Italy
Assessment of the Use of a Passive Pre-Chamber in a Marine Engine Fueled with Ammonia–Hydrogen Mixtures
Oct 2025
Publication
This study investigates the combustion process in a marine spark-ignition engine fueled with an ammonia–hydrogen blend (15% hydrogen by volume) using a passive pre-chamber. A 3D-CFD model supported by a 1D engine model was employed to analyze equivalence ratios between 0.7 and 0.9 and pre-chamber nozzle diameters from 7 to 3 mm. Results indicate that combustion is consistently initiated by turbulent jets but at an equivalence ratio of 0.7 the charge combustion is incomplete. For lean mixtures reducing nozzle size improves flame propagation although not sufficiently to ensure stable operation. At an equivalence ratio of 0.8 reducing the nozzle diameter from 7 to 5 mm advances CA50 by about 6 CAD while further reduction causes minor variations. At richer conditions nozzle diameter plays a negligible role. Optimal performance was achieved with a 7 mm nozzle at equivalence ratio 0.8 delivering about 43% efficiency and 1.17 MW per cylinder.
Cost-Optimal Design of a Stand-Alone PV-Driven Hydrogen Production and Refueling Station Using Genetic Algorithms
Nov 2025
Publication
Driven by the growing availability of funding opportunities electrolyzers have become increasingly accessible unlocking significant potential for large-scale green hydrogen production. The goal of this investigation is to develop a techno-economic optimization framework for the design of a stand-alone photovoltaic (PV)-driven hydrogen production and refueling station with the explicit objective of minimizing the levelized cost of hydrogen (LCOH). The system integrates PV generation a proton-exchange-membrane electrolyzer battery energy storage compression and high-pressure hydrogen storage to meet the daily demand of a fleet of fuel cell buses. Results show that the optimal configuration achieves an LCOH of 11 €/kg when only fleet demand is considered whereas if surplus hydrogen sales are accounted for the LCOH reduces to 7.98 €/kg. The analysis highlights that more than 75% of total investment costs are attributable to PV and electrolysis underscoring the importance of capital incentives. Financial modeling indicates that a subsidy of about 58.4% of initial CAPEX is required to ensure a 10% internal rate of return under EU market conditions. The proposed methodology provides a reproducible decision-support tool for optimizing off-grid hydrogen refueling infrastructure and assessing policy instruments to accelerate hydrogen adoption in heavy-duty transport.
Hydrogen Utilization for Decarbonizing the Dairy Industry: A Techno-economic Scenario Analysis
Nov 2025
Publication
This study investigates the integration of on-site green hydrogen as a substitute for methane in steam generation in the dairy industry specifically in the production of Parmigiano Reggiano cheese. This represents a novel application of green hydrogen in industrial dairy processing with the potential to reduce greenhouse gas emissions. Hydrogen is assumed to be generated via electrolysis powered by photovoltaic energy. A comprehensive techno-economic assessment was conducted with simulations covering key design variables such as hydrogen fraction in steam production photovoltaic panel orientation and storage pressure. A wide range of scenarios was defined in order to account for variability in system structures and performance and a comprehensive economic assessment was then carried out using a Monte Carlo simulation approach and a sensitivity analysis. Results indicate that in all scenarios the net present value over a 15-year period remains negative when benefits are limited to methane savings. Indeed the high capital expenditure associated with hydrogen systems presents a major barrier. The most favorable cases occur at low hydrogen shares with seasonal storage while full conversion to hydrogen maximizes CO2 abatement but is least economical. With public funding the emissions saved per euro of public support range from 1.58 to 2.14 kg CO2eq/€.
Decarbonised H2 Recovery and CO2 Capture Using a Cost-effective Membrane Plant: A Step Towards Energy Transition
Oct 2025
Publication
Separation of H2 from CO2 is crucial in industry since they are the products of water gas shift reaction. In addition the demand for pure H2 as well as the potential reuse of CO2 as reactant are increasing as a consequence of the transition from fossil fuels to decarbonization processes. In this scenario this work aims to propose a possible solution to get simultaneously pure H2 and CO2 meeting the world’s requirements in terms of reduction of CO2 emissions and transition to cleaner energy. A simulated plant combining Pd-based and SAPO-34 membrane modules is able to provide pure H2 with a final recovery higher than 97%. In addition the entire CO2 fed to SAPO-34 unit is recovered in the permeate stream with a concentration of 97.7%. A cost analysis shows that feed gas gives a higher contribution than compression heat exchange and membranes (e.g. 70 20 3 and 7% respectively). Net profit and net present value are positive within a specific feed gas price range (e.g. net profit up to 0.10 and 0.155 $/Nm3 depending on the labour cost set) showing that the process can be cost-effective and profitable. H2 purification cost ranges between 2.6 and 7.8 $/kg.
Hydrogen Strategies Under Uncertainty: Risk-Averse Choices for Green Hydrogen Pathways
Oct 2025
Publication
The last decade has been characterized by a growing environmental awareness and the rise of climate change concerns. Continuous advancement of renewable energy technologies in this context has taken a central stage on the global agenda leading to a diverse array of innovations ranging from cutting-edge green energy production technologies to advanced energy storage solutions. In this evolving context ensuring the sustainability of energy systems—through the reduction of carbon emissions enhancement of energy resilience and responsible resource integration—has become a primary objective of modern energy planning. The integration of hydrogen technologies for power-to-gas (P2G) and power-topower (P2P) and energy storage systems is one of the areas where the most remarkable progress is being made. However real case implementations are lagging behind expectations due to large-scale investments needed which under high energy price uncertainty act as a barrier to widespread adoption. This study proposes a risk-averse approach for sizing an Integrated Hybrid Energy System considering the uncertainty of electricity and gas prices. The problem is formulated as a mixed-integer program and tested on a real-world case study. The analysis sheds light on the value of synergies and innovative solutions that hold the promise of a cleaner more sustainable future for generations to come.
Application of Machine Learning and Data Augmentation Algorithms in the Discovery of Metal Hydrides for Hydrogen Storage
Nov 2025
Publication
The development of efficient and sustainable hydrogen storage materials is a key challenge for realizing hydrogen as a clean and flexible energy carrier. Among various options metal hydrides offer high volumetric storage density and operational safety yet their application is limited by thermodynamic kinetic and compositional constraints. In this work we investigate the potential of machine learning (ML) to predict key thermodynamic properties—equilibrium plateau pressure enthalpy and entropy of hydride formation—based solely on alloy composition using Magpie-generated descriptors. We significantly expand an existing experimental dataset from ~400 to 806 entries and assess the impact of dataset size and data augmentation using the PADRE algorithm on model performance. Models including Support Vector Machines and Gradient Boosted Random Forests were trained and optimized via grid search and cross-validation. Results show a marked improvement in predictive accuracy with increased dataset size while data augmentation benefits are limited to smaller datasets and do not improve accuracy in underrepresented pressure regimes. Furthermore clustering and cross-validation analyses highlight the limited generalizability of models across different material classes though high accuracy is achieved when training and testing within a single hydride family (e.g. AB2). The study demonstrates the viability and limitations of ML for accelerating hydride discovery emphasizing the importance of dataset diversity and representation for robust property prediction.
An Effective Integrated Optimal Day-ahead and Real-time Power Scheduling Approach for Hydrogen-based Microgrid
Oct 2025
Publication
The increasing penetration of renewable energy sources in power systems poses significant challenges for maintaining grid reliability mainly due to the variability and uncertainty of solar and demand profiles. Microgrids equipped with diverse storage technologies have emerged as a promising solution to address these issues.This paper proposes an integrated day-ahead and real-time power scheduling approach for grid-connected microgrids equipped with both conventional and hydrogen-based ESSs. While existing strategies often address day-ahead and real-time scheduling separately or rely on a single storage technology this work introduces a unified framework that exploits the complementary characteristics of batteries and hydrogen systems. The proposed approach is based on a novel two-stage stochastic optimization model embedded within a hierarchical optimization framework to address these two intertwined problems efficiently. For the day-ahead scheduling a two-stage stochastic programming energy management model is solved to optimize the microgrid schedule based on forecasted load demand and PV production profiles. Building upon the day-ahead schedule another optimization model is solved which addresses real-time power imbalances caused by deviations in actual PV production and load demand power profiles with respect to the forecasted ones with the aim of minimizing operational disruptions. Simulation results demonstrate the validity of the proposed approach achieving both cost reductions and minimal power imbalances. By dynamically adjusting energy flows and using both conventional batteries and hydrogen systems the proposed approach ensures improved reliability reduced operational costs and enhanced integration of RES in microgrids. These findings highlight the potential of the proposed hierarchical framework to support the large-scale deployment of RES while ensuring resilient and cost-effective microgrid operations.
Modelling a Small-scale Hydrogen Valley: Optimisation Under Techno-economic and Environmental Perspectives
Oct 2025
Publication
Renewable hydrogen is a promising pathway to decarbonise hard-to-electrify sectors though its widespread deployment remains hindered by economic challenges. Hydrogen valleys integrated regional systems have emerged as a strategic solution to scale up hydrogen infrastructure and demand. This study assesses the technoeconomic feasibility of a hydrogen valley in southeastern Crete based on the CRAVE-H2 project using a MixedInteger Linear Programming (MILP) optimisation model. The system serves multiple end-uses: touristic fuel cell buses and a vessel as well as cold ironing for ships at berth. In addition to renewable generators electricity can be supplied via a hybrid storage system or purchased from the grid with dispatch optimised according to hourly market prices. A customised modelling framework is developed within PyPSA using the Linopy extension enabling the inclusion of piecewise affine approximations of non-linear performance curves for electrolysers and fuel cells alongside operating range constraints. Hydrogen leakage is also explicitly modelled to assess its environmental and economic implications. The model delivers optimal component sizing energy dispatch strategies and key performance metrics including Levelised Cost Of Hydrogen (LCOH) aggregated Levelised Cost Of Energy (LCOE) and carbon intensity. Most scenarios yield competitive LCOH values between 5.36 and 8.21 €/kgH2 increasing to 15 €/kgH2 under full decarbonisation due to extensive storage investments. Hydrogen emissions that may exceed 10 % of total production in worst-case scenarios become more pronounced in fully decarbonised scenarios. These findings underline the importance of emissions tracking and provide practical insights to inform the design of cost-effective low-emission hydrogen valleys.
Modeling Electrochemical Impedance Spectroscopy of Hydrogen Complexes During Hydrogen Evolution on Single-stom Electrocatalysts
Nov 2025
Publication
Single Atom Catalysts (SACs) are an emerging frontier in heterogeneous electrocatalysis. They are made of metal atoms atomically dispersed on a matrix. A lot of attention has been dedicated to the study of Hydrogen Evolution Reaction (HER) mechanism due to its relevance in energy conversion technologies both with computational and experimental methods. The classical HER mechanism can be described by a Volmer–Heyrovsky–Tafel mechanism where the two desorption steps are competitive. The Volmer-Heyrovsky mechanism is conventionally proposed for single-atom catalysts. It has been computationally demonstrated that hydrogen complexes can form on SACs due to their analogy with homogeneous catalysts. Unfortunately it is hard to “visualize” these species experimentally. Electrochemical Impedance Spectroscopy (EIS) could be the most promising approach to study electrocatalytic mechanisms. In this work we present microkinetic and Electrochemical Impedance Spectroscopy models for HER on SACs describing Volmer-Heyrovsky and a mechanism mediated by the formation of hydrogen complexes. Our simulated data applied to a case study based on Pd@TiN show that Tafel plots will not suffice in the visualization of hydrogen complexes formation and will need the support of electrochemical impedance spectra in order to clarify the correct mechanism.
Techno-Economic Feasibility Analysis of Biomethane Production via Electrolytic Hydrogen and Direct Biogas Methanation
Nov 2025
Publication
Biomethane plays a key role in the green transition offering a renewable carbon-neutral substitute for natural gas while enabling the storage and use of intermittent renewable energy. This work presents a techno-economic assessment of biomethane production through the Power-to-Biomethane concept which combines electrolytic hydrogen from renewable electricity with the direct catalytic methanation of raw biogas from anaerobic digestion. The main objective of this study is to identify the optimal plant size and configuration taking into account the different operational management strategies of the system’s constituting units. The analysis integrates thermochemical modeling with a techno-economic optimization procedure. Three different configurations for renewable energy production photovoltaic-based wind-based and hybrid photovoltaic–wind were evaluated for a case study in Southern Italy. Results show that the hybrid configuration provides the best techno-economic balance achieving the highest annual biomethane output (≈2288 t) and the lowest levelized cost of biomethane (EUR 97.4/MWh). While current biomethane production costs exceed natural gas prices the proposed pathway represents a viable long-term solution for renewable integration and climate-neutral gas supply
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