Applications & Pathways

As hydrogen fuel cell vehicles gain momentum as crucial zero-emission transportation solutions the urgency to address hydrogen permeability through the polymer liner becomes paramount for ensuring the safety efficiency and longevity of Type IV hydrogen storage tanks. This paper synthesizes existing research findings analyzes the influence of different materials and structures on gas permeability elucidates the dissolution and diffusion mechanisms of hydrogen in plastic liners and discusses their engineering applications. We focus on measurement methods influencing factors and improvement strategies for liner gas permeability. Additionally we explore the prospects of Type IV hydrogen storage tanks in fields such as automotive aerospace and energy storage industries. Through this comprehensive review of liner gas permeability critical insights are provided to guide the development of efficient and safe hydrogen storage and transportation systems. These insights are vital for advancing the widespread application of hydrogen energy technology and fostering sustainable energy development significantly contributing to efforts aimed at enhancing the performance and safety of Type IV hydrogen storage tanks.

The transportation sector is a significant contributor to global carbon emissions thus necessitating a transition toward renewable energy sources (RESs) and electric vehicles (EVs). Among EV technologies fuel-cell EVs (FCEVs) offer distinct advantages in terms of refueling time and operational efficiency thus rendering them a promising solution for sustainable transportation. Nevertheless the integration of FCEVs in rural areas poses challenges due to the limited availability of refueling infrastructure and constraints in energy access. In order to address these challenges this study proposes a multi-objective energy management model for a hydrogen refueling station (HRS) integrated with RESs a battery storage system an electrolyzer (EL) a fuel cell (FC) and a hydrogen tank serving diverse FCEVs in rural areas. The model formulated using mixed-integer linear programming (MILP) optimizes station operations to maximize both cost and load factor performance. Additionally bi-directional trading with the power grid and hydrogen network enhances energy flexibility and grid stability enabling a more resilient and self-sufficient energy system. To the best of the authors’ knowledge this study is the first in the literature to present a multi-objective optimal management approach for grid-interactive renewablesupported HRSs serving hydrogen-powered vehicles in rural areas. The simulation results demonstrate that RES integration improves economic feasibility by reducing costs and increasing financial gains while maximizing the load factor enhances efficiency cost-driven strategies that may impact stability. The impact of the EL on cost is more significant while RES capacity has a relatively smaller effect on cost. However its influence on the load factor is substantial. The optimization of RES-supported hydrogen production has been demonstrated to reduce external dependency thereby enabling surplus trading and increasing financial gains to the tune of USD 587.83. Furthermore the system enhances sustainability by eliminating gasoline consumption and significantly reducing carbon emissions thus supporting the transition to a cleaner and more efficient transportation ecosystem.

Virtual power plants (VPPs) are gaining significance in the energy sector due to their capacity to aggregate distributed energy resources (DERs) and optimize energy trading. However their effectiveness largely depends on accurately modeling the uncertain parameters influencing optimal bidding strategies. This paper proposes a deep learning-based forecasting method to predict these uncertain parameters including solar irradiation temperature wind speed market prices and load demand. A stochastic programming approach is introduced to mitigate forecasting errors and enhance accuracy. Additionally this research assesses the flexibility of VPPs by mapping the flexible regions to determine their operational capabilities in response to market dynamics. The study also incorporates power-to‑hydrogen (P2H) and hydrogen-to-power (H2P) conversion processes to facilitate the integration of hydrogen fuel cell vehicles (HFCVs) into VPPs enhancing both technical and economic aspects. A network-aware VPP connected to generation resources storage facilities demand response programming (DRP) vehicle-to-grid technology (V2G) P2H and H2P is used to evaluate the proposed method. The problem is formulated as a convex model and solved using the GUROBI optimizer. Results indicate that a hydrogen refueling station can increase profits by approximately 49 % compared to the base case of directly selling surplus generation from renewable energy sources (RESs) to the market and profits can further increase to roughly 86 % when other DERs are incorporated alongside the hydrogen refueling station.

Reducing CO2 emissions is an increasingly important goal in general aviation. The dual-fuel hydrogen–kerosene combustion process has proven to be a suitable technology for use in small aircraft. This robust and reliable technology significantly reduces CO2 emissions due to the carbon-free combustion of hydrogen during operation while pure kerosene or sustainable aviation fuel (SAF) can be used in safety-critical situations or in the event of fuel supply issues. Previous studies have demonstrated the potential of this technology in terms of emissions performance and efficiency while also highlighting challenges related to abnormal combustion phenomena such as knocking and pre-ignition which limit the maximum achievable hydrogen energy share. However the causes of such phenomena—especially regarding the role of lubricating oils—have not yet been sufficiently investigated in hydrogen engines making this a crucial area for further development. In this paper investigations at the TU Wien Institute of Powertrain and Automotive Technology concerning the role of different engine oils in influencing pre-ignition tendencies in a hydrogen–kerosene dual-fuel engine are described. A specialized test procedure was developed to account for the unique combustion characteristics of the dual-fuel process along with a detailed purge procedure to minimize oil carryover. Multiple engine oils with varying compositions were tested to evaluate their influence on pre-ignition tendencies with a particular focus on additives containing calcium magnesium and molybdenum known for their roles in detergent and anti-wear properties. Additionally the study addressed the contribution of particles to pre-ignition occurrences. The results indicate that calcium and magnesium exhibit no notable impact on pre-ignition behavior; however the addition of molybdenum results in a pronounced reduction in pre-ignition events which could enable a higher hydrogen energy share and thus decrease CO2 emissions in the context of hydrogen dual-fuel aviation applications.

This study explores a multi-faceted approach to improving the combustion performance and emission characteristics of a single-cylinder four-stroke direct injection (DI) compression ignition engine through the combined effects of butanol enrichment green-synthesized copper oxide (CuO) nanoparticles and hydrogen supplementation. The baseline fuel was a B20 biodiesel blend further enriched with 10 % butanol to enhance oxygen availability and atomization. CuO nanoparticles were synthesized via an eco-friendly aloe vera extractmediated method and dispersed into the fuel to promote oxidation kinetics and stabilize combustion. Experimental results revealed that the B20+But10 %+CuO100 blend achieved the highest brake thermal efficiency (BTE) of 33.6 % at full load alongside notable reductions in carbon monoxide (CO) unburned hydrocarbons (HC) nitrogen oxides (NOx) and smoke opacity compared to neat B20. Reactivity controlled compression ignition (RCCI) trials further demonstrated that hydrogen enrichment at 5 LPM and 10 LPM improved flame propagation Brake thermal efficiency (33.89 % & 35.43 %) and reduced brake-specific fuel consumption of nearly 10 % (0.26 Kg/KWh) & 0.25 Kg/KWh). While excessive hydrogen supply (10 LPM) marginally increased HC emissions (110 PPM) at higher loads due to localized incomplete oxidation overall results confirm significant emission mitigation. The findings highlight that the synergistic integration of butanol oxygenation catalytically active CuO nanoparticles and optimized hydrogen enrichment offers a viable pathway toward cleaner combustion improved energy efficiency and reduced pollutant emissions in biodiesel-fueled CI engines.

This study develops and applies a life cycle assessment (LCA) framework combined with predictive market models to evaluate the environmental impacts of electricity and hydrogen for transport in the EU27+UK from 2020 to 2050. By linking evolving power sector scenarios with hydrogen supply models we assess the wellto-wheels (WTW) performance of battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs) under consistent energy assumptions. Results show that electricity decarbonization can reduce GWP by up to 80% by 2050 but increases land use and mineral/metal demand due to renewable infrastructure expansion. The environmental impacts of hydrogen production are strongly influenced by the electricity mix especially in high electrolysis scenarios. WTW analysis indicates that while BEVs consistently achieve lower WTW GWP than FCEVs across all scenarios both drivetrains exhibit notable trade-offs in other impact categories. Scenarios dominated by blue hydrogen although not optimal in terms of GWP present a more balanced environmental profile making them a viable transitional pathway in contexts that prioritize minimizing other environmental impacts.

The thermal management system and the balance-of-plant (BoP) in fuel cell electric vehicles (FCEV) are characterized by a particularly high level of complexity and a number of interfaces. Optimizing the efficiency of the overall vehicle is of special importance to maximize the range and increase the attractiveness of this technology to customers. This paper focuses on the optimization potential of the air supply system in the BoP whereby the charging concepts of the electric supercharger (ESC) and the electrically assisted turbocharger (EAT) as well as the integration of water spray injection (WSI) at the compressor inlet are investigated in the framework of an FCEV complete vehicle co-simulation. As a benchmark for the integration of these optimization measures the complete vehicle co-simulation is designed for a fuel cell electric passenger car of the current generation. Here thermo-hydraulic fluid circuits in the thermal management software KULI are coupled with mathematical-physical models in MATLAB/Simulink. Applying advanced simulation methodologies for the components of fuel cell powertrain and vehicle cabin enables the mapping of the effects of realistic operating conditions on the FCEV characteristics. The EAT offers the advantage over the ESC that due to the arrangement of an exhaust gas turbine a part of the exhaust gas enthalpy flow downstream of the fuel cell stack can be recovered which reduces the electrical compressor drive power. Moreover an additional reduction of this power consumption can be achieved by WSI as the effect of evaporative cooling lowers the initial compression temperature. For analysis and comparison these concepts are again modeled with high degree of detail and integrated into the benchmark overall vehicle simulation. The results indicate considerable reductions in the electric compressor drive power of the EAT compared to the ESC with noteworthy potential for reducing the vehicle’s hydrogen consumption. At an operating point in Worldwide harmonized Light Duty Test Cycle (WLTC) under 35 ◦ C ambient temperature and 25 % relative humidity the electrical compressor drive power shows a reduction potential of −40 % which corresponds to a vehicle-level hydrogen consumption reduction of up to −3 %. In addition the results also highlight the effect of the WSI in both charging concepts whereby its potential to reduce the hydrogen consumption on the overall vehicle level is relatively small. In WLTC at 35 ◦C ambient temperature and 25 % relative humidity the compressor drive power reduction potential for ESC and EAT averages −5 % while the effect on hydrogen consumption is only around −0.25 %.

This paper presents QDQN-ThermoNet a novel Quantum-Driven Dual Deep Q-Network framework for intelligent thermal regulation in next-generation electric vehicles with hybrid energy systems. Our approach introduces a dual-agent architecture where a classical DQN governs solid-state battery thermal management while a quantumenhanced DQN regulates proton exchange membrane fuel cell dynamics both sharing a unified quantumenhanced experience replay buffer to facilitate cross-system information transfer. Hardware-in-the-Loop validation across diverse operational scenarios demonstrates significant performance improvements compared to classical methods including enhanced thermal stability (95.1 % vs. 82.3 %) faster thermal response (2.1 s vs. 4.7 s) reduced overheating events (0.3 vs. 3.2) and superior energy efficiency (22.4 % energy savings). The quantum-enhanced components deliver 38.7 % greater sample efficiency and maintain robust performance under sparse data conditions (33.9 % improvement) while material-adaptive control strategies leveraging MXeneenhanced phase change materials achieve a 50.3 % reduction in peak temperature rise during transients. Component lifetime analysis reveals a 33.2 % extension in battery service life through optimized thermal management. These results establish QDQN-ThermoNet as a significant advancement in AI-driven thermal management for future electric vehicle platforms effectively addressing the complex challenges of coordinating thermal regulation across divergent energy sources with different optimal operating temperatures.

This study investigates numerically combustion attributes and NOx formation of premixed ammonia-hydrogen/air flames within a swirl burner of a gas turbine considering various conditions of hydrogen fraction (HF: 0 % 5 % 30 % 40 % and 50 %) equivalence ratio (φ: 0.85 1.0 and 1.2) and mixture inlet temperature (Tin: 400–600 K). The results illustrate that flame temperature increases with hydrogen addition from 1958 K for pure ammonia to 2253 K at 50 % HF. Raising the inlet temperature from 400 K to 600 K markedly enhances combustion intensity resulting in an increase of the Damköhler number (Da) from 117 to 287. NOx levels rise from ∼1800 ppm (0 % HF) to ∼7500 ppm (50 % HF) and peak at 8243 ppm under lean conditions (φ = 0.85). Individual NO N2O and NO2 emissions also reach maxima at φ = 0.85 with values of 5870 ppm 2364 ppm and 10 ppm respectively decreasing significantly under richer conditions (2547 ppm 1245 ppm and 5 ppm at φ = 1.2). These results contribute to advancing low-carbon fuel technologies and highlight the viability of ammonia-hydrogen co-firing as a pathway toward sustainable gas turbine operation.

This study presents a comprehensive review of the viability of hydrogen as an energy carrier for offshore wind energy compared to existing electricity carrier systems. To enable a state-of-the-art system comparison a review of wind-to-hydrogen energy conversion and transmission systems is conducted alongside wind-to-electricity systems. The review reveals that the wind-to-hydrogen energy conversion and transmission system becomes more cost-effective than the wind-to-electricity conversion and transmission system for offshore wind farms located far from the shore. Electrical transmission systems face increasing technical and economic challenges relative to the hydrogen transmission system when the systems move farther offshore. This study also explores the feasibility of using seawater for hydrogen production to conserve freshwater resources. It was found that while this approach conserves freshwater and can reduce transportation costs it increases overall system costs due to challenges such as membrane fouling in desalination units. Findings indicated that for this approach to be sustainable proper management of these challenges and responsible handling of saline waste are essential. For hydrogen energy transmission this paper further explores the potential of repurposing existing oil and gas pipeline infrastructure instead of constructing new pipelines. Findings indicated that with proper retrofitting the existing natural gas pipelines could provide a cost-effective and environmentally sustainable solution for hydrogen transport in the near future.

This paper explores how the deployment of “High-Performance Heat-Powered Heat Pumps” (HP3 s)—a novel heating technology—could help meet the domestic heating demand in the UK and reduce how much grid-scale energy storage is needed in comparison to a scenario where electrical heat pumps fully supply the heating demand. HP3 systems can produce electricity which can partially alleviate the stress caused by electrical heat pumps. A parametric analysis focusing on two variables the penetration of HP3 systems (H) and the amount of electricity exported (Ɛ) is presented. For every combination of H and Ɛ the electricity system is optimized to minimize the cost of electricity. Three parameters define the electricity system: the generation mix the energy storage mix and the amount of over-generation. The cost of electricity is at its highest when electrical heat pumps supply all demand. This reduces as the penetration of HP3 systems increases due to a reduction in the need for energy storage. When HP3 systems supply 100% of the heating demand the total cost of electricity and the storage capacity needed are 6% and 50% lower respectively compared to a scenario where electrical heat pumps are in 100% of residences.

Ammonia is a highly promising zero-carbon fuel for engines. However it exhibits high ignition energy slow flame propagation and severe pollutant emissions so it is usually burned in combination with highly reactive fuels such as hydrogen. An accurate understanding and modeling of ammonia–hydrogen combustion is of fundamental and practical significance to its application. Deep Neural Networks (DNNs) demonstrate significant potential in autonomously learning the interactions between high-dimensional inputs. This study proposed a deep neural network-based method for optimizing chemical reaction mechanism parameters producing an optimized mechanism file as the final output. The novelty lies in two aspects: first it systematically compares three DNN structures (Multilayer perceptron (MLP) Convolutional Neural Network and Residual Regression Neural Network (ResNet)) with other machine learning models (generalized linear regression (GLR) support vector machine (SVM) random forest (RF)) to identify the most effective structure for mapping combustion-related variables; second it develops a ResNet-based surrogate model for ammonia–hydrogen mechanism optimization. For the test set (20% of the total dataset) the ResNet outperformed all other ML models and empirical correlations achieving a coefficient of determination (R2 ) of 0.9923 and root mean square error (RMSE) of 135. The surrogate model uses the trained ResNet to optimize mechanism parameters based on a Stagni mechanism by mapping the initial conditions to experimental IDT. The results show that the optimized mechanism improves the prediction accuracy on laminar flame speed (LFS) by approximately 36.6% compared to the original mechanism. This method while initially applied to the optimization of an ammonia–hydrogen combustion mechanism can potentially be adapted to optimize mechanisms for other fuels.

Refrigeration units in semi-trucks or rigged-body trucks have an energy demand of 8.2–12.4 MWh/y and emit 524.26 kt CO2e/y in Germany. Electrification with fuel cell systems reduces the CO2 emission but an increase of efficiency is necessary because of rapidly increasing hydrogen costs. A metal hydride refrigeration system can increase the efficiency. Even though it was already demonstrated in lab scale with 900 W this power is not sufficient to support a truck refrigeration system and the power output of the lab system was not controllable. Here we show the design and validation of a MATLAB© Simulink model of this metal hydride refrigeration system and its suitability for high power applications with a scaled-up reactor. It was scaled up to rated power of 5 kW and efficiency improvements with an advanced valve switching as well as a controlled cooling pump were implemented. Two application-relevant use cases with hydrogen mass flows from hydrogen fuel cell truck systems were analyzed. The simulation results of these use cases provide an average cooling power of 4.2 and 6.1 kW. Additionally the control of the coolant mass flow at different temperature levels a controlled hydrogen mass flow with a bypass system and an advanced valve switching mechanism increased the system efficiency of the total refrigeration system by 30 % overall.

The growing demand for air connectivity coupled with the forecasted increase in passengers by 2040 implies an exigency in the aviation sector to adopt sustainable approaches for net zero emission by 2050. Sustainable Aviation Fuel (SAF) is currently the most promising short-term solution; however ensuring its overall sustainability depends on reducing the life cycle carbon footprints. A key challenge prevails in hydrogen usage as a reactant for the approved ASTM routes of SAF. The processing conversion and refinement of feed entailing hydrodeoxygenation (HDO) decarboxylation hydrogenation isomerisation and hydrocracking requires substantial hydrogen input. This hydrogen is sourced either in situ or ex situ with the supply chain encompassing renewables or non-renewables origins. Addressing this hydrogen usage and recognising the emission implications thereof has therefore become a novel research priority. Aside from the preferred adoption of renewable water electrolysis to generate hydrogen other promising pathways encompass hydrothermal gasification biomass gasification (with or without carbon capture) and biomethane with steam methane reforming (with or without carbon capture) owing to the lower greenhouse emissions the convincing status of the technology readiness level and the lower acidification potential. Equally imperative are measures for reducing hydrogen demand in SAF pathways. Strategies involve identifying the appropriate catalyst (monometallic and bimetallic sulphide catalyst) increasing the catalyst life in the deoxygenation process deploying low-cost iso-propanol (hydrogen donor) developing the aerobic fermentation of sugar to 14 dimethyl cyclooctane with the intermediate formation of isoprene and advancing aqueous phase reforming or single-stage hydro processing. Other supportive alternatives include implementing the catalytic and co-pyrolysis of waste oil with solid feedstocks and selecting highly saturated feedstock. Thus future progress demands coordinated innovation and research endeavours to bolster the seamless integration of the cutting-edge hydrogen production processes with the SAF infrastructure. Rigorous technoeconomic and life cycle assessments alongside technological breakthroughs and biomass characterisation are indispensable for ensuring scalability and sustainability

The paper studies and analyzes electric vehicle engines powered by hydrogen under the WLTP standard driving protocol. The driving range extension is estimated using a specific protocol developed for FCEV compared with the standard value for battery electric vehicles. The driving range is extended by 10 km averaging over the four protocols with a maximum of 11.6 km for the FTP-75 and a minimum of 7.7 km for the WLTP. This driving range extension represents a 1.8% driving range improvement on average. Applying the FCEV current weight the driving range is extended to 18.9 km and 20.4 km on average when using power source energy capacity standards for BEVs and FCEVs.

Aiming at the problems of poor transient characteristics of converter output DC voltage and large DC current ripple caused by alkaline electrolyzer (AEL) switching operation in the wind power-hydrogen coupled integrated system this paper proposes an interleaved parallel VDCM control method to improve the stable operation of the system. Firstly a refined mathematical-physical model of the wind power-hydrogen coupled integrated system including HD-PMSG interleaved parallel buck and AEL is constructed. Then the VDCM control strategy is introduced into the interleaved parallel buck converter which provides reliable inertia and damping support for the output voltage of the hydrogen production system by simulating the DC motor power regulation characteristics and effectively improving the current ripple of the output current. Meanwhile the influence of rotational inertia and the damping coefficient on the dynamic stability of the system in the control strategy is analyzed based on the small signal method. Finally the proposed method is validated through MATLAB/SIMULINK simulation experiments and RCP + HIL hardware-in-the-loop experiments. The results show that the proposed method can improve the dynamic stability of the wind power-hydrogen coupled integrated system effectively.

This study evaluates the techno-economic performance of hybrid renewable microgrids integrating hydrogen storage and fuel cells in two Moroccan pilot farms: a grid-connected site (BLFARM) and an off-grid site (RIMSAR). Real meteorological and load data were analyzed in HOMER Pro to assess feasibility. In 2024 BLFARM achieved a Levelized Cost of Energy (LCOE) of e1.63/kWh and a Renewable Fraction (Ren Frac) of 83.9% while RIMSAR reached e4.32/kWh with 100% renewable contribution. Hydrogen use remained limited due to low demand and high costs. Assuming 2050 hydrogen-technology reductions LCOE decreased to e0.160/kWh (BLFARM) and e0.425/kWh (RIMSAR) while hydrogen components were still underutilized. Aggregating demand from 5-80 farms reduced LCOE by over 50% from e0.093 to e0.045/kWh (BLFARM) and from e0.142 to e0.074/kWh (RIMSAR) while increasing electrolyzer and fuelcell operation. Community-networked hydrogen microgrids thus enhance component utilization energy resilience and cost effectiveness in rural Moroccan agriculture.

Due to the lower radiative fraction and typically higher storage pressures gas temperatures can often result in longer safety distances compared to radiative heat transfer for hydrogen jet flames. The high temperatures however also lead to a low density causing the flow to rise at a certain distance from the release. Unfortunately a model to determine this distance similar to what is available for unignited releases is currently not available which this paper aim to provide. An experimental study was conducted investigating the buoyancy effect on ignited horizontal hydrogen jet releases with different release diameters. The invisible hydrogen plume was visualized using a Background Oriented Schlieren technique (BOS). The transition of the initial momentumdriven jet into a fully buoyancy-driven jet was estimated by following the gradient of the centerline of the plume. A model based on the Froude number of the release similar to the model for unignited releases was developed and the distance showed a very similar dependence on the Froude number but giving consistently approximately 39% shorter distances.

As a zero-carbon energy carrier hydrogen is playing an increasingly vital role in the decarbonization of maritime transportation. The hydrogen pressure reducing valve (PRV) is a core component of ship-borne hydrogen storage systems directly influencing the safety efficiency and reliability of hydrogen-powered vessels. However the marine environment— characterized by persistent vibrations salt spray corrosion and temperature fluctuations— poses significant challenges to PRV performance including material degradation flow instability and reduced operational lifespan. This review comprehensively summarizes and analyzes recent advances in the study of high-pressure hydrogen PRVs for marine applications with a focus on transient flow dynamics turbulence and compressible flow characteristics multi-stage throttling strategies and valve core geometric optimization. Through a systematic review of theoretical modeling numerical simulations and experimental studies we identify key bottlenecks such as multi-physics coupling effects under extreme conditions and the lack of marine-adapted validation frameworks. Finally we conducted a preliminary discussion on future research directions covering aspects such as the construction of coupled multi-physics field models the development of marine environment simulation experimental platforms the research on new materials resistant to vibration and corrosion and the establishment of a standardized testing system. This review aims to provide fundamental references and technical development ideas for the research and development of high-performance marine hydrogen pressure reducing valves with the expectation of facilitating the safe and efficient application and promotion of hydrogen-powered shipping technology worldwide.

The hybrid energy storage system (HESS) that combines battery with hydrogen storage exploits complementary power/energy characteristics but most studies optimize capacity and operation separately leading to suboptimal overall performance. To address this issue this paper proposes a bi-level co-optimization framework that integrates deep reinforcement learning (DRL) and mixed integer programming (MIP). The outer layer employs the TD3 algorithm for capacity configuration while the inner layer uses the Gurobi solver for optimal operation under constraints. On a standalone PV–wind–load-HESS system the method attains near-optimal quality at dramatically lower runtime. Relative to GA + Gurobi and PSO + Gurobi the cost is lower by 4.67% and 1.31% while requiring only 0.52% and 0.58% of their runtime; compared with a direct Gurobi solve the cost remains comparable while runtime decreases to 0.07%. Sensitivity analysis further validates the model’s robustness under various cost parameters and renewable energy penetration levels. These results indicate that the proposed DRL–MIP cooperation achieves near-optimal solutions with orders of magnitude speedups. This study provides a new DRL–MIP paradigm for efficiently solving strongly coupled bi-level optimization problems in energy systems.

The urgent global transition toward low-carbon energy systems has highlighted the need for systematic planning of hydrogen refueling stations (HRS) to facilitate clean energy adoption. This study develops an integrated framework for regional HRS layout optimization and carbon emission assessment considering population distribution land area and hydrogen demand. Using Hainan Province as a case study the model estimates regional hydrogen demand determines optimal HRS deployment evaluates spatial coverage and refueling distances and quantifies potential carbon emission reductions under various renewable energy scenarios. Model validation with Haikou demonstrates its reliability and applicability at the regional scale. Results indicate pronounced spatial disparities in hydrogen demand and infrastructure requirements emphasizing that prioritizing station deployment in densely populated urban areas can enhance accessibility and maximize emission reduction. The framework offers a practical data-efficient tool for policymakers and planners to guide early-stage hydrogen infrastructure development and supports strategies for regional decarbonization and sustainable energy transitions.

While community energy initiatives and pilot projects have demonstrated technical feasibility and economic benefits their site-specific nature limits transferability to systematic scalable investment models. This study addresses this gap by proposing a modular framework for Renewable Energy Valleys (REVs) developed from real-world Community Energy Lab (CEL) demonstrations in Crete Greece which is an island with pronounced seasonal demand fluctuation strong renewable potential and ongoing hydrogen valley initiatives. Four modular business schemes are defined each representing different sectoral contexts by combining a baseline of 50 residential units with one representative large consumer (hotel rural households with thermal loads municipal swimming pool or hydrogen bus). For each scheme a mixed-integer linear programming model is applied to optimally size and operate integrated solar PV wind battery (BAT) energy storage and hydrogen systems across three renewable energy penetration (REP) targets: 90% 95% and 99.9%. The framework incorporates stochastic demand modeling sector coupling and hierarchical dispatch schemes. Results highlight optimal technology configurations that minimize dependency on external sources and curtailment while enhancing reliability and sustainability under Mediterranean conditions. Results demonstrate significant variation in optimal configurations across sectors and targets with PV capacity ranging from 217 kW to 2840 kW battery storage from 624 kWh to 2822 kWh and hydrogen systems scaling from 65.2 kg to 192 kg storage capacity. The modular design of the framework enables replication beyond the specific context of Crete supporting the scalable development of Renewable Energy Valleys that can adapt to diverse sectoral mixes and regional conditions.

Driven by carbon neutrality goals electric–hydrogen coupled virtual power plants (EHCVPPs) integrate renewable hydrogen production with power system flexibility resources emerging as a critical technology for large-scale renewable integration. As distributed energy resources (DERs) within EHCVPPs diversify heterogeneous resources generate diversified market values. However inadequate benefit allocation mechanisms risk reducing participation incentives destabilizing cooperation and impairing operational efficiency. To address this benefit allocation must balance fairness and efficiency by incorporating DERs’ regulatory capabilities risk tolerance and revenue contributions. This study proposes a multi-stage benefit allocation framework incorporating risk–reward tradeoffs and an enhanced optimization model to ensure sustainable EHCVPP operations and scalability. The framework elucidates bidirectional risk–reward relationships between DERs and EHCVPPs. An individualized risk-adjusted allocation method and correction mechanism are introduced to address economic-centric inequities while a hierarchical scheme reduces computational complexity from diverse DERs. The results demonstrate that the optimized scheme moderately reduces high-risk participants’ shares increasing operator revenue by 0.69% demand-side gains by 3.56% and reducing generation-side losses by 1.32%. Environmental factors show measurable yet statistically insignificant impacts. The framework meets stakeholders’ satisfaction and minimizes deviation from reference allocations.

During the critical period of energy transition the collaborative optimization of the electricity-hydrogentransportation coupling system is of vital importance for achieving efficient energy utilization and sustainable development.This paper proposes a collaborative operation mechanism of Distributed Robust Optimization (DRO) considering carbon emissions. Firstly a Stackelberg game dynamic pricing strategy is constructed for the integrated energy station (IES) and the electricity-hydrogen hybrid charging station (HRS) where the upper-level IES optimizes the electricity price setting strategy and the lower-level HRS dynamically adjusts the electricity purchase-hydrogen production plan. Secondly the Wasserstein distance is used to describe the uncertainties of hydrogen vehicle loads and wind-solar power generation and a bisection algorithm-column constraint generation (BA-C&CG) hybrid algorithm is designed to solve the model. Finally the numerical example verification shows that the daily operation cost of HRS under the proposed mechanism is as low as 1108.53 EUR which is 10.58 % and 7.38 % lower than that of the commonly used stochastic optimization (SO) and robust optimization (RO) respectively. The variance analysis (F = 536.05P < 0.001) confirms that the cost advantage is statistically significant. In terms of carbon emission reduction effect the DRO-Stackelberg game model has the lowest daily carbon cost (6.98EUR). This mechanism effectively balances the economic and robustness of the system and the single dispatch calculation time is only 112.09 s meeting the real-time operation requirements of engineering. It provides technical support for the low-carbon collaborative operation of the electricity-hydrogen-transportation coupling system.

With the IMO’s 2050 decarbonization target hydrogen is a key zero-carbon fuel for shipping but the lack of systematic risk assessment methods for hydrogen-powered marine propulsion systems (under harsh marine conditions) hinders its large-scale application. To address this gap this study proposes an integrated risk evaluation framework by fusing Failure Mode Effects and Criticality Analysis (FMECA) with the Fuzzy Analytic Hierarchy Process (FAHP)—resolving the limitation of traditional single evaluation tools and adapting to the dynamic complexity of marine environments. Scientific findings from this framework confirm that hydrogen leakage high-pressure storage tank valve leakage and inverter overload are the three most critical failure modes with hydrogen leakage being the primary risk source due to its high severity and detection difficulty. Further hazard matrix analysis reveals two key risk mechanisms: one type of failure (e.g. insufficient hydrogen concentration) features “high severity but low detectability” requiring real-time monitoring; the other (e.g. distribution board tripping) shows “high frequency but controllable impact” calling for optimized operations. This classification provides a theoretical basis for precise risk prevention. Targeted improvement measures (e.g. dual-sealed valves redundant cooling circuits AI-based regulation) are proposed and quantitatively validated reducing the system’s overall risk value from 4.8 (moderate risk) to 1.8 (low risk). This study’s core contribution lies in developing a universally applicable scientific framework for marine hydrogen propulsion system risk assessment. It not only fills the methodological gap in traditional evaluations but also provides a theoretical basis for the safe promotion of hydrogen shipping supporting the scientific realization of the IMO’s decarbonization goal.