Multi-stack proton exchange membrane (PEM) water electrolysis systems are increasingly deployed to improve the scalability and flexibility of green hydrogen production. However, sharing balance-of-plant equipment introduces coupling between stacks, and differences in stack performance increase the complexity of plantwide operation. In particular, non-identical efficiencies and safety constraints, such as hydrogen-to-oxygen (HTO) ratio limits, can render single-stack or equal-power-sharing control strategies suboptimal. In this work, the steady-state optimal operating regime of a two-stack PEM electrolysis system is characterized using a plantwide optimization approach and active constraint mapping over a range of system power loads. Performance differences between the stacks are represented through variations in Faraday efficiency to emulate simplified degradation. For identical stacks, the system behaves similarly to a single large electrolyzer, where equal power distribution is optim... [more]

A safety-intelligent framework is presented for developing a multiple-input multiple-output (MIMO) risk-based explicit model predictive control (R-eMPC) for metal hydride storage systems (MHSS). These systems are susceptible to thermal runaway during the charging process as a result of the exothermic adsorption reaction within the metal alloy. To address this issue, deterministic and stochastic safety-intelligent control algorithms are designed and implemented by explicitly embedding a dynamic risk index (RI) or risk tolerance (() into the control law and decision-making. In closed-loop analysis, the deterministic R-eMPC regulates both core temperature and hydrogen storage capacity by forecasting fault occurrence, triggering alarms, and reducing the risk index by adjusting the optimal control actions, supply pressure and water flowrate. Meanwhile, the stochastic R-eMPC accounts for uncertainties in core temperature variation by incorporating risk tolerance through chance-constraints. W... [more]

This study presents a techno-economic modeling framework integrating a modular blue H2N2 production unit with a hydrogen refueling station (HRS) across capacities ranging from 0.1 to 4.0 tpd. A model-based approach is used to size key process and refueling components and to estimate the resulting hydrogen retail cost. The analysis indicates that hydrogen retail costs range from 4.6 to 10.8 USD kgH2-1 over the considered capacity range. Relative to alternative on-site hydrogen production pathways, the proposed system demonstrates better cost-effectiveness while meeting clean hydrogen production standards. The approach is particularly suitable for regions with established natural gas infrastructure, as it leverages existing supply chains. Overall, the results provide actionable insights for policymakers and industry stakeholders in planning future hydrogen refueling infrastructure.

The electrification of regional aviation requires coordinated planning of airport energy systems that integrate renewable generation, energy storage, and hydrogen technologies in a cost-efficient and resilient manner. This paper presents a scalable techno-economic optimization framework that models multiple airports as collaborative energy hubs. An object-oriented mixed-integer linear programming (MILP) formulation is combined with a genetic algorithm (GA) to optimize infrastructure sizing and energy dispatch. The framework is applied to three Swedish regional airports-Västerås, Jönköping, and Visby. A set of scenarios, including parties operating under shared wind-energy contracts using power purchase agreements (PPAs) and dynamic pricing (DP), was studied. Detailed representations of battery energy storage, hydrogen production and storage, and market interactions are included. Results show that coordinated operation and airport collaboration under a smart energy management system can... [more]

Grid-connected electrolyzers with intermediate hydrogen storage offer significant potential for reducing electricity costs through flexible operation under dynamic pricing. A threshold-based scheduling optimization approach is developed that derives interpretable on/off production rules from electricity price signals. The method identifies local price thresholds separating high-price from low-price periods, yielding binary production schedules. Adaptive horizon partitioning-subdividing the scheduling horizon when constant thresholds become infeasible-is combined with a receding horizon strategy that implements only a portion of each optimized schedule before re-optimization. This procedure enables systematic investigation of how characteristics of Integrated Electrolyzer-Storage Systems (IESS) influence cost reduction potential while maintaining computational tractability for both offline analysis and online implementation. A case study applying the approach to historical German electr... [more]

To effectively distribute power to a system of multiple electrolyzer stack units, control strategies have been developed that now need to be applied to heterogeneous electrolysis systems. These are the 'segment principle', the 'slow start principle' and the 'start-stop principle'. As there are many possible combinations to the system composition of a modular heterogeneous electrolysis system together with the most suitable control strategy, a discrete multi-criteria optimisation problem can be formulated. To solve this discrete multi-criteria optimisation problem, two discrete decision variables are introduced. One is the electrolysis system composition, represented by the power ratio/configuration (C). A total of 17 different configurations were used for this, consisting of different proportions of alkaline electrolysis (AEL) and proton exchange membrane electrolysis (PEMEL). The other one are the control strategies (R). For the control strategies, the conventional strategies, mention... [more]

The use of green hydrogen to reduce iron ore is a promising approach to drastically decrease CO2 emissions in the steel industry. To enable the rapid adoption of this technology, it is essential to start from the fundamentals, namely understanding the intrinsic kinetics of iron oxide reduction. In this work, a kinetic investigation was conducted in a PBRlike system using both pure and commercial iron oxide powders under a wide range of operating conditions. The thermal conductivity of the outlet gas was measured and innovatively correlated with the extent of solid reduction through a rigorous mathematical procedure. To simulate the reduction process and determine the kinetic parameters, a deterministic axial dispersion model was developed in conjunction with a dynamic multistep shrinking core model. The model incorporates the particle size distribution of the solid into the mass balance and includes a reactionfront control mechanism to ensure physical consistency during kinetic param... [more]

Styrene is mainly produced by dehydrogenating ethylbenzene over an iron oxide-based catalyst. The reaction is endothermic and thermodynamically limited when operated in conventional catalytic fixed-bed reactors. This makes the styrene production process a conversion-selectivity trade-off, where different objectives must be compromised. In this work, a one-dimensional reactor model accounting for changes in molar flowrate, temperature, and pressure is used to predict the performance of a membrane reactor. Three main hydrogen flux profiles were assumed along the reactor axial direction: constant, linearly increasing, and linearly decreasing. It is found that the styrene yield and selectivity in a membrane reactor operated with a linearly decreasing hydrogen flux profile are higher than those with constant or linearly increasing hydrogen flux profiles in both isothermal and nonisothermal cases. It is also observed that the styrene yield and selectivity of the membrane reactor operated wit... [more]

The present work aims to demonstrate the synergy achieved through the integration of biomass gasification with a direct air capture (DAC) system to maximize overall CO2 removal capacity, while simultaneously converting waste into value-added products (hydrogen) and supplying the energy required for DAC operation (BG-H2P-DAC). The proposed configuration is modeled using Aspen Plus to investigate the synergistic interactions and key performance indicators of the BG-H2P-DAC system. Parametric analyses are conducted by varying gasification temperature, air inlet flow rate, and amine concentration and flow rate. The results indicate that increasing the monoethanolamine (MEA) concentration from 10% to 40% leads to a gradual decline in CO2 capture efficiency, accompanied by a reduction in CO2 slip. The system achieves a net specific electricity consumption of 0.0293 MWh/t CO2, confirming that the electricity generated from the integrated steam power cycle is sufficient to fully offset the ele... [more]

The conceptual design and performance of a novel Methylcyclohexane-Toluene-Hydrogen based chemical heat pump was studied using steady state simulations. The distillation operating parameters of the chemical heat pump were optimized to maximize the Coefficient of Performance based on heat quantity (COP) and its corresponding Coefficient of Performance based on electric work input (COPW) was calculated. The best operating temperature ranges of the endothermic and exothermic reactor are 200°C-225°C and 250°C-275°C respectively. An endothermic temperature of 200°C and an exothermic temperature of 250°C results in a COP of 0.1357 and a COPW of 13.3. By integrating this chemical heat pump with a vapor compression heat pump COP increased to 0.1445 while COPW reduced to 4.9.

Decarbonization of hydrogen-intensive industrial clusters is essential to meet the European Union's net-zero targets. Although hydrogen can replace fossil-based feedstocks and fuels in refineries and chemical industries, its production remains largely dependent on natural gas. Therefore, cost-effective and low-emission supply routes require a system-level approach that integrates regional resources, technologies, and industrial demand. This study applies a multi-objective optimization framework to design a low-carbon hydrogen supply system for Galicia (northwestern Spain), addressing two gaps in regional energy system modeling: model transferability across regions and integration of social criteria beyond techno-economic assessment. The model quantifies trade-offs between total system cost and greenhouse gas emissions, and an employment indicator is integrated via post-processing using TOPSIS. The results show that meeting 100% of the projected 2030 demand (105 kt H2/a) yields a single... [more]

Recent geopolitical disruptions and extreme weather events have underscored the importance of resilience in global energy supply chains, particularly for import-dependent economies pursuing ambitious energy transition targets. These events have exposed the limitations of supply chain designs focused solely on cost minimization that lack the flexibility and redundancy required for secure operation under stress. As energy systems evolve toward higher shares of variable renewable energy and increased demand uncertainty, episodic manual re-planning becomes inadequate, highlighting the need for modeling frameworks that integrate predictive modeling, optimization, and control to enable intelligent and adaptive supply-chain design and operations under uncertainty. This work presents a comprehensive data-driven modeling and optimization framework for adaptive energy supply-chain networks under evolving demand. The framework integrates three layers: (i) a machine-learning model for demand forec... [more]

"Green" hydrogen production via polymer electrolyte membrane (PEM) electrolyzers must overcome significant energy penalties and high costs to become competitive in renewables-based energy systems. Adaptive operating strategies for PEM electrolyzers-by dynamically adjusting current density, pressure, and temperature-have demonstrated efficiency improvements in simple energy systems. However, their effectiveness in the context of complex power-to-X energy systems featuring variable downstream synthesis processes remains unclear. This work shows that integrated optimization of PEM electrolyzer operating parameters in conjunction with downstream methanation processes (MP) delivers substantial system-wide efficiency and cost benefits under dynamic hydrogen demand and pressure conditions. To demonstrate this, an equation-oriented process model of a PEM electrolysis system is embedded within a higher-level energy system model to compare sequential optimization (where the electrolyzer adapts t... [more]

The transition toward low-carbon ammonia production increasingly relies on highly efficient routes for renewable hydrogen generation, with Solid Oxide Electrolysis (SOE) representing a particularly promising solution. SOEs, operating with steam at elevated temperatures, offer intrinsic thermodynamic advantages and are attractive when integrated with processes that can effectively utilize or supply high-grade heat. This context opens the possibility for advanced energy coupling between hydrogen production and the exothermic ammonia synthesis process. This work investigates such an energy integration strategy by simulating a small-scale ammonia plant where hydrogen is produced through an SOE system thermally coupled to the ammonia synthesis loop. Specifically, high-grade heat available in the Haber-Bosch (HB) reactor outlet is recovered via a "Heat Recovery Steam Generator" (HRSG) to provide a substantial fraction (55 wt%) of the steam required by the electrolyzer. The assessment demonst... [more]

Cryogenic fuel tanks used in ships are continuously subjected to heat ingress and motions which affect the thermal behavior of the fluid inside the tanks. In this study, the ullage space of a liquid hydrogen (LH2) tank subjected to heat ingress and periodic rolling motion is analyzed using Computational Fluid Dynamics (CFD). A two-dimensional transient model utilizing the dynamic mesh approach is created to represent the ullage space of a partially filled LH2 tank. Three cases are studied where the properties of the thermal insulation of the tank model are varied, resulting in a different heat ingress for each case. A low-frequency motion is applied to the model domain, which induces mixing of temperature layers and cooling due to vapor contact with wetted walls. After 60 s of tank motion, most mixing is observed in the case with the smallest heat ingress, whereas in the cases with larger heat ingress and, consequently, larger thermal and density gradients, separation into a warmer and... [more]

The present work explores computationally the potential of hybrid operation of a direct reduction shaft furnace with a feed gas mixture of methane and hydrogen, considering the operation of the associated gas handling and conversion units (reformers, condensers, heat exchangers, compressors, heaters, etc.). The state of the system is dependent on both the performance of the shaft furnace, which is sensitive to the feed gas composition and quantity, and the reformer, which converts the methane and the recycled top gas from the shaft furnace into feed gas. This coupling gives rise to nonlinear behavior of the system with respect to changes in the boundary conditions, which justifies a model-based approach for holistic analysis. The system is modelled in Aspen Plus to simulate the operation of an industrial-scale plant using a detailed model of the process units. Three configurations of the system are evaluated: (i) co-feeding of hydrogen with methane, (ii) feeding hydrogen directly to th... [more]

Green hydrogen constitutes a strategic energy vector for achieving the Sustainable Development Goals (SDGs 7, 9, 12, and 13) due to its high energy density, flexibility for renewable energy storage, and direct emission-free operation. However, its production critically depends on the supply of high-purity water, which is unsustainable in the context of a projected 40% global water deficit by 2030. Given that more than 97% of available water is saline, integrating desalination processes with electrolysis constitutes an essential strategy for transitioning toward circular economy models in water resource management. This work presents the conceptual design, detailed modeling, and optimization of an integrated process for the sustainable production of green hydrogen from saline water. The system couples a desalination technology (Solar Distillation) with two electrolysis technologies (AEL and SOEC), modeled through physicochemical, electrochemical, and thermodynamic principles. The object... [more]

When designing and planning Green Hydrogen Supply Chains (GHSCs), sustainability considerations are increasingly recognized as essential, particularly in light of decarbonization goals and climate policy targets. Existing research has largely focused on economic and environmental however, social sustainability aspects remain significantly underexplored. This work aims to develop a mathematical programming model to design a GHSC, considering simultaneously economic and social aspects. Solar PV, wind power, and PPA (wind) as energy sources are integrated, while transportation options include the construction of new pipelines, compared to the use of existing highways for trucks carrying liquefied or compressed hydrogen to deliver hydrogen to an oil refinery. The model is applied to a case study conducted in the Brazilian state of Bahia, where different social indicators will be explored, characterizing the case study context while allowing generalization to other contexts. Results allow u... [more]

Hydrogen from biomass gasification combined with carbon capture and storage (CCS) can lead to negative emissions and support Europe's energy transition. This study presents a mixed-integer bilinear optimization model for the cost-optimal design of a Northern European hydrogen supply chain with integrated CCS, focusing on exports from Norway to Germany and CO2 sequestration in Norway. The model is formulated as a superstructure problem and implemented in Pyomo, considering multiple locations for infrastructure nodes and transport options for hydrogen, wood chips, and CO2. The results show that shipping wood chips and CO2 is generally more cost-effective than shipping compressed hydrogen. Supply chain costs range from 35-55 NOK/kg H2, and net-negative emissions (scope 1 and scope 2) are achieved at CO2 capture rates above approximately 30%.

Achieving and sustaining net-zero greenhouse-gas emissions will require the long-term deployment of green hydrogen. Proton exchange membrane water electrolysers (PEMWEs) are attractive for variable renewable electricity (VRE) because of their fast dynamic response; however, they rely on iridium (Ir) anode catalysts, and Ir supply is severely constrained. Here, a Japan-specific dynamic material flow analysis (DMFA) model is developed for 2025-2100 to quantify Ir circularity in PEMWE deployment under a backcasting-oriented hydrogen production pathway. The model tracks Ir in anode catalysts only and represents: (i) Ir demand for new capacity additions and replacements, (ii) end-of-life (EoL) outflows governed by a Weibull lifetime distribution, and (iii) closed-loop recycling characterised by an overall recycling rate across collection, separation/pre-processing, and refining. Sensitivity analyses show that long-term primary Ir requirements are governed by the coupled effects of catalyst... [more]

This document provides supplementary material supporting the Conference Paper “A Multi-Objective Optimisation and Superstructure-Based Decision-Support Tool for Regional Low-Carbon Hydrogen Roadmaps: Methodology and Application to a region of Spain”.

It includes additional methodological details, input data, model assumptions, and extended results that complement the analyses presented in the main manuscript.

Model simulation flowsheet of biomass gasification combined cycle system for simultaneous power and hydrogen production coupled with direct air capture in Aspen Plus.

We designed a novel methylcyclohexane–toluene–hydrogen (MTH) based chemical heat pump (CHP) and determined its key performance indicators using Aspen Plus process simulations.

This study presents a mixed-integer bilinear optimization model for the cost-optimal design of a Northern European hydrogen supply chain with integrated CCS, focusing on exports from Norway to Germany and CO2 sequestration in Norway. The model is formulated as a superstructure problem and implemented in Pyomo, considering multiple locations for infrastructure nodes and transport options for hydrogen, wood chips, and CO2.

This study presents a mixed-integer bilinear optimization model for the cost-optimal design of a Northern European hydrogen supply chain with integrated CCS, focusing on exports from Norway to Germany and CO2 sequestration in Norway. The model is formulated as a superstructure problem and implemented in Pyomo, considering multiple locations for infrastructure nodes and transport options for hydrogen, wood chips, and CO2.