Australia

To combat global temperature rise we need affordable clean and renewable energy that does not add carbon to the atmosphere. Hydrogen is a promising option because it can be used as a carbon-free energy source. However storing and transporting pure hydrogen in liquid or gaseous forms is challenging. To overcome the limitations associated with conventional compressed and liquefied hydrogen or physio-chemical adsorbents for bulk storage and transport hydrogen can be attached to other molecules known as hydrogen carriers. Circular carriers which involve the production of CO2 or nitrogen during the hydrogen recovery process include substances such as methanol ammonia or synthetic natural gas. These carriers possess higher gravimetric and volumetric hydrogen densities (i.e. 12.5 wt% and 11.88 MJ/L for methanol) than cyclic carriers (i.e. 6.1 wt% and 5.66 MJ/L for methylcyclohexane (MCH)) which produce cyclic organic chemicals during dehydrogenation. This makes circular carriers particularly appealing for the Australian energy export market. Furthermore the production-decomposition cycle of circular carriers can be made carbon-neutral if they are derived from renewable H2 sources and combined with atmospheric or biomass-based CO2 or nitrogen. The key parameters are investigated in this study focusing on circular hydrogen carriers relevant to Australia. The parameters are ranked from 0 (worst) to 10 (best) depending on the bandwidth of the parameter in this review. Methanol shows great potential as a cost-effective solution for long-distance transport of renewable energy being a liquid at standard conditions with a boiling point of 64.7 °C. Methane is also an important hydrogen carrier due to the availability of natural gas infrastructure and its role as a significant export product for Australia.

Hydrogen shaft injection into blast furnaces (BFs) has a large potential to eliminate carbon dioxide emissions yet the temporal evolution of thermal and chemical states following shaft-injected hydrogen utilisation has not been reported in the open literature. In this research a recently developed transient-state multifluid BF model is applied to elucidate the temporal evolution of in-furnace phenomena. Besides a domain-average method is adopted to analyse the extensive simulation data to determine the time required to attain the next steady-like state. The results show that the evolution of thermal and chemical conditions varies across different regions with distinct characteristics near the furnace wall. The shifts in iron oxide reduction behaviour are completed within 10 to 20 h after the new operation and the transition time points to the next steady-like states of thermal and chemical conditions are different. As the hydrogen flow rate increases the average transition time decreases. However 2 to 4 days are required for the studied BF to reach a new steady-like state in the considered scenarios. The model offers a cost-effective approach to investigating the transient smelting characteristics of an ironmaking BF with hydrogen injection.

This study explores the generation of natural hydrogen through the serpentinization of onshore ultramafic rocks highlighting its potential as a clean energy resource. By investigating critical factors such as mineral composition temperature and pressure the research develops an empirical model using multiple regression analysis to predict hydrogen generation rates under varying geological conditions. A novel five-stage volumetric calculation methodology is introduced to estimate hydrogen production from ultramafic rock bodies. The application of this framework to the Giles Complex an ultramafic-mafic intrusion in Australia suggests a hydrogen generation potential of approximately 2.24 × 1013 kg of hydrogen through partial serpentinization. This estimate is based on the assumed mineral composition depth and temperature conditions within the intrusion which influence the extent of serpentinization reactions. The findings demonstrate the significant potential of ultramafic complexes for natural hydrogen production and provide a foundation for advancing natural hydrogen exploration refining predictive models and supporting sustainable energy development.

This study explores the design and feasibility of a novel fuel cell-powered wind farm for residential electricity hydrogen/oxygen production and cooling/heating via a compression chiller. Wind turbine energy powers Proton Exchange Membrane (PEM) electrolyzers and a compression chiller unit. The proposed system was modeled using EES thermodynamic software and its economic viability was assessed. A case study across seven Italian regions with varying wind potentials evaluated the system’s feasibility in diverse weather conditions. Multi-objective optimization using Response Surface Methodology (RSM) determined the number of wind turbines as optimum number of electrolyzers & fuel cell units. Optimization results indicated that 37 wind turbines 1 fuel cell unit and 2 electrolyzer units yielded an exergy efficiency of 27.98 % and a cost rate of 619.9 $/h. TOPSIS analysis suggested 32 wind turbines 2 electrolyzers and 2 reverse osmosis units as an alternative configuration. Further twelve different scenarios were examined to enhance the distribution of wind farmgenerated electricity among the grid electrolyzers and reverse osmosis systems. revealing that directing 25 % to reverse osmosis 20 % to electrolyzers and 55 % to grid sales was optimal. Performance analysis across seven Italian cities (Turin Bologna Florence Palermo Genoa Milan and Rome) identified Genoa Palermo and Bologna as the most suitable locations due to favorable wind conditions. Implementing the system in Genoa the optimal site could produce 28435 MWh of electricity annually prevent 5801 tons of CO2 emissions (equivalent to 139218 $). Moreover selling this clean electricity to the grid could meet the annual clean electricity needs of approximately 5770 people in Italy

Australia has set a new climate target of reducing emissions by 62–70% below 2005 levels by 2035 with sustainable aviation fuel (SAF) central to achieving this goal. This review critically examines techno-economic analysis (TEA) and life cycle assessment (LCA) of Powerto-Liquid (PtL) electrofuels (e-fuels) which synthesize atmospheric CO2 and renewable hydrogen (H2) via Fischer-Tropsch (FT) synthesis. Present PtL pathways require ~0.8 kg of H2 and 3.1 kg of CO2 per kg SAF with ~75% kerosene yield. While third-generation feedstocks could cut greenhouse gas emissions by up to 93% (as low as 8 gCO2e/MJ) real world reductions have been limited (~1.5%) due to variability in technology rollout and feedstock variability. Integrated TEA–LCA studies demonstrate up to 20% energy efficiency improvements and 40% cost reductions but economic viability demands costs below $3/kg. In Australia abundant solar resources vast transport networks and supportive policy frameworks present both opportunities and challenges. This review provides the first comprehensive assessment of PtL-FT SAF for Australian conditions highlighting that large-scale development will require technological advancement feedstock development infrastructure investment and coordinated policy support.

Replacing the energy density and convenience of diesel fuel for all forms of fossil fuel-powered trains presents significant challenges. Unlike the traditional evolutions of rail which has largely self-optimised to different fuels and cost structures over 150 years the challenges now present with a timeline of just a few decades. Fortunately unlike the mid-1800s simulation and modelling tools are now quite advanced and a full range of scenarios of operations and train trips can be simulated before new traction systems are designed. Full trip simulations of large heavy haul trains or high speed passenger trains are routinely completed controlled by emulations of human drivers or automated control systems providing controls of the “virtual train”. Recent developments in digital twins can be used to develop flexible and dynamic models of passenger and freight rail systems to support the new complexities of decarbonisation efforts. Interactions between many different traction components and the train multibody system can be considered as a system of systems. Adopting this multi-modelling paradigm enables the secure and integrated interfacing of diverse models. This paper demonstrates the application of the multi-modelling approach to develop digital twins for rail decarbonisation traction and it presents physics-based multi-models that include key components required for studying rail decarbonisation problems. Specifically the challenge of evaluating zero-emission options is addressed by adding further layers of modelling to the existing fully detailed multibody dynamics simulations. The additional layers detail control options energy storage the alternate traction system components and energy management systems. These traction system components may include both electrical system and inertia dynamics models to accurately represent the driveline and control systems. This paper presents case study examples of full trip scenarios of both long haul freight trains and higher speed passenger trains. These results demonstrate the many complex scenarios that are difficult to anticipate. Flowing on from this risks can be assessed and practical designs of zero-emission systems can be proposed along with the required recharging or refuelling systems.

The experimental performance of an autothermal hydrogen release unit comprising a perhydro benzyltoluene (H12-BT) dehydrogenation chamber and a catalytic hydrogen combustion (CHC) chamber in thermal contact is discussed. In detail the applied set-up comprised a multi-tubular CHC heating based on seven parallel tubes with the reactor shell containing a commercial dehydrogenation catalyst. In this way the CHC heated the endothermal LOHC dehydrogenation using a part of the hydrogen generated in the dehydrogenation. The proposed heating concept for autothermal LOHC dehydrogenation offers several advantages over state-of-the-art heating concepts including minimized space consumption high efficiency and zero NOx emissions. During performance tests the process reached a minimum hydrogen combustion fraction of 37 % while the minimum heat requirement for the dehydrogenation reaction for industrial scale plants is 33 %. The reactor orientation (vertical vs horizontal) and the flow configuration (counter-current vs. co-current) showed very little influence on the performance demonstrating the robustness of the proposed reactor design.

Green hydrogen has become a core element of Europe’s energy transition to assist in lowering carbon emissions. However the transition to green hydrogen faces challenges including the cost of production availability of renewable energy sources public opposition and the need for supportive government policies and financial initiatives. While there are other alternatives for producing low-carbon hydrogen for example blue hydrogen German funding favours projects that involve hydrogen production via electrolysis. Beyond climate goals it is anticipated that a green hydrogen industry will create economic benefits and a wide-range of collaborative opportunities with key international partnerships increasing energy security if done appropriately. Germany a leader in green hydrogen technology will need to rely on imports to meet long-term demand due to limited renewable energy capacity. Despite the current obstacles to transitioning to green hydrogen it is felt that ultimately the benefits of this industry and reducing emissions will outweigh the associated costs of production. This study analyses the hydrogen transition in Germany by interviewing 37 European experts guided by the research question: What are the key perceived barriers and opportunities influencing the successful adoption and integration of hydrogen technologies in Germany’s hydrogen transition?

The global energy sector is aiming to substantially reduce CO2 emissions to meet the UN climate goals. Among the proposed strategies underground storage solutions such as radioactive disposal CO2 NH3 and underground H2 storage (UHS) have emerged as promising options for mitigating anthropogenic emissions. These approaches require rigorous research and development (R&D) often involving laboratory-scale experiments to establish their feasibility before being scaled up to pilot plant operations. Microorganisms which are ubiquitous in laboratory environments can significantly influence geochemical reactions under variable experimental conditions of porous media and a salt cavern. We have selected a consortium composed of Bacillus sp. Enterobacter sp. and Cronobacter sp. bacteria which are typically present in the laboratory environment. These microorganisms can contaminate the rock sample and develop experimental artifacts in UHS experiments. Hence it is pivotal to sterilize the rock prior to conduct experimental research related to effects of microorganisms in the porous media and the salt cavern for the investigation of UHS. This study investigated the efficacy of various disinfection and sterilization methods including ultraviolet irradiation autoclaving oven heating ethanol treatments and gamma irradiation in removing the microorganisms from silica sand. Additionally the consideration of their effects on mineral properties are reviewed. A total of 567 vials each filled with 9 mL of acid-producing bacteria (APB) media were used to test killing efficacy of the cleaning methods. We conducted serial dilutions up to 10−8 and repeated them three times to determine whether any deviation occurred. Our findings revealed that gamma irradiation and autoclaving were the most effective techniques for eradicating microbial contaminants achieving sterilization without significantly altering the mineral characteristics. These findings underscore the necessity of robust cleaning protocols in hydrogeochemical research to ensure reliable reproducible data particularly in future studies where microbial contamination could induce artifacts in laboratory research.

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.