Publications

Hydrogen is the most abundant element on earth being a low polluting and high efficiency fuel that can be used for various applications such as power generation heating or transportation. As a reaction to climate change authorities are working for determining the most promising applications for hydrogen one of the best examples of crossborder initiative being the IPCEI (Important Project of Common European Interest) on Hydrogen under development at EU level. Given the large interest for future uses of hydrogen special safety measures have to be implemented for avoiding potential accidents. If hydrogen is stored and used under pressure accidental leaks from pressure vessels may result in fires or explosions. Worldwide researchers are investigating possible accidents generated by hydrogen leaks. Special attention is granted to the atmospheric dispersion after the release so that to avoid fires or explosions. The use of consequence modelling software within safety and risk studies has shown its’ utility worldwide. In this paper there are modelled the consequences of the accidental release and atmospheric dispersion of hydrogen from a pressure tank using state-of-the-art QRA software. The simulation methodology used in this paper uses the “leak” model for carrying out discharge calculations. This model calculates the release rate and state of the gas after its expansion to atmospheric pressure. Accidental release of hydrogen is modelled by taking into account the process and meteorological conditions and the properties of the release point. Simulation results can be used further for land use planning or may be used for establishing proper protection measures for surrounding facilities. In this work we analysed two possible accident scenarios which may occur at an imaginary hydrogen refuelling station accidents caused by the leaks of the pressure vessel with diameters of 10 and 20 mm for a pressure tank filled with hydrogen at 35 MPa / 70 MPa. Process Hazard Analysis Software Tool 8.4 has been used for assessing the effects of the scenarios and for evaluating the hazardous extent around the analysed installation. Accident simulation results have shown that the leak size has an important effect on the flammable/explosive ranges. Also the jet fire’s influence distance is strongly influenced by the pressure and actual size of the accidental release.

This study addresses the optimization of urban integrated energy systems (UIESs) under uncertainty in peer-to-peer (P2P) electricity trading by introducing a two-stage robust optimization strategy. The strategy includes a UIES model with a photovoltaic (PV)–green roof hydrogen storage and cascading cold/heat energy subsystems. The first stage optimizes energy trading volume to maximize social welfare while the second stage maximizes operational profit considering uncertainties in PV generation and power prices. The Nested Column and Constraint Generation (NC&CG) algorithm enhances privacy and solution precision. Case studies with three UIESs show that the model improves economic performance energy efficiency and sustainability increasing profits by 1.5% over non-P2P scenarios. Adjusting the robustness and deviation factors significantly impacts P2P transaction volumes and profits allowing system operators to optimize profits and make risk-aligned decisions.

Using High-Temperature Gas-cooled Reactor (HTGR) for hydrogen production through steam methane reforming (SMR) offers advantages such as high hydrogen yield methane savings relatively low cost and ease of scale-up. However due to the limitation of the temperature of the heating helium gas the methane conversion ratio of SMR using HTGR is much lower than that of traditional SMR. The membrane reactor (MR) with its high conversion efficiency compact structure and low cost is a suitable way to improve the methane conversion ratio. This study establishes a one-dimensional reaction flow model for MR heated by the helium gas from HTGR. And the model is validated and applied to analyze the performance of MR. The results show that compared to the original reformer tube MR demonstrates superior performance especially at higher methane conversion ratio and hydrogen yield. And the significant impact of sweep gas and membrane thickness on the performance of MR is discussed in detail. This work offers a new insight into highly enhancing the efficiency of SMR for hydrogen production using HTGR.

Advancements in water electrolysis technologies are crucial for green hydrogen production. Proton exchange membrane water electrolysis (PEMWE) is characterized by its efficiency and environmental benefits. The pre diction and optimization of hydrogen production rates (HPRs) in PEMWE systems is difficult and still challenging because of the complexity of the system as well as the operational parameters. The integration of artificial in telligence (AI) and machine learning (ML) appears to be effective in optimization within the energy sector. Hence this work employs the artificial neural network (ANN) to develop a model that accurately predicts HPR in PEMWE setups. A novel approach is introduced by employing the Levenberg–Marquardt backpropagation (LMBP) algorithm for training the ANN. This model is designed to predict HPR based on critical operational parameters including anode and cathode areas (mm2 ) cell voltage (V) and current (A) water flow rate (mL/ min) power (W) and temperature (K). The optimized ANN configuration features an architecture with 7 input nodes two hidden layers of 64 neurons each and a single output node. The performance of the ANN model was evaluated against conventional regression models using key metrics: mean squared error (MSE) coefficient of determination (R2 ) and mean absolute error (MAE). The findings of this study reveal that the developed ANN model significantly outperforms traditional models achieving an R2 value of 0.9989 and an MAE of 0.012. In comparison random forest (R2 = 0.9795) linear regression (R2 = 0.9697) and support vector machines (R2 = − 0.4812) show lower predictive accuracy underscoring the ANN model’s superior performance. This work demonstrates the efficiency of the LMBP in enhancing hydrogen production forecasts and sets a foundation for future improvements in PEMWE efficiency. By enabling precise control and optimization of operational pa rameters this study contributes to the broader goal of advancing green hydrogen production as a viable and scalable alternative to fossil fuels offering both immediate and long-term benefits to sustainable energy initiatives.

The energy sector constitutes a dynamic and complex system indicating that its actions are influenced not just by its individual components but also by the emergent behavior resulting from interactions among them. Moreover there are crucial limitations of previous approaches for addressing the sustainability challenge of the energy sector. Changing transforming and integrating paradigms are the most relevant leverage points for transforming a given system. In other words nowadays the integration of new predominant paradigms in order to provide a unified framework could aim at this actual transformation looking for a sustainable future. This research aims to develop a new unified framework for the integration of the following three paradigms: (1) Sustainability (2) Complexity and (3) Systems Thinking which will be applied to achieving sustainable energy production (using hydrogen production as a case study). The novelty of this work relies on providing a holistic perspective through the integration of the aforementioned paradigms considering the multiple and complex interdependencies among the economy the environment and the economy. For this purpose an integrated seven-stage approach is introduced which explores from the starting point of the integration of paradigms to the application of this integration to sustainable energy production. After applying the Three-Paradigm approach for sustainable hydrogen production as a case study 216 feedback loops are identified due to the emerged complexity linked to the analyzed system. Additionally three system dynamics-based models are developed (by increasing the level of complexity) as part of the application of the Three-Paradigm approach. This research can be of interest to a broad professional audience (e.g. engineers policymakers) as looks into the sustainability of the energy sector from a holistic perspective considering a newly developed Three-Paradigm model considering complexity and using a Systems Thinking approach.

Hard-to-electrify sectors will require renewable fuels to facilitate the green transition in the future. Therefore it is crucial to identify promising production locations while taking into account the local biomass resources variable renewable energy sources and the synergies between sectors. In this study investments and dispatch operations are optimised of a large catalogue of renewable fuel production technologies in the opensource software SpineOpt and this is soft-linked to the comprehensive energy system model Balmorel. We analyse future production pathways by comparing various levels of hydrogen infrastructure including large-scale hydrogen storage and assess system impacts. The results indicate that methanol may provide synergies in its multipurpose use as an early (2030-2040) shipping fuel and later as an aviation fuel through further refining if ammonia becomes more competitive (2050). We furthermore show that a hydrogen infrastructure increases the competitiveness of non-flexible hydrogen-based fuel production technologies. Offshore electrolysis hubs decrease energy system impacts in scenarios with 105 TWh of Nordic hydrogen export. However hydrogen export scenarios are much costlier compared to scenarios with no export unless a high hydrogen price is received. Finally we find that emission taxes in the range of 250-265 euro/tCO2 will be necessary for renewable fuels to become competitive.

In this podcast episode Hydrogen Europe CEO Jorgo Chatzimarkakis engages in a dynamic conversation with Hydrogen Europe Research President Luigi Crema. Together they delve into the crucial partnership between industry and research within the hydrogen sector. The episode explores the symbiotic relationship between innovative research initiatives and practical industry applications shedding light on how collaboration fosters advancements in hydrogen technology.

This study investigates hydrogen and hydrogen-methane mixtures as alternative fuels for industrial burners focusing on combustion dynamics flame stability and emissions. CFD simulations in ANSYS Fluent utilized the RANS framework with the k-ε turbulence model and the mixture fraction/PDF approach. Supporting Python scripts and Cantera-based kinetic modeling employing the GRI-Mech 3.0 mechanism and Zeldovich pathways analyzed equivalence ratios (Φ) adiabatic flame temperatures (Tad) and NOx formation mechanisms. Results revealed non-linear temperature trends with a 50 % hydrogen blend yielding the lowest peak temperature (1880 K) and a 75 % hydrogen blend achieving optimal performance balancing peak temperatures (~1900 K) reduced NOx emissions (5.39 × 10-6) and near-zero CO2 emissions (0.137) though flame stability was impacted by rich mixtures. Pure hydrogen combustion produced the highest peak temperature (2080 K) and NOx emissions (3.82 × 10-5) highlighting the need for NOx mitigation strategies. Mass flow rate (MFR) adjustments and excess air variation significantly influenced emissions with a 25 % MFR increase reducing NOx to 2.8 × 10-5 while higher excess air (e.g. 30 %) raised NOx under lean conditions. Statistical analysis identified Φ hydrogen content (H2%) and flame stability as key factors with 50 %–75 % hydrogen blends minimizing emissions and optimizing performance emphasizing hydrogen’s potential with controlled MFR and air adjustments.

More than 150 Hydrogen refueling stations were built around the world in the past 10 years. Much of the technical issues with passenger fuel cell car were discussed and studied. However fuel cell passenger cars are still far from mass production stage. The problem mainly lies with the high cost of fuel cell car production and insufficient hydrogen refueling infrastructure. While the future of fuel cell passenger cars are not clear fuel cell for personal mobility devices like bicycles get more and more attractive. This is mainly due to the simplicity in system design and reducing cost of small size hydrogen fuel cells. But for this technology to be commercialized affordable hydrogen refueling stations is crucial. This study discusses solutions for small sized hydrogen refueling stations based on pressure equalization and simulates the Hydrogen utilization ratio based on different equipment setup. The study is also supported with the experimental data from prototype fuel cell vehicles developed by eMobility in Singapore.

Hydrogen is on the rise as a substitute for fossil fuel in the energy sector. While this substitution does not happen dramatically the steady increase in hydrogen related research might be a good indicator of such desire. As it stands there are issues regarding its safe handling and use; consequently the health and safety subsectors observe the situation conspicuously. As we yet to know the behavior of hydrogen in critical situations uncertainties make these tasks prone to emerging risks. Thus hydrogen safety falls under emerging risk studies. Conventional perspective on safety especially regarding the flammable material focuses on calculating the hypothetical risks of failures in system. Resilience Engineering has another perspective as it focuses on normal operations offering new perspectives to tackle emerging risks from a new angle. Born from the heart of Resilience Engineering the Functional Resonance Analysis Method (FRAM) captures sociotechnical systems’ essence in a tangible way. In this study FRAM has been used to model a series of experiments done on hydrogen management to analyze its jet fire. FRAM is used to test whether the method could be suitable to model a system in which emerging risks are present. It is the conclusion of this study that FRAM seems promising in raising risk awareness especially when available data is limited.