Publications

This review critically examines hydrogen energy systems highlighting their capacity to transform the global energy framework and mitigate climate change. Hydrogen showcases a high energy density of 120 MJ/kg providing a robust alternative to fossil fuels. Adoption at scale could decrease global CO2 emissions by up to 830 million tonnes annually. Despite its potential the expansion of hydrogen technology is curtailed by the inefficiency of current electrolysis methods and high production costs. Presently electrolysis efficiencies range between 60 % and 80 % with hydrogen production costs around $5 per kilogram. Strategic advancements are necessary to reduce these costs below $2 per kilogram and push efficiencies above 80 %. Additionally hydrogen storage poses its own challenges requiring conditions of up to 700 bar or temperatures below −253 °C. These storage conditions necessitate the development of advanced materials and infrastructure improvements. The findings of this study emphasize the need for comprehensive strategic planning and interdisciplinary efforts to maximize hydrogen's role as a sustainable energy source. Enhancing the economic viability and market integration of hydrogen will depend critically on overcoming these technological and infrastructural challenges supported by robust regulatory frameworks. This comprehensive approach will ensure that hydrogen energy can significantly contribute to a sustainable and low-carbon future.

In order to reduce carbon emissions the effects of gas composition and initial turbulence on the premixed flame dynamics of hydrogen-blended natural gas were investigated. The results show that an increase in hydrogen content leads to earlier formation of flame wrinkles. When the equivalence ratio is 1 and hydrogen blending ratio is below 20% Tulip flames appear approximately 2.25 m away from the ignition point. When hydrogen blending ratio exceeds 20% Tulip flames appear approximately 1.3 m away from the ignition point and twisted Tulip flames appear approximately 2.5 m away from the ignition position. During the 0.05 m process of flame propagation downstream from ignition point flame propagation velocity increases by about 2 m/s for every 10% increase in hydrogen content. The increase in hydrogen content has the most significant impact on the flame propagation velocity during the ignition stage. The average flame propagation velocity increases with the increase of hydrogen blending ratio. The greater the initial turbulence the more obvious the stretching deformation of flame front structure. With the increase of wind speed the flame propagation velocity first increases and then decreases. At a wind speed of 3 m/s the flame propagation velocity reaches its maximum value.

Hydrogen (2 ) has a big role to play in energy transition to achieve net-zero carbon emissions by 2050. For 2 to compete with other fuels in the energy market more research is required to mitigate key issues like greenhouse gas (GHG) emissions safety and end-use costs. For these reasons a software-supported technical overview of 2 production storage transportation and utilisation is introduced. Drawbacks and mitigation approaches for 2 technologies were highlighted. The recommended areas include solar thermal or renewable-powered plasma systems for feedstock preheating and oxy-hydrogen combustion to meet operating temperatures and heat duties due to losses; integration of electrolysis of 2 into hydrocarbon reforming methods to replace air separation unit (ASU); use of renewable power sources for electrical units and the introduction of thermoelectric units to maximise the overall efficiency. Furthermore a battolyser system for small-scale energy storage; new synthetic hydrides with lower absorption and desorption energy; controlled parameters and steam addition to the combustor/cylinder and combustors with fitted heat exchangers to reduce emissions and improve the overall efficiency are also required. This work also provided detailed information on any of these systems implementations based on location factors and established a roadmap for 2 production and utilisation. The proposed 2 production technologies are hybrid pyrolysis-electrolysis and integrated AD-MEC and DR systems using renewable bioelectrochemical and low-carbon energy systems. Production and utilisation of synthetic natural gas (NG) using renewablepowered electrolysis of 2 oxy-fuel and direct air capture (DAC) is another proposed 2 energy system for a sustainable 2 economy. By providing these factors and information researchers can work towards pilot development and further efficiency enhancement.

In this study we employ an optimization model to optimally design a self-sufficient independent of any imports and exports hydrogen infrastructure for Austria by 2030. Our approach integrates key hydrogen technologies within a detailed spatial investment and operation model – coupled with a European scale electricity market model. We focus on optimizing diverse infrastructure componentsincluding trailers pipelines electrolyzers and storages to meet Austria's projected hydrogen demand. To accurately estimate this demand in hourly resolution we combine existing hydrogen strategies and projections to account for developments in various industrial sectors consider demand driven by the transport sector and integrate hydrogen demand arising from its use in gas-powered plants. Accounting for the inherent uncertainty linked to such projections we run the analysis for two complementary scenarios. Our approach addresses the challenges of integrating large quantities of renewable hydrogen into a future energy system by recognizing the critical role of domestic production in the early market stages. The main contribution of this work is to address the gap in optimizing hydrogen infrastructure for effective integration of domestic renewable hydrogen production in Austria by 2030 considering sector coupling potentials optimal electrolyzer placement and the design of local hydrogen networks.

Clean energy vehicles (CEVs) e.g. battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs) are being adopted gradually to substitute for internal combustion engine vehicles (ICEVs) around the world. The fueling infrastructure is one of the key drivers for the development of the CEV market. When the government develops funding policies to support the fueling infrastructure development for FCEVs and BEVs it has to assess the effectiveness of different policy options and identify the optimal policy combination which is very challenging in transportation research. In this paper we develop a system dynamics model to study the feedback mechanism between the fueling infrastructure funding policies and the medium- to long-term diffusion of FCEVs and BEVs and the competition between FCEVs and BEVs based on relevant policy and market data in Guangzhou China. The results of the modeling analysis are as follows. (1) Funding hydrogen refueling stations and public charging piles has positive implications for achieving the substitution of CEVs for ICEVs. (2) Adjusting the funding ratio of hydrogen refueling stations and public charging piles or increasing the funding budget and extending the funding cycle does not have a significant impact on the overall substitution of CEVs for ICEVs but only impacts the relative competitive advantage between FCEVs and BEVs. (3) An equal share of funding for hydrogen refueling stations and public charging piles would have better strategic value for future net-zero-emissions urban transportation. (4) Making a moderate-level full investment in hydrogen refueling stations coupled with hydrogen refueling subsidies can provide the ideal conditions for FCEV diffusion.

Hydrogen (H2 ) is positioned as a key solution to the decarbonization challenge in both the energy and transportation sectors. While hydrogen is a clean and versatile energy carrier it poses significant safety risks due to its wide flammability range and high detonation potential. Hydrogen leaks can occur throughout the hydrogen value chain including production storage transportation and utilization. Thus effective leak detection systems are essential for the safe handling storage and transportation of hydrogen. This review aims to survey relevant codes and standards governing hydrogen-leak detection and evaluate various sensing technologies based on their working principles and effectiveness. Our analysis highlights the strengths and limitations of the current detection technologies emphasizing the challenges in achieving sensitive and specific hydrogen detection. The results of this review provide critical insights into the existing technologies and regulatory frameworks informing future advancements in hydrogen safety protocols.

This paper investigates innovative solutions to enhance the performance and lifespan of standalone photovoltaic (PV)-based microgrids with a particular emphasis on off-grid communities. A major challenge in these systems is the limited lifespan of batteries. To overcome this issue researchers have created hybrid energy storage systems (HESS) along with advanced power management strategies. This study introduces innovative multi-level HESS approaches and a related energy management strategy designed to alleviate the charge/discharge stress on batteries. Comprehensive Matlab Simulink models of various HESS topologies within standalone PV microgrids are utilized to evaluate system performance under diverse weather conditions and load profiles for rural site. The findings reveal that the proposed HESS significantly extends battery life expectancy compared to existing solutions. Furthermore the paper presents a novel energy management strategy based on the Reduced Fractional Gradient Descent (RFGD) algorithm optimization tailored for hybrid systems that include photovoltaic fuel cell battery and supercapacitor components. This strategy aims to minimize hydrogen consumption of Fuel Cells (FCs) thereby supporting the production of green ammonia for local industrial use. The RFGD algorithm is selected for its minimal user-defined parameters and high convergence efficiency. The proposed method is compared with other algorithms such as the Lyrebird Optimization Algorithm (LOA) and Osprey Optimization Algorithm (OOA). The RFGD algorithm exhibits superior accuracy in optimizing energy management achieving a 15% reduction in hydrogen consumption. Its efficiency is evident from the reduced computational time compared to conventional algorithms. Although minor losses in computational resources were observed they were substantially lower than those associated with traditional optimization techniques. Overall the RFGD algorithm offers a robust and efficient solution for enhancing the performance of hybrid energy systems.

The derivation of an efficient operational strategy for storing intermittent renewable energies using a hybrid battery-hydrogen energy storage system is a difficult task. One approach for deriving an efficient operational strategy is using mathematical optimization in the context of model predictive control. However mathematical optimization derives an operational strategy based on a non-exact mathematical system representation for a specified prediction horizon to optimize a specified target. Thus the resulting operational strategies can vary depending on the optimization settings. This work focuses on evaluating potential improvements in the operational strategy for a hybrid batteryhydrogen energy storage system using mathematical optimization. To investigate the operation a simulation model of a hybrid energy storage system and a tailor-made mixed integer linear programming optimization model of this specific system are utilized in the context of a model predictive control framework. The resulting operational strategies for different settings of the model predictive control framework are compared to a rule-based controller to show the potential benefits of model predictive control compared to a conventional approach. Furthermore an in-depth analysis of different factors that impact the effectiveness of the model predictive controller is done. Therefore a sensitivity analysis of the effect of different electricity demands and resource sizes on the performance relative to a rule-based controller is conducted. The model predictive controller reduced the energy consumption by at least 3.9 % and up to 17.9% compared to a rule-based controller. Finally Pareto fronts for multi-objective optimizations with different prediction and control horizons are derived and compared to the results of a rule-based controller. A cost reduction of up to 47 % is achieved by a model predictive controller with a prediction horizon of 7 days and perfect foresight. Keywords: Model Predictive Control Optimization Mixed Integer Linear Programming Hybrid Battery-Hydrogen Energy Storage System

With the question of ‘can short messages be effective in increasing public support for a complex new technology (hydrogen)?‘ this study uses a representative national survey in Australia to analyze the differences and variations in subjective support for hydrogen in response to four differently framed short messages. The findings of this study show that short messages can increase social acceptance but the effects depend on how strongly the message is framed in terms of its alignment with either an economic or environmental values framework. Furthermore the effects depend on the social and cultural context of the receiver of the message.

This paper presents the application of an active energy management strategy to a hybrid system consisting of a proton exchange membrane fuel cell (PEMFC) battery and supercapacitor. The purpose of energy management is to control the battery and supercapacitor states of charge (SOCs) as well as minimizing hydrogen consumption. Energy management should be applied to hybrid systems created in this way to increase efficiency and control working conditions. In this study optimization of an existing model in the literature with different meta-heuristic methods was further examined and results similar to those in the literature were obtained. Ant lion optimizer (ALO) moth-flame optimization (MFO) dragonfly algorithm (DA) sine cosine algorithm (SCA) multi-verse optimizer (MVO) particle swarm optimization (PSO) and whale optimization algorithm (WOA) meta-heuristic algorithms were applied to control the flow of power between sources. The optimization methods were compared in terms of hydrogen consumption and calculation time. Simulation studies were conducted in Matlab/Simulink R2020b (academic license). The contribution of the study is that the optimization methods of ant lion algorithm moth-flame algorithm and sine cosine algorithm were applied to this system for the first time. It was concluded that the most effective method in terms of hydrogen consumption and computational burden was the sine cosine algorithm. In addition the sine cosine algorithm provided better results than similar meta-heuristic algorithms in the literature in terms of hydrogen consumption. At the same time meta-heuristic optimization algorithms and equivalent consumption minimization strategy (ECMS) and classical proportional integral (PI) control strategy were compared as a benchmark study as done in the literature and it was concluded that meta-heuristic algorithms were more effective in terms of hydrogen consumption and computational time.