Publications

This study proposed a deep reinforcement learning-based energy management strategy (DRL-EMS) that can be applied to a hybrid electric ship propulsion system (HSPS) integrating liquid hydrogen (LH2 ) fuel gas supply system (FGSS) proton-exchange membrane fuel cell (PEMFC) and lithium-ion battery systems. This study analyzed the optimized performance of the DRL-EMS and the operational strategy of the LH2 -HSPS. To train the proposed DRL-EMS a reward function was defined based on fuel consumption and degradation of power sources during operation. Fuel consumption for ship propulsion was estimated with the power for balance of plant (BOP) of the LH2 FGSS and PEMFC system. DRL-EMS demonstrated superior global and real-time optimality compared to benchmark algorithms namely dynamic programming (DP) and sequential quadratic programming (SQP)-based EMS. For various operation cases not used in training DRL-EMS resulted in 0.7% to 9.2% higher operating expenditure compared to DP-EMS. Additionally DRL-EMS was trained to operate 60% of the total operation time in the maximum efficiency range of the PEMFC system. Different hydrogen fuel costs did not affect the optimized operational strategy although the operating expenditure (OPEX) was dependent on the hydrogen fuel cost. Different capacities of the battery system did not considerably change the OPEX.

As Sweden takes its first steps towards a hydrogen-based economy a strategic approach to infrastructure development for both storage and delivery becomes necessary. Although compressed hydrogen is currently the state-of-the-art its low volumetric density and associated high capital costs pose challenges to widespread societal deployment of hydrogen. In order to avoid technological lock-in alternatives storage technologies including chemical hydrides e.g. methanol ammonia methane and LOHC must also be explored. These alternatives offer higher hydrogen densities safer handling and compatibility with existing infrastructure. However each hydride has unique chemical and physical properties requires distinct feedstock and conversion processes and interacts with the energy system in different ways all of which influences their suitability for various applications. Therefore a comprehensive evaluation of these alternative hydrogen storage technologies as carried out in this article is vital to allow for informed investment decisions and pave the way towards a successful and sustainable hydrogen economy.

To reduce carbon emissions generation of electricity from combustion systems is being replaced by renewable resources. However the most abundant renewable sources – solar and wind – are not dispatchable vary diurnally and are subject to intermittency and produce electricity at times in excess of demand (excess production). To manage this variability and capture the excess renewable energy energy storage technologies are being developed and deployed such as battery energy storage (BES) hydrogen production with electrolyzers (ELY) paired with hydrogen energy storage (HES) and fuel cells (FCs) and renewable natural gas (RNG) production. While BES may be better suited for short duration storage hydrogen is suited for long duration storage and RNG can decarbonize the natural gas system. California Senate Bill 100 (SB100) sets a goal that all retail electricity sold in the State must be sourced from renewable and zero-carbon resources by 2045 raising the questions of which set of technologies and in what proportion are required to meet the 2045 target in the required timeframe as well as the role of the natural gas infrastructure if any. To address these questions this study combines electric grid dispatch modeling and optimization to identify the energy storage and dispatchable technologies in 5-year increments from 2030 to 2045 required to transition from a 60% renewable electric grid in 2035 to a 100% renewable electric grid in 2045. The results show that by utilizing the established natural gas system to store and transmit hydrogen and RNG the deployment of battery energy storage is dramatically reduced. The required capacity for BES in 2045 for example is 40 times lower by leveraging the natural gas infrastructure with a concomitant reduction in cost and associated challenges to transform the electric grid.

The increasing demand for sustainable air mobility has led to the development of innovative aircraft designs necessitating a balance between environmental responsibility and profitability. However despite technological advancements there is still limited understanding of the maintenance implications for hydrogen systems in aviation. The aim of this study is to estimate the maintenance costs of replacing the hydrogen storage system in an aircraft as part of its life cycle costs. To achieve this we compared conventional and hydrogenpowered aircraft. As there is insufficient data for new aircraft concepts typical probabilistic methods are not applicable. However by combining global sensitivity analysis with Dempster–Shafer Theory of Evidence and discrete event simulation it is possible to identify key uncertainties that impact maintenance costs and economic efficiency. This innovative framework offers an early estimate of maintenance costs under uncertainty enhancing understanding and assisting in decision-making when integrating hydrogen storage systems and new aviation technologies.

This research conducted a probabilistic life-cycle assessment (pLCA) into the greenhouse gas (GHG) emissions performance of nine combinations of truck size and powertrain technology for a recent past and a future (largely decarbonised) situation in Australia. This study finds that the relative and absolute life-cycle GHG emissions performance strongly depends on the vehicle class powertrain and year of assessment. Life-cycle emission factor distributions vary substantially in their magnitude range and shape. Diesel trucks had lower life-cycle GHG emissions in 2019 than electric trucks (battery hydrogen fuel cell) mainly due to the high carbon-emission intensity of the Australian electricity grid (mainly coal) and hydrogen production (mainly through steam–methane reforming). The picture is however very different for a more decarbonised situation where battery electric trucks in particular provide deep reductions (about 75–85%) in life-cycle GHG emissions. Fuel-cell electric (hydrogen) trucks also provide substantial reductions (about 50–70%) but not as deep as those for battery electric trucks. Moreover hydrogen trucks exhibit the largest uncertainty in emissions performance which reflects the uncertainty and general lack of information for this technology. They therefore carry an elevated risk of not achieving the expected emission reductions. Battery electric trucks show the smallest (absolute) uncertainty which suggests that these trucks are expected to deliver the deepest and most robust emission reductions. Operational emissions (on-road driving and vehicle maintenance combined) dominate life-cycle emissions for all vehicle classes. Vehicle manufacturing and upstream emissions make a relatively small contribution to life-cycle emissions from diesel trucks (

Hydrogen is the most promising alternative fuel in the field of engines. Exhaust heat assisted methanol dissociation is an attractive approach for generating hydrogen. In this work simulations are conducted on a compression ignition engine fueled with different proportions of diesel-dissociated methanol gas (DMG) blends at intermediate engine speed full load and 0% EGR ratio. The results reveal that the indicated thermal efficiency and indicated mean effective pressure are greatly enhanced combustion efficiency is increased and regular emissions of CO HC and soot are reduced while NOx emissions are reduced with increased DMG substitution. In addition a simulation is conducted at an intermediate engine speed full load 15% DMG substitution ratio and varying EGR ratios of 0–20%. The results indicate that the dual-fuel engine outperforms the original engine with respect to power fuel economy and regular emissions once an optimal EGR rate is adopted.

In the context of the German Energiewende the current government intends to install six million heat pumps by 2030. Replacing gas heating by power has significant implications on the infrastructure. One of the biggest advantages of using gas is the existing storage portfolio. It has not been clarified yet how power demand should be structured on an annual level—especially since power storage is already a problem and solar power is widely promoted to fuel heat pumps despite having an inverse profile. In this article three different solutions namely hydrogen batteries and carbon capture and storage are discussed with respect to resources energy and financial demand. It shows that relying solely on batteries or hydrogen is not solving the structuring problem. A combination of all existing technologies (including fossil fuels) is required to structure the newly generated electricity demand

With the current trends of wind energy already playing a major part in the Scottish energy supply the capacity of wind farms is predicted to grow exponentially and reach further depths offshore. However a key challenge that presents itself is the integration of large producing assets into the current UK grid. One potential solution to this is green hydrogen production which is being heavily researched in industry with many concepts being investigated for large-scale purposes. However the operations and maintenance (O&M) costs and availability of green hydrogen systems need to be quantified to ensure economical and technical viability which is sparse in the available literature. The study presented in this paper investigated the availability and O&M costs of coupled wind–hydrogen systems by attempting to quantify the failure rates repair times repair costs and number of technicians required for key green hydrogen components. This study also utilised an O&M model created by the University of Strathclyde which uses Monte Carlo Markov chain simulations to produce the O&M outputs. A number of assumptions were made throughout the study in relation to the O&M model inputs and the baseline availability for the coupled wind–hydrogen system was 85.24%. Whilst the wind turbine still contributed a major part to the downtime seen in the simulations the combined hydrogen system also contributed a significant amount a total of 37% which could have been due to the technology readiness levels of some the components included in the hydrogen system.

Green hydrogen is expected to play a crucial role in the future energy landscape particularly in the pursuit of deep decarbonisation strategies within hard-to-abate sectors such as the chemical and steel industries and heavy-duty transport. However competitive production costs are vital to unlock the full potential of green hydrogen. In the case of green hydrogen produced via water electrolysis powered by fluctuating renewable energy sources the design of the plant plays a pivotal role in achieving market-competitive production costs. The present work investigates the optimal design of power-to-hydrogen systems powered by renewable sources (solar and wind energy). A detailed model of a power-to-hydrogen system is developed: an energy simulation framework coupled with an economic assessment provides the hydrogen production cost as a function of the component sizes. By spanning a wide range of size ratios namely the ratio between the size of the renewable generator and the size of the electrolyser the cost-optimal design point (minimum hydrogen production cost) is identified. This investigation is carried out for three plant configurations: solar-only wind-only and hybrid. The objective is to extend beyond the analysis of a specific case study and provide broadly applicable considerations for the optimal design of green hydrogen production systems. In particular the rationale behind the cost-optimal size ratio is unveiled and discussed through energy (utilisation factors) and economic (hydrogen production cost) indicators. A sensitivity analysis on investment costs for the power-to-hydrogen technologies is also conducted to explore various technological learning paths from today to 2050. The optimal size ratio is found to be a trade-off between the utilisation factors of the electrolyser and the renewable generator which exhibit opposite trends. Moreover the costs of the power-to-hydrogen technologies are a key factor in determining the optimal size ratio: depending on these costs the optimal solution tends to improve one of the two utilization factors at the expense of the other. Finally the optimal size ratio is foreseen to decrease in the upcoming years primarily due to the reduction in the investment cost of the electrolyser.

In this study we examined the effect of CO2 injection into deep saline aquifers considering impurities present in blue hydrogen production. A fluid model was designed for reservoir conditions with impurity concentrations of 3.5 and 20%. The results showed that methane caused density decreases of 95.16 and 76.16% at 3.5 and 20% respectively whereas H2S caused decreases of 99.56 and 98.77% respectively. Viscosity decreased from 0.045 to 0.037 cp with increasing methane content up to 20%; however H2S did not affect the viscosity. Notably CO2 with H2S impacted these properties less than methane. Our simulation model was based on the Gorae-V properties and simulated injections for 10 years followed by 100 years of monitoring. Compared with the pure CO2 injection methane reached its maximum pressure after eight years and eleven months at 3.5% and eight years at 20% whereas H2S reached maximum pressure after nine years and two months and nine years and six months respectively. These timings affected the amount of CO2 injected. With methane as an impurity injection efficiency decreased up to 73.16% whereas with H2S it decreased up to 81.99% with increasing impurity concentration. The efficiency of CO2 storage in the dissolution and residual traps was analyzed to examine the impact of impurities. The residual trap efficiency consistently decreased with methane but increased with H2S. At 20% concentration the methane trap exhibited higher efficiency at the end of injection; however H2S had a higher efficiency at the monitoring endpoint. In carbon capture and storage projects methane impurities require removal whereas H2S may not necessitate desulfurization due to its minimal impact on CO2 storage efficiency. Thus the application of carbon capture and storage (CCS) to CO2 emissions containing H2S as an impurity may enable economically viable operations by reducing additional costs.