their thermophysical properties. A Non-dominated Sorting Genetic Algorithm-II (NSGA-II) algorithm was used for MOO through the pymoo library package in Python, which was then coupled with Aspen HYSYS. The decision variables to be optimized include MR composition, MR flow rate, compressor discharge pressure, and JT valve outlet pressure. Several constraints are also introduced, such as vapor fraction at the inlet compressor, minimum internal temperature difference (MITD) of heat exchangers, JT valve temperature difference, and several temperature constraints to ensure thermodynamic behavior is not violated.
In this study, Mixture 8 (for SMR) and Mixture 6 (for DMR) appear to be the top-performing mixtures, achieving specific energy consumptions (SEC) of 1.25 kWh/kgH2 and 1.13 kWh/kgH2, respectively, with levelized precooling costs (LPC) of €0.47/kgH2 and €0.60/kgH2. The study indicates that aligning the boiling points of mixed refrigerant components to enhance temperature glide, combined with tuning of operating conditions, is the key to achieving both energy efficiency and cost competitiveness. Furthermore, the optimized results in DMR also suggest that the intermediate-compression stage in the MR2 cycle could be removed.
From the sensitivity analysis, it was observed that as the precooling temperature target increased, the gap in SEC between the SMR and DMR configurations narrowed. Starting from 95 K, both systems reached similar SEC values, highlighting equal technical performance. However, the LPC further SMR dominant over the DMR. This indicates that beyond this temperature target, DMR was no longer economically competitive. Additionally, variations in pressure drop across heat exchangers and coolers had a stronger impact on the SMR configuration. The percentage increase in SEC and LPC was more severe due to the accumulation of pressure losses within a single-loop cycle. In contrast, the DMR system distributes losses across two separate loops, making it less sensitive to pressure drop effects. ...
However, most of the study of the hydrogen precooling omits economic analysis, refrigerant freeze-out discussion, and employs a portion of a non-environmentally sustainable substance as the refrigerant. This study focused on addressing the gap by conducting multi-objective optimization (MOO) on specific energy consumption (SEC) and levelized precooling cost (LPC) to find out the optimal trade-off between the technical and economic competitiveness of the precooling stage, while ensuring the freeze-out risk in the streams was avoided and using environmentally friendly mixed refrigerant (MR) mixtures.
Two cycles, namely single mixed refrigerant (SMR) and dual mixed refrigerant (DMR), are modeled in Aspen HYSYS V12, where the configurations are defined based on freeze-out consideration. Nine MR mixtures for SMR and DMR are defined based on their thermophysical properties. A Non-dominated Sorting Genetic Algorithm-II (NSGA-II) algorithm was used for MOO through the pymoo library package in Python, which was then coupled with Aspen HYSYS. The decision variables to be optimized include MR composition, MR flow rate, compressor discharge pressure, and JT valve outlet pressure. Several constraints are also introduced, such as vapor fraction at the inlet compressor, minimum internal temperature difference (MITD) of heat exchangers, JT valve temperature difference, and several temperature constraints to ensure thermodynamic behavior is not violated.
In this study, Mixture 8 (for SMR) and Mixture 6 (for DMR) appear to be the top-performing mixtures, achieving specific energy consumptions (SEC) of 1.25 kWh/kgH2 and 1.13 kWh/kgH2, respectively, with levelized precooling costs (LPC) of €0.47/kgH2 and €0.60/kgH2. The study indicates that aligning the boiling points of mixed refrigerant components to enhance temperature glide, combined with tuning of operating conditions, is the key to achieving both energy efficiency and cost competitiveness. Furthermore, the optimized results in DMR also suggest that the intermediate-compression stage in the MR2 cycle could be removed.
From the sensitivity analysis, it was observed that as the precooling temperature target increased, the gap in SEC between the SMR and DMR configurations narrowed. Starting from 95 K, both systems reached similar SEC values, highlighting equal technical performance. However, the LPC further SMR dominant over the DMR. This indicates that beyond this temperature target, DMR was no longer economically competitive. Additionally, variations in pressure drop across heat exchangers and coolers had a stronger impact on the SMR configuration. The percentage increase in SEC and LPC was more severe due to the accumulation of pressure losses within a single-loop cycle. In contrast, the DMR system distributes losses across two separate loops, making it less sensitive to pressure drop effects.
Electrochemical conversion of CO2 to methane: Process modeling and economics
Electrochemical conversion of CO2 to methane: Process modeling and economics
This thesis investigates the dynamic behaviour and optimal sizing of a directly coupled wind-powered alkaline electrolyser system, with the aim of minimising the Levelized Cost of Hydrogen (LCOH). Although static operating conditions are often assumed in existing models, this work addresses gaps in the literature by developing a time-resolved simulation model that includes wind variability, dynamic efficiency, degradation effects, realistic operational limits of the electrolyser, and time-dependent efficiency of power electronics.
An electrolyser model was developed and implemented in Python using an Electrical Equivalent Circuit (EEC) approach. An initial analysis compared intra-hour wind power fluctuations with hourly averages, revealing that the impact on hydrogen conversion efficiency was negligible (<0.06% over three 3-hour periods). Given this minimal difference and the widespread availability of hourly wind data across numerous locations, hourly wind data was deemed sufficiently accurate for system-level analysis.
The model was subsequently applied to evaluate system performance across 38 onshore European locations using 2015 wind data, assuming a constant configuration of a 2MW wind turbine coupled to a 1380kW electrolyser (69% ratio). For each location, the wind turbine and electrolyser capacity factors were calculated to assess the geographical variability in system utilisation. In addition, two Dutch sites, one coastal and one inland, were studied in greater detail to analyse annual operational behaviour, power electronics impact, conversion efficiency, hydrogen yield, and degradation patterns. Finally, lifetime simulations over 20 years were performed to evaluate system economics under varying electrolyser sizes, three cost scenarios, and two discount rates. Results showed that optimal electrolyser sizing is highly location-dependent and influenced by design objectives: the size yielding the highest hydrogen production is not necessarily the one that results in the lowest LCOH. In fact, the LCOH-optimal size was consistently smaller. Moreover, cost scenarios affected optimal sizing, with higher capital costs favouring slightly larger systems to offset investment through increased hydrogen output.
Time-resolved modelling further revealed the importance of minimum load constraints (to avoid gas crossover) and degradation effects, which influence system utilisation and stack replacement timing. While lifetime hydrogen production estimates from the dynamic model did not deviate significantly from those based on static assumptions, the dynamic approach enabled more accurate performance forecasting and degradation tracking. This research highlights the necessity of time-resolved modelling for techno-economic assessment of wind-powered hydrogen systems. The developed framework provides a comprehensive foundation for future optimisation studies and supports more accurate design and investment decisions for renewable hydrogen deployment. ...
This thesis investigates the dynamic behaviour and optimal sizing of a directly coupled wind-powered alkaline electrolyser system, with the aim of minimising the Levelized Cost of Hydrogen (LCOH). Although static operating conditions are often assumed in existing models, this work addresses gaps in the literature by developing a time-resolved simulation model that includes wind variability, dynamic efficiency, degradation effects, realistic operational limits of the electrolyser, and time-dependent efficiency of power electronics.
An electrolyser model was developed and implemented in Python using an Electrical Equivalent Circuit (EEC) approach. An initial analysis compared intra-hour wind power fluctuations with hourly averages, revealing that the impact on hydrogen conversion efficiency was negligible (<0.06% over three 3-hour periods). Given this minimal difference and the widespread availability of hourly wind data across numerous locations, hourly wind data was deemed sufficiently accurate for system-level analysis.
The model was subsequently applied to evaluate system performance across 38 onshore European locations using 2015 wind data, assuming a constant configuration of a 2MW wind turbine coupled to a 1380kW electrolyser (69% ratio). For each location, the wind turbine and electrolyser capacity factors were calculated to assess the geographical variability in system utilisation. In addition, two Dutch sites, one coastal and one inland, were studied in greater detail to analyse annual operational behaviour, power electronics impact, conversion efficiency, hydrogen yield, and degradation patterns. Finally, lifetime simulations over 20 years were performed to evaluate system economics under varying electrolyser sizes, three cost scenarios, and two discount rates. Results showed that optimal electrolyser sizing is highly location-dependent and influenced by design objectives: the size yielding the highest hydrogen production is not necessarily the one that results in the lowest LCOH. In fact, the LCOH-optimal size was consistently smaller. Moreover, cost scenarios affected optimal sizing, with higher capital costs favouring slightly larger systems to offset investment through increased hydrogen output.
Time-resolved modelling further revealed the importance of minimum load constraints (to avoid gas crossover) and degradation effects, which influence system utilisation and stack replacement timing. While lifetime hydrogen production estimates from the dynamic model did not deviate significantly from those based on static assumptions, the dynamic approach enabled more accurate performance forecasting and degradation tracking. This research highlights the necessity of time-resolved modelling for techno-economic assessment of wind-powered hydrogen systems. The developed framework provides a comprehensive foundation for future optimisation studies and supports more accurate design and investment decisions for renewable hydrogen deployment.
Carbon Nanofibre Purification
Process design, modelling and analysis of carbon nanofibre purification with acid leaching
CNF produced by CMP with a Ni-SiO2 catalyst was used for this study and initially contains 4700 ppm of nickel. The baseline scenario of the designed process has a production capacity of 20,000 tonnes per year and includes acid leaching with HCl, liquid removal and post-treatment steps. The techno-economic analysis showed a Levelized Cost of Purification (LCOP) of 10.09 $/kg and a Net Present Value (NPV) of 1.48 billion $ for the baseline scenario. The process is very profitable due to the assumed high selling price of 25 $/kg. However, the conversion of nickel is only equal to 5.15 %, leaving 4460 ppm of nickel in the CNF product while the desired nickel content is below 300 ppm. The low conversion indicates that the quality of the CNF product is barely improved and that the assumed selling price is probably too high. The acid leaching kinetics are modelled using literature on acid leaching with HCl of nickel from a Ni-Al2O3 spent catalyst. Acid leaching experiments of nickel from CNF with H2SO4 showed a more positive average nickel conversion of 70.9 % so far. The leaching kinetics still have to be determined for a variety of acids and will be necessary to model the leaching more accurately.
Sensitivity analyses showed that the impact of the acid waste price on the LCOP was the largest of the economic parameters with ±2.5 $/kg variation, followed by the electricity price. The acid feed price also had a significant impact on the LCOP. The high impact of the acid waste and feed price showed a need for the implementation of an acid recycle. A Monte Carlo analysis indicated a robust process design under economic uncertainties. The mean of the LCOP was equal to 10.12 $/kg and the standard deviation was equal to 0.90 $/kg.
Two improved design cases of the baseline scenario are presented. The first includes changes to the reactor temperature, residence time, acid molarity, ratio of CNF feed to acid feed and the inclusion of an acid recycle. The conversion is improved to 61.04 % with an LCOP of 24.68 $/kg. The second design case builds upon the first and includes further changes to the residence time and ratio of CNF feed to acid feed. Furthermore, the reactor setup is changed to three reactors placed in series for the second design case. The conversion is increased to 93.95 %, leaving only 285.66 ppm of nickel in the CNF product. The LCOP is equal to 21.84 $/kg, but a total of 90 reactors are required. While the process is profitable and the nickel content in the product is below 300 ppm, questions arise whether the second improved design is practical. ...
CNF produced by CMP with a Ni-SiO2 catalyst was used for this study and initially contains 4700 ppm of nickel. The baseline scenario of the designed process has a production capacity of 20,000 tonnes per year and includes acid leaching with HCl, liquid removal and post-treatment steps. The techno-economic analysis showed a Levelized Cost of Purification (LCOP) of 10.09 $/kg and a Net Present Value (NPV) of 1.48 billion $ for the baseline scenario. The process is very profitable due to the assumed high selling price of 25 $/kg. However, the conversion of nickel is only equal to 5.15 %, leaving 4460 ppm of nickel in the CNF product while the desired nickel content is below 300 ppm. The low conversion indicates that the quality of the CNF product is barely improved and that the assumed selling price is probably too high. The acid leaching kinetics are modelled using literature on acid leaching with HCl of nickel from a Ni-Al2O3 spent catalyst. Acid leaching experiments of nickel from CNF with H2SO4 showed a more positive average nickel conversion of 70.9 % so far. The leaching kinetics still have to be determined for a variety of acids and will be necessary to model the leaching more accurately.
Sensitivity analyses showed that the impact of the acid waste price on the LCOP was the largest of the economic parameters with ±2.5 $/kg variation, followed by the electricity price. The acid feed price also had a significant impact on the LCOP. The high impact of the acid waste and feed price showed a need for the implementation of an acid recycle. A Monte Carlo analysis indicated a robust process design under economic uncertainties. The mean of the LCOP was equal to 10.12 $/kg and the standard deviation was equal to 0.90 $/kg.
Two improved design cases of the baseline scenario are presented. The first includes changes to the reactor temperature, residence time, acid molarity, ratio of CNF feed to acid feed and the inclusion of an acid recycle. The conversion is improved to 61.04 % with an LCOP of 24.68 $/kg. The second design case builds upon the first and includes further changes to the residence time and ratio of CNF feed to acid feed. Furthermore, the reactor setup is changed to three reactors placed in series for the second design case. The conversion is increased to 93.95 %, leaving only 285.66 ppm of nickel in the CNF product. The LCOP is equal to 21.84 $/kg, but a total of 90 reactors are required. While the process is profitable and the nickel content in the product is below 300 ppm, questions arise whether the second improved design is practical.
Integration of CO2 Electrolysers into an Industrial-Scale Process System
Effects of Non-Aqueous Solvents and Gaseous Impurities
Large-Scale Hydrogen Liquefaction Based on Brayton Cycle Concept
Process Modelling, Viability and Techno-Economic Analysis
Large energy storage systems can address the issue of energy demand fluctuations in renewable energy grids by storing excess energy produced and compensating for any energy shortfalls. The development of hydrogen energy storage systems will thus support the advancement and increased utilization of renewable energy sources. The demand for liquid hydrogen is expected to rise in the near future, driven by environmentally friendly applications and use in mobility sector. As a result, large-scale hydrogen liquefaction (LHL) plants will become increasingly important in the clean energy efficient hydrogen supply chain.
This thesis aims to develop a Large-scale Hydrogen Liquefaction (LHL) plant based on the Brayton cycle concept of 86 TPD. The plant is modeled using Aspen HYSYS, with preliminary designs for key equipment—such as compressors, turbines, and plate-fin heat exchangers, ensuring compatibility with current technological constraints. State properties of the fluid used in the design of compressors and turbine equipment were obtained from REFPROP software, utilizing the Peng-Robinson Equation of State (EOS). For the design of plate-fin heat exchangers, Aspen Exchanger Design and Rating (EDR) was employed. Subsequently, a techno-economic analysis was conducted using the Aspen Process Economic Analyzer (APEA) to estimate both capital and operating expenditures, based on the process simulation model and preliminary equipment designs.
The specific energy consumption (SEC) of the plant, accounting for power recovery from turbine shafts, is determined to be 6.9025 kWh/kgLH2. The plant’s exergy efficiency is calculated at 43.665%, and the specific liquefaction power is found to be 3.014 kWh/kgLH2. Assuming an electricity price of 0.1 €/kWh, modelled 86 TPD Brayton-cycle concept yielded specific liquefaction cost (SLC) of 1.57 €/kgLH2.
A sensitivity analysis was conducted to identify the parameters that influence the specific liquefaction cost (SLC) of the plant. The analysis focused on two key parameters: 1) electricity price and 2) feed pressure. The results reveal that fluctuations in electricity prices have a substantial impact on the plant’s economic performance. Additionally, the analysis indicates that the plant’s efficiency and economic viability are significantly sensitive to decreases in feed hydrogen pressure. ...
Large energy storage systems can address the issue of energy demand fluctuations in renewable energy grids by storing excess energy produced and compensating for any energy shortfalls. The development of hydrogen energy storage systems will thus support the advancement and increased utilization of renewable energy sources. The demand for liquid hydrogen is expected to rise in the near future, driven by environmentally friendly applications and use in mobility sector. As a result, large-scale hydrogen liquefaction (LHL) plants will become increasingly important in the clean energy efficient hydrogen supply chain.
This thesis aims to develop a Large-scale Hydrogen Liquefaction (LHL) plant based on the Brayton cycle concept of 86 TPD. The plant is modeled using Aspen HYSYS, with preliminary designs for key equipment—such as compressors, turbines, and plate-fin heat exchangers, ensuring compatibility with current technological constraints. State properties of the fluid used in the design of compressors and turbine equipment were obtained from REFPROP software, utilizing the Peng-Robinson Equation of State (EOS). For the design of plate-fin heat exchangers, Aspen Exchanger Design and Rating (EDR) was employed. Subsequently, a techno-economic analysis was conducted using the Aspen Process Economic Analyzer (APEA) to estimate both capital and operating expenditures, based on the process simulation model and preliminary equipment designs.
The specific energy consumption (SEC) of the plant, accounting for power recovery from turbine shafts, is determined to be 6.9025 kWh/kgLH2. The plant’s exergy efficiency is calculated at 43.665%, and the specific liquefaction power is found to be 3.014 kWh/kgLH2. Assuming an electricity price of 0.1 €/kWh, modelled 86 TPD Brayton-cycle concept yielded specific liquefaction cost (SLC) of 1.57 €/kgLH2.
A sensitivity analysis was conducted to identify the parameters that influence the specific liquefaction cost (SLC) of the plant. The analysis focused on two key parameters: 1) electricity price and 2) feed pressure. The results reveal that fluctuations in electricity prices have a substantial impact on the plant’s economic performance. Additionally, the analysis indicates that the plant’s efficiency and economic viability are significantly sensitive to decreases in feed hydrogen pressure.
Dual Fuel combustion of Methanol and PODE in a marine ICE and on-board production of PODE
Modelling of a process plant design and engine system
Closed-loop recycling of Li-ion batteries
An integration between hydrometallurgy and bipolar membrane electrodialysis
Up until now, numerous companies have attempted to resolve these issues through the use of pyro- and hydrometallurgical recycling methods. However, they are yet to meet the mandated recycling goals put in place by the European Commission. This enhances the urgency for the development of a novel, efficient and scalable technology for the recovery of valuable material from spent lithium-ion batteries.
In order to achieve such a development, this study proposes to incorporate Bipolar Membrane Electrodialysis into the standard hydrometallurgical recycling approach. During the course of this research, a prototype of this technology was realized and used to investigate its effectiveness. For practical reasons, the research focused exclusively on the metal and acid recovery from leached LCO cathode material.
Within the subsequent experimental phase of this research a critical issue was identified. Namely, the tendency of divalent cobalt ions to precipitate in non-acidic media. The resolution to this issue required the incorporation of Donnan dialysis into the built BPMED setup, which was used to adjust the acidity of the solutions within the different electrolytic compartments.
Ultimately, this approach led to the respectively recovery of 14 and 22 percent of the lithium and cobalt initially present in the feed solution. Simultaneously, the study recovered a significant amount of the starting leaching agent in the form of 0.6 M nitric acid. Whilst additional optimizations are required to improve the recovery efficiencies, the study successfully demonstrates a proof of concept of the proposed solution.
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Up until now, numerous companies have attempted to resolve these issues through the use of pyro- and hydrometallurgical recycling methods. However, they are yet to meet the mandated recycling goals put in place by the European Commission. This enhances the urgency for the development of a novel, efficient and scalable technology for the recovery of valuable material from spent lithium-ion batteries.
In order to achieve such a development, this study proposes to incorporate Bipolar Membrane Electrodialysis into the standard hydrometallurgical recycling approach. During the course of this research, a prototype of this technology was realized and used to investigate its effectiveness. For practical reasons, the research focused exclusively on the metal and acid recovery from leached LCO cathode material.
Within the subsequent experimental phase of this research a critical issue was identified. Namely, the tendency of divalent cobalt ions to precipitate in non-acidic media. The resolution to this issue required the incorporation of Donnan dialysis into the built BPMED setup, which was used to adjust the acidity of the solutions within the different electrolytic compartments.
Ultimately, this approach led to the respectively recovery of 14 and 22 percent of the lithium and cobalt initially present in the feed solution. Simultaneously, the study recovered a significant amount of the starting leaching agent in the form of 0.6 M nitric acid. Whilst additional optimizations are required to improve the recovery efficiencies, the study successfully demonstrates a proof of concept of the proposed solution.
Integrated Process Design and Modeling for LNG Evaporation and CO2 Liquefaction Systems
Heat and Power Systems That Can Liquefy CO2 Utilizing the Cold Exergy of LNG
Towards Sustainable Ammonia Production: Harnessing Lithium Chemistry for Ammonia Synthesis Under Moderate Conditions
Proof of Concept delivery for the first steps towards a sustainable NH3 synthesismethod
Techno-Economics of Green Hydrogen
Production, Compression, Transportation and Storage
The aim of this thesis was to evaluate the levelized costs of hydrogen at various phases of supply chain, from hydrogen production to utilization. In order to accomplish this task, a literature review was conducted to identify the most promising methods in hydrogen production, compression, storage and transport followed by developing mathematical models of various technologies. According to the literature review, water electrolysis using electrolyzers such as alkaline, polymer electrolyte membrane (PEM), and solid oxide was shown to be techno-economically feasible. The literature review also revealed that centrifugal and diaphragm compression, pipeline transmission, and salt cavern storage were all techno-economically feasible technologies. These technologies’ steady-state mathematical models were built for scaling and techno-economic analysis. In the end, learning curves were applied for electrolyzers to predict the cost reductions in future.
According to the results of mathematical modeling, hydrogen production contributes the most to total levelized costs of supply chain followed by overall compression costs. Moreover, capital costs of electrolyzer stack and electricity costs significantly influence the levelized costs of hydrogen production. For 1 MW electrolyzer capacity and average capital and operating costs of electrolyzer stack, alkaline electrolysis is currently the most cost-effective technique of producing hydrogen with levelized cost of hydrogen (LCOH) calculated to be 3.69 €/ kg, followed by solid oxide electrolysis (4.55 €/kg).However, the use of learning curves indicates that by 2050, solid oxide electrolysis may be the most cost-effective technique of producing hydrogen with projected levelized cost of 1.72 €/kg. The pipeline compression costs were found to be around 0.065 €/ kg whereas diaphragm compression costs were found to be in the range of 0.55 to 1.2 €/ kg depending on the outlet pressure. While hydrogen storage and transportation require substantial capital investment, their overall impact on levelized costs was found to be minimal compared to production and compression expenses, with storage costs averaging around 0.8 €/kg and transportation costs at approximately 0.0007 €/kg per kilometer. The same mathematical model was used to analyze two hydrogen utilization scenarios: fuel for fuel cell vehicles and feed for industry. Both pessimistic and optimistic cases were examined by varying cost-influencing parameters to predict the possible range of total levelized costs for the supply chain. The results showed that hydrogen as a fuel for fuel cell vehicles will stay more expensive than hydrogen as a feed for industry. ...
The aim of this thesis was to evaluate the levelized costs of hydrogen at various phases of supply chain, from hydrogen production to utilization. In order to accomplish this task, a literature review was conducted to identify the most promising methods in hydrogen production, compression, storage and transport followed by developing mathematical models of various technologies. According to the literature review, water electrolysis using electrolyzers such as alkaline, polymer electrolyte membrane (PEM), and solid oxide was shown to be techno-economically feasible. The literature review also revealed that centrifugal and diaphragm compression, pipeline transmission, and salt cavern storage were all techno-economically feasible technologies. These technologies’ steady-state mathematical models were built for scaling and techno-economic analysis. In the end, learning curves were applied for electrolyzers to predict the cost reductions in future.
According to the results of mathematical modeling, hydrogen production contributes the most to total levelized costs of supply chain followed by overall compression costs. Moreover, capital costs of electrolyzer stack and electricity costs significantly influence the levelized costs of hydrogen production. For 1 MW electrolyzer capacity and average capital and operating costs of electrolyzer stack, alkaline electrolysis is currently the most cost-effective technique of producing hydrogen with levelized cost of hydrogen (LCOH) calculated to be 3.69 €/ kg, followed by solid oxide electrolysis (4.55 €/kg).However, the use of learning curves indicates that by 2050, solid oxide electrolysis may be the most cost-effective technique of producing hydrogen with projected levelized cost of 1.72 €/kg. The pipeline compression costs were found to be around 0.065 €/ kg whereas diaphragm compression costs were found to be in the range of 0.55 to 1.2 €/ kg depending on the outlet pressure. While hydrogen storage and transportation require substantial capital investment, their overall impact on levelized costs was found to be minimal compared to production and compression expenses, with storage costs averaging around 0.8 €/kg and transportation costs at approximately 0.0007 €/kg per kilometer. The same mathematical model was used to analyze two hydrogen utilization scenarios: fuel for fuel cell vehicles and feed for industry. Both pessimistic and optimistic cases were examined by varying cost-influencing parameters to predict the possible range of total levelized costs for the supply chain. The results showed that hydrogen as a fuel for fuel cell vehicles will stay more expensive than hydrogen as a feed for industry.