Applications & Pathways

This study expresses energy scheduling in intelligent distribution grid with renewable resources charging stations and hydrogen stations for electric vehicles and integrated energy systems. In deterministic model objective function minimizes total operating energy losses and environmental costs of grid. Constraints are power flow equations network operating and voltage security limits operating model of renewable resources electric vehicle stations and integrated energy systems. Scheme includes uncertainties in load renewable resources charging and hydrogen stations and energy prices. Robust optimization uses to obtain an operation that is robust against the forecast error of the aforementioned uncertainties. Modeling electric vehicles station and aforementioned integrated energy systems considering economic operational and environmental objectives of network operator as objective function extracting a robust model of aforementioned uncertainties in order to extract a solution that is robust against the uncertainty prediction error and examining ability of energy management to improve voltage security of grid are among innovations of this paper. Numerical results obtained from various cases prove the aforementioned advantages and innovations. Energy management of resources charging and hydrogen stations and aforementioned integrated systems lead to scheme being robust against 35% of the prediction error of various uncertainties. In these conditions scheme has improved economic operational environmental and voltage security conditions by about 33.6% 7%- 37.4% 44.4% and 24.7% respectively compared to load flow studies. By applying optimal penalty price for energy losses and pollution pollution and energy losses in the network are reduced by about 45.15% and 34.1% respectively.

Decarbonising aquaculture support vessels is pivotal to reducing greenhouse gas (GHG) emissions across both the aquaculture and maritime sectors. This study evaluates the technical and economic feasibility of deploying hydrogen as a marine fuel for a 14.95 m net cleaning vessel (NCV) operating in Tasmania Australia. The analysis retains the vessel’s original layout and subdivision to enable a like-for-like comparison between conventional diesel and hydrogen-based systems. Two options are evaluated: (i) replacing both the main propulsion engines and auxiliary generator sets with hydrogen-based systems— either proton exchange membrane fuel cells (PEMFCs) or internal combustion engines (ICEs); and (ii) replacing only the diesel generator sets with hydrogen power systems. The assessment covers system sizing onboard hydrogen storage integration operational constraints lifecycle cost and GHG abatement. Option (i) is constrained by the sizes and weights of PEMFC systems and hydrogen-fuelled ICEs rendering full conversion unfeasible within current spatial and technological limits. Option (ii) is technically feasible: sixteen 700 bar cylinders (131.2 kg H2 total) meet one day of onboard power demand for net-cleaning operations with bunkering via swap-and-go skids at the berth. The annualised total cost of ownership for the PEMFC systems is 1.98 times that of diesel generator sets while enabling annual CO2 reductions of 433 t. The findings provide a practical decarbonisation pathway for small- to medium-sized service vessels in niche maritime sectors such as aquaculture while clarifying near-term trade-offs between cost and emissions.

Fuel-cell flying vehicles suffer from limited endurance while ammonia decomposed onboard to supply hydrogen offers a carbon-free high-density solution to extend flight missions. However the system’s performance is governed by a multi-scale coupling between propulsion and control systems. To this end this paper introduces a novel optimization paradigm termed physics-informed gradient-enhanced multi-objective optimization (PIGEMO) to simultaneously optimize the ammonia decomposition unit (ADU) catalyst composition powertrain sizing and flight control parameters. The PI-GEMO framework leverages a physics-informed neural network (PINN) as a differentiable surrogate model which is trained not only on sparse simulation data but also on the governing differential equations of the system. This enables the use of analytical gradient information extracted from the trained PINN via automatic differentiation to intelligently guide the evolutionary search process. A comprehensive case study on a flying vehicle demonstrates that the PIGEMO framework not only discovers a superior set of Pareto-optimal solutions compared to traditional methods but also critically ensures the physical plausibility of the results.

By integrating Renewable Energy Sources (RES) and storage devices Hybrid Energy Systems (HESs) represent a promising solution for decarbonizing isolated and remote communities. Proper sizing and management of systems comprising a variety of components requires however more advanced methods than conventional energy systems. This study proposes a novel Mixed Integer Linear Programming (MILP) framework for the simultaneous design of a grid-connected HES supported by renewable generators. Unlike the standard design approach based on parametric dispatch strategies this framework simultaneously optimizes the energy management of each system configuration under analysis. The novel approach is applied to size a combination of Li-Ion batteries an alkaline electrolyzer H2 tanks and a PEM fuel cell to maximize the NPV of a system including a wind turbine and a photovoltaic field. Managing thousands of variables at the same time the framework simultaneously optimizes how all components are used to fulfill the load and balance the input/export of power within a limited electrical network. Results show that the combination of BESS and H2 can provide for both the need for short- and long-term energy storage and that the MILP optimization can effectively allocate the energy flows and produce 558 k€ of revenues per year 15.5% of the initial investment cost of 3.6 M€. The investment cost of the system is recovered in six years and presents an NPV of 5.51 M€ after 20 years. Results from the proposed method are also compared to common approaches based on rule-based parametric dispatch strategies demonstrating the superiority of MILP for the design and management of complex HESs.

Air travel demand is rising rapidly and the aviation sector is relying on technology to decouple environmental impacts from its growth. Using Sweden as a case study we assessed the absolute environmental sustainability of medium-distance air travel in 2050 positioning the aviation sector's environmental impacts in relation to the planetary limits. We employed a novel framework that integrates prospective life cycle assessment and absolute environmental sustainability assessment methodologies. Our findings suggest that projected medium-distance air travel powered by e-kerosene or liquid hydrogen could have life cycle environmental impacts that overshoot global climate change and biodiversity loss thresholds by several orders of magnitude. Based on our case results for Sweden for aviation to develop within the planetary limits we recommend cross-sector collaboration to address environmental impacts from fossil-free energy supplies and the establishment of integrated targets that incorporate broader environmental issues. Given the unlikelihood of decoupling growth from environmental impacts policymakers and the aviation sector should consider concurrently supporting technological development and implementing measures to manage air travel demand.

The integration of electric vehicles (EVs) and fuel-cell electric vehicles (FCEVs) requires accessible and profitable facilities for fast charging. To promote fast-charging stations (FCSs) a systematic analysis that encompasses both planning and operation is required including the incorporation of multi-energy resources and uncertainty. This paper presents an optimization framework that addresses a joint strategy for the configuration and operation of an EV/FCEV fast-charging station (FCS) integrated with distributed energy resources (DERs) and hydrogen systems. The framework incorporates uncertainties related to solar photovoltaic (PV) generation and demand for EVs/FCEVs. The proposed joint strategy comprises a four-phase decision-making framework. Phase 1 involves modeling EV/FECE demand while Phase 2 focuses on determining an optimal long-term infrastructure configuration. Subsequently in Phase 3 the operator optimizes daily power scheduling to maximize profit. A real-time uncertainty update is then executed in Phase 4 upon the realization of uncertainty. The proposed optimization framework formulated as mixed-integer quadratic programming (MIQP) considers configuration investment operational maintenance and penalty costs for excessive grid power usage. A heuristic algorithm is proposed to solve this problem. It yields good results with significantly less computational complexity. A case study shows that under the most adverse conditions the proposed joint strategy increases the FCS owner’s profit by 3.32% compared with the deterministic benchmark.

In this study we investigate the dual-fuel operation of compression ignition engines using biodiesel at varying concentrations in combination with biogas with and without hydrogen enrichment. A response surface methodology based on a central composite experimental design was employed to optimize energy efficiency and minimize pollutant emissions. The partial substitution of diesel with gaseous fuel substantially reduces the specific fuel consumption achieving a maximum decrease of 21% compared with conventional diesel operation. Enriching biogas with hydrogen accounting for 13.3% of the total flow rate increases the thermal efficiency by 0.8% compensating for the low calorific value and reduced volumetric efficiency of biogas. Variations in biodiesel concentration exhibits a nonlinear effect yielding an additional average efficiency gain of 0.4%. Regarding emissions the addition of hydrogen to biogas contributes to an average reduction of 5% in carbon monoxide emissions compared to the standard dual-fuel operation. However dual-fuel operation leads to higher unburned hydrocarbon emissions relative to neat diesel; hydrogen enrichment mitigates this drawback by reducing hydrocarbon emissions by 4.1%. Although NOx emissions increase by an average of 26.6% with hydrogen addition dual-fuel strategies achieve NOx reductions of 11.5% (hydrogen-enriched mode) and 33.3% (pure biogas mode) relative to diesel-only operation. Furthermore the application of response surface methodology is robust and reliable with experimental validation showing errors of 0.55–8.66% and an overall uncertainty of 4.84%.

The transport sector is a major contributor to greenhouse gas emissions largely due to its dependence on fossil fuels. Electrifying transport through Battery Electric Vehicles (BEVs) and Hydrogen Fuel Cell Electric Vehicles (FCEVs) is widely recognized as a key pathway to reducing emissions. While both BEVs and FCEVs are zero-emission during operation they still require electricity to function. Sourcing this electricity from solar energy presents a promising opportunity for sustainable operation. The novelty of this work lies in exploring how solar energy can be effectively integrated into both BEV and FCEV systems. The paper examines the potential scope and infrastructure requirements of these vehicle types as well as innovative charging and refuelling strategies. For BEVs charging options include fixed charging stations battery swapping stations and wireless charging. In the context of solar integration photovoltaic (PV) systems can be mounted directly on the vehicle body or used to power charging stations. While current PV efficiency and reliability are insufficient to meet the full energy demand of BEVs they can provide valuable auxiliary power. For FCEVs solar energy can be utilized for hydrogen production enabling the concept of solar-powered FCEVs. Refuelling options include onsite and offsite hydrogen production facilities as well as mobile refuelling units. In both cases land requirements for PV installations are significant. Alternatives to ground-mounted PV such as floating PV or agrivoltaics (agriPV) should be considered to optimize land use. While solar-powered charging or refuelling stations are technically feasible complete reliance on solar power alone is not yet practical. A hybrid approach with grid connections energy storage or backup generation remains necessary to ensure consistent energy availability. For BEVs the cost of charging particularly for long-distance travel where rapid charging is required remains a barrier. For FCEVs challenges include the high cost of hydrogen production and the limited availability of refuelling infrastructure despite their advantage of fast refuelling times. Government policies and incentives are playing a critical role in overcoming these barriers fostering investment in infrastructure and accelerating the transition toward a cleaner transport sector. In summary integrating solar energy into BEV and FCEV infrastructure can advance sustainable mobility by reducing lifecycle emissions. While current PV efficiency storage and hydrogen production limitations require hybrid energy solutions ongoing technological improvements and supportive policies can enable broader adoption. A balanced renewable energy mix with solar as a key component will be essential for realizing truly sustainable zero-emission transport.

Against the dual backdrop of intensifying carbon emission constraints and the large-scale integration of renewable energy integrated electricity–hydrogen energy systems (EH-ESs) have emerged as a crucial technological pathway for decarbonising energy systems owing to their multi-energy complementarity and cross-scale regulation capabilities. This paper proposes an operational optimisation and carbon reduction capability assessment framework for EH-ESs focusing on revealing their operational response mechanisms and emission reduction potential under multi-disturbance conditions. A comprehensive model encompassing an electrolyser (EL) a fuel cell (FC) hydrogen storage tanks and battery energy storage was constructed. Three optimisation objectives—cost minimisation carbon emission minimisation and energy loss minimisation—were introduced to systematically characterise the trade-offs between economic viability environmental performance and energy efficiency. Case study validation demonstrates the proposed model’s strong adaptability and robustness across varying output and load conditions. EL and FC efficiencies and costs emerge as critical bottlenecks influencing system carbon emissions and overall expenditure. Further analysis reveals that direct hydrogen utilisation outperforms the ‘electricity–hydrogen–electricity’ cycle in carbon reduction providing data support and methodological foundations for low-carbon optimisation and widespread adoption of electricity–hydrogen systems.

Hydrogen is the key to decarbonising heavy-duty transport. Understanding the distribution of hydrogen demand is crucial for effective planning and development of infrastructure. However current data on future hydrogen demand is often coarse and aggregated limiting its utility for detailed analysis and decision-making. This study developed a spatial disaggregation approach to estimating hydrogen demand for heavy-duty trucks and mapping the spatial distribution of hydrogen demand across multiple scales in Australia. By integrating spatial datasets with economic factors market penetration rates and technical specifications of hydrogen fuel cell vehicles the approach disaggregates the projected demand into specific demand centres allowing for the mapping of regional hydrogen demand patterns and the identification of key centres of hydrogen demand based on heavy-duty truck traffic flow projections under different scenarios. This approach was applied to Australia and the findings offered valuable insights that can help policymakers and stakeholders plan and develop hydrogen infrastructure such as optimising hydrogen refuelling station locations and support the transition to a low-carbon heavy-duty transport sector.