Applications & Pathways

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.

Liquid hydrogen (LH2) is a promising candidate for zero emission aviation but its cryogenic properties make the refuelling process fundamentally different from that of conventional jet fuels. Although previous studies have addressed LH2 storage and system integration detailed modelling of the refuelling process remains limited. This paper presents the first part of a two-part study focused on simulation of the refuelling process for an LH2-powered commercial aircraft. An existing tank model is substantially modified to more accurately capture relevant physical phenomena including heat transfer and droplet dynamics during top-fill spray injection. Newly available experimental data on LH2 no-vent filling enables direct validation of the model under conditions that match the experimental setup. A sensitivity analysis identifies the most influential parameters that affect model precision including loss coefficient droplet diameter radiative heat ingress and vent-closing pressure. The validated model forms the basis for Part 2 of this study in which it is applied to a representative LH2-powered commercial aircraft to simulate refuelling times quantify venting losses and assess the impact of key operational settings. These results support the design of efficient LH2 refuelling systems for future aircraft and airport infrastructure.

Hydrogen’s increasing potential as an alternative fuel for heavy-duty transport has led to the conversion of conventional diesel compression-ignition engines to spark-ignition hydrogen operation. Hydrogen’s broad flammability range enables leaner operation achieving both higher engine efficiency and near-zero emissions. In particular direct injection hydrogen combustion improves volumetric efficiency and reduces problems including pre-ignition and knock related to hydrogen port-fuel injection. In the present work we performed an optical investigation of direct injection (DI) hydrogen combustion under leaner mixture conditions. The study was conducted using a heavy-duty optical diesel engine modified for spark-ignition operation. Bottom-view natural flame luminosity and OH-PLIF imaging were conducted along with in-cylinder pressure measurements. Experiments were conducted at three air-excess ratios (3 3.4 and 3.8) with spark timings (ST) varied from − 15 ◦CA aTDC to − 30 ◦CA aTDC. Hydrogen injection ended at − 30 ◦CA aTDC with the start of injection adjusted accordingly to achieve the desired lambda conditions. The maximum IMEPg corresponded to the lowest COV of the IMEPg indicating optimal spark timing for lean DI hydrogen combustion. The optimized spark timing for λ = 3 λ = 3.4 and λ = 3.8 were occurred at − 25 ◦CA aTDC − 25 ◦CA aTDC and − 30 ◦CA aTDC respectively. The corresponding COV of IMEPg values were below 5 % indicating stable combustion. The flame kernel first initiates at the spark plug and then propagates toward the piston’s outer boundary however the flame propagation does not remain as a continuous front unlike port-fuel injected hydrogen combustion. The effect of fuel stratification is evident in combustion luminosity and OH-PLIF images showing pockets of varying intensity within the combustion chamber. Natural flame luminosity images reveal incomplete flame coverage and asymmetric combustion emphasizing the need for metal engine experiments to further quantify the unburned hydrogen and associated combustion losses.

Fuel cell electric vehicles (FCEVs) are zero-emission but face cost and power density challenges. To mitigate these limitations a novel 3D-ordered nano-structured self-supporting membrane electrode assembly (MEA) has been developed. This paper investigates the optimal component sizing of the battery and fuel cell in FCEVs equipped with 3D-ordered MEAs integrating the energy management. To explore the trade-offs between component cost operational cost and fuel cell degradation the sizing and energy management problem is formulated into a multi-objective optimisation problem. A Pareto frontier (PF) study is conducted using the decomposed multi-objective evolutionary algorithm (MOEA/D) for a more diverse distribution of feasible solutions. The modular design of fuel cells is derived from a scaled and stressed experiment. After executing MOEA/D across the three aggressive driving cycles power source configurations are selected from the corresponding PFs based on objective trade-offs ensuring robustness of the overall system. The optimisation performance of the MOEA/D is compared with that of the multi-objective Particle Swarm Optimisation. In addition the selected powertrain configurations are evaluated and compared through standard and realworld driving cycles in a simulation environment. This paper also performs a sensitivity analysis to reveal the influence of diverse component unit costs and hydrogen price. The results indicate that the mediumsized configuration consisting of a 63.31 kW fuel cell stack and a 52.15 kWh battery pack delivers the best overall performance. It achieves a 26.71% reduction in component cost and up to 12.76% savings in hydrogen consumption across various driving conditions. These findings provide valuable insights into the design and optimisation of fuel cell systems for FCEVs.

Coastal regions in Cameroon including Douala Kribi Campo Dibamba and Limbe faced persistent electricity challenges driven by grid instability growing demand and dependence on fossil fuels. Solar resource availability was high but intermittent whereas tidal energy was predictable and energy-dense yet underused. This pilot delivers the first Cameroonian assessment of an off-grid tidal/PV/electrolyzer/hydrogen-storage/fuel-cell architecture explicitly co-optimizing electricity service and green hydrogen production and evaluating performance with a tri-metric economic lens (net present cost levelized cost of electricity and the levelized cost of hydrogen). The system was optimized to minimize net present cost (NPC) levelized cost of electricity (LCOE) levelized cost of hydrogen (LCOH) and three tidal-flow scenarios were analyzed to represent hydrokinetic variability. The design served households small businesses fishing activities schools and health facilities with a baseline demand of 389.50 kWh/day; surplus renewable power drove the electrolyzer to produce hydrogen for later reconversion in the fuel cell. Under the first scenario (1.25 m/s average speed) the optimal mix comprised 137 PV modules (600 W each) a 100 kW fuel cell six 40 kW tidal turbines six 10 kW electrolyzers a 19.5 kW converter and 41 hydrogen tanks (40 L each) yielding an NPC of US$ 2.16 million an LCOE of US$ 0.782/kWh and a LCOH of US$ 19.2/kg of hydrogen. The second scenario (1.47 m/s) required only 12 PV modules one electrolyzer and an 11.3 kW converter lowering costs to an NPC of US$ 1.52 million an LCOE of US$ 0.553/ kWh and a LCOH of US$ 15.4/kg of hydrogen. In the third scenario (1.61 m/s) the configuration shifted to 298 PV modules three tidal turbines eight electrolyzers and a 39.6 kW converter resulting in the highest NPC (US$ 2.47 million) and LCOE (US$ 0.901/kWh) with a LCOH of US$ 18.8/kg of hydrogen. The study also contributes a transparent component-wise employment indicator linking installed capacities/energies to jobs; deployment is expected to create about seven local jobs during installation and early operation tidal turbines (3) solar panels (1) electrolyzers (1) hydrogen tanks (1) and fuel cell (1) with additional minor operation and maintenance positions thereafter. Social analysis indicated improved energy access support for local livelihoods and job creation; environmental results confirmed clean operation with limited marine disturbance. A sensitivity study varying capital and replacement-cost multipliers showed robust performance across economic conditions. Taken together these contributions provide a decision-ready blueprint for coastal communities: a first-of-its-kind Cameroonian hybrid that quantifies both electricity and hydrogen costs (including feasible LCOH) and demonstrates socio-economic co-benefits offering a cost-effective pathway to strengthen energy security foster local development and reduce environmental impact.

This study presents an experimental investigation of a direct injection ammonia-fuelled engine using hydrogen pre-chamber jet ignition. All tests have been conducted in an optically accessible combustion chamber that is installed in the head of a single-cylinder engine. The effect of ammonia injection timing on ignition and combustion characteristics was investigated with the timing varied from 165 CAD BTDC to 40 CAD BTDC. The experiments were conducted with a fixed spark timing of 14 CAD BTDC while ammonia injection duration was adjusted to maintain a main chamber global equivalence ratio of 0.6. Two pre-chamber nozzle configurations a single-hole and a multi-hole were tested. The results show that the later NH3 injection timing (40 CAD BTDC) significantly improved combustion with a peak in-cylinder pressure of 80 bar measured compared to a peak in-cylinder pressure of 50 bar with earlier injection (165 CAD BTDC). This study indicates the importance of optimising ammonia injection timing in order to enhance combustion stability and efficiency. The hydrogen pre-chamber jet ignition combined with a late ammonia injection is a promising approach for addressing the combustion challenges of ammonia as a zero-carbon fuel for maritime applications.