Publications

Subsurface porous formations provide large capacities for underground hydrogen storage (UHS). Successful utilization of these porous reservoirs for UHS depends on accurate quantification of the hydrogen transport characteristics at continuum (macro) scale specially in contact with other reservoir fluids. Relative-permeability and capillary-pressure curves are among the macro-scale transport characteristics which play crucial roles in quantification of the storage capacity and efficiency. For a given rock sample these functions can be determined if pore-scale (micro-scale) surface properties specially contact angles are known. For hydrogen/brine/rock system these properties are yet to a large extent unknown. In this study we characterize the contact angles of hydrogen in contact with brine and Bentheimer and Berea sandstones at various pressure temperature and brine salinity using captive-bubble method. The experiments are conducted close to the in-situ conditions which resulted in water-wet intrinsic contact angles about 25 to 45 degrees. Moreover no meaningful correlation was found with changing tested parameters. We monitor the bubbles over time and report the average contact angles with their minimum and maximum variations. Given rock pore structures using the contact angles reported in this study one can define relative-permeability and capillary-pressure functions for reservoir-scale simulations and storage optimization.

Green hydrogen produced from surplus electricity during peak production can be injected into subsurface reservoirs and retrieved during high-demand periods. In this study X-ray tomography was employed to examine hysteresis resulting from repeated hydrogen injection and withdrawal. An unsteady state experiment was performed to evaluate the distribution of hydrogen and brine after drainage and imbibition cycles: images of the pore-space configuration of fluids were taken immediately once injection had stopped and after waiting for a period of 16 h with no flow. A Bentheimer sandstone sample with a length of 60 mm and diameter of 12.8 mm was used and hydrogen was injected at ambient temperature and a pore pressure of 1 MPa. The gas flow rate was decreased from 2 ml/min to 0.08 ml/min over three cycles of gas injection followed by water flooding while the brine injection rate was kept constant. The results showed the presence of capillary pressure hysteresis and hydrogen migration through Ostwald ripening due to the diffusion of gas dissolved in the brine. These phenomena were characterized through analysis of interfacial curvature area connectivity and pore occupancy. The hydrogen tended to reside in the larger pore spaces consistent with water-wet conditions. 16 h after flow had stopped the hydrogen aggregated into larger ganglia with a single large connected ganglion dominating the volume. Moreover the Euler characteristic decreased after 16 h indicating an improvement in connectivity. The work implies that Ostwald ripening – mass transport of dissolved gas – leads to less hysteresis and better connectivity than would be assumed ignoring this effect as done in assessments of hydrocarbon flow and trapping.

Underground hydrogen storage (UHS) in porous media is proposed to balance seasonal fluctuations between demand and supply in an emerging hydrogen economy. Despite increasing focus on the topic worldwide the understanding of hydrogen flow in porous media is still not adequate. In particular relative permeability hys teresis and its impact on the storage performance require detailed investigations due to the cyclic nature of H2 injection and withdrawal. We focus our analysis on reservoir simulation of an offshore aquifer setting where we use history matched relative permeability to study the effect of hysteresis and gas type on the storage efficiency. We find that omission of relative permeability hysteresis overestimates the annual working gas capacity by 34 % and the recovered hydrogen volume by 85 %. The UHS performance is similar to natural gas storage when using hysteretic hydrogen relative permeability. Nitrogen relative permeability can be used to model the UHS when hysteresis is ignored but at the cost of the accuracy of the bottom-hole pressure predictions. Our results advance the understanding of the UHS reservoir modeling approaches.

Implementation of the hydrogen economy for emission reduction will require storage facilitiesand underground hydrogen storage (UHS) in porous media offers a readily available large-scale option. Lack ofstudies on multiphase hydrogen flow in porous media is one of the several barriers for accurate predictions ofUHS. This paper reports for the first time measurements of hysteresis in hydrogen-water relative permeabilityin a sandstone core under shallow storage conditions. We use the steady state technique to measure primarydrainage imbibition and secondary drainage relative permeabilities and extend laboratory measurements withnumerical history matching and capillary pressure measurements to cover the whole mobile saturation range.We observe that gas and water relative permeabilities show strong hysteresis and nitrogen as substitute forhydrogen in laboratory assessments should be used with care. Our results serve as calibrated input to field scalenumerical modeling of hydrogen injection and withdrawal processes during porous media UHS.

We consider a profit-maximizing renewable energy producer operating in a rural area with limited electricity distribution capacity to the grid. While maximizing profits the energy producer is responsible for the electricity supply of a local community that aims to be self-sufficient. Energy storage is required to deal with the energy productions' uncertain and intermittent character. A promising new solution is to use strategic hydrogen reserves. This provides a long-term storage option to deal with seasonal mismatches in energy production and the local community's demand. Using a Markov decision process we provide a model that determines optimal daily decisions on how much energy to store as hydrogen and buy or sell from the power grid. We explicitly consider the seasonality and uncertainty of production demand and electricity prices. We show that ignoring seasonal demand and production patterns is suboptimal and that introducing hydrogen storage transforms loss-making operations into profitable ones. Extensive numerical experiments show that the distribution capacity should not be too small to prevent local grid congestion. A higher storage capacity increases the number of buying actions from the grid thereby causing more congestion which is problematic for the grid operator. We conclude that a profit-maximizing hydrogen storage operation alone is not an alternative to grid expansion to solve congestion which is essential knowledge for policy-makers and grid operators.

Hydrogen and electricity derived from renewable sources present feasible alternative energy options for the decarbonisation of the transportation and power sectors. This study presents the utilisation of hydrogen generated from solar and wind energy resources as a clean fuel for mobility and backup storage for stationary applications under economic and environmental uncertainties. This is achieved by developing a detailed technoeconomic model of an integrated system consisting of a hydrogen refuelling station and an electric power generation system using Mixed Integer Quadratic Constrained Programming (MIQCP) which is further relaxed to Mixed Integer Linear Programming (MILP). The model is implemented in the Advanced Interactive Multidi mensional Modelling Software (AIMMS) and considering the inherent uncertainties in the wind resource solar resource costs and discount rate the total cost of the three configurations (Hybrid PV-Wind Standalone PV and Standalone wind energy system) was minimised using robust optimisation technique and the corresponding optimal sizes of the components levelised cost of energy (LCOE) excess energy greenhouse emission avoided and carbon tax were evaluated. The levelised cost of the deterministic optimisation solution for all the config uration ranges between 0.0702 $/kWh to 0.0786 $/kWh while the levelised cost of the robust optimisation solution ranges between 0.07188 $/kWh to 0.1125 $/kWh. The proposed integration has the advantages of affordable hydrogen and electricity prices minimisation of carbon emissions and grid export of excess energy.

Acceleration of the hydrogen economy is being observed on a global scale. It is considered to be a potential solution to the problems with high-carbon energy industry and transport systems. The potential of production cost-competitiveness and opportunities are currently being investigated to provide insights to policymakers researchers and industry. In this context this study makes a quantitative assessment of the competitiveness of hydrogen storage compared to Li-ion batteries based on price arbitrage in the day-ahead market. Two scenarios that form the boundaries of rational decision-making regarding the charging and discharging of energy storage are considered. The first one assumes the charging and discharging of energy storage facilities over the same hours throughout the entire year. The selection of these hours is based on historical electricity prices. The second scenario assumes charge and discharge during historical daily minimum and maximum prices. The results show that NPV is below zero for both technologies when current values of investment expenditure are assumed. The outcomes of sensitivity analysis indicate that only a substantial reduction of investment expenditure could improve the financial results of the Li-ion batteries (NPV>0). The investigation also shows that even simplified charge and discharge over the same hours allows one to achieve 47% (hydrogen) and 70% (Li-ion batteries) of the maximum operating profit when the perfect foresight of prices is applied. In each case NPV for Li-ion technology is significantly higher than for hydrogen; for example for a 1 MWh and 1 MWout storage system NPV is EUR -4.85 million in the case of hydrogen and with Li-ion NPV is EUR -0.23 million. Consequently the application of expensive decision support systems in small systems may be unprofitable. The increase in profits may not cover the cost of developing and introducing such a system.

T The large-scale implementation of solar hydrogen production requires an optimal combination of photovoltaic systems with suitably-designed electrochemical cells possibly avoiding power electronics for DC-DC conversion to decrease costs. Here a stable solar-driven water splitting system is presented obtained through the direct connection of a state-of-the-art proton exchange membrane (PEM) electrolyzer to a bifacial silicon hetero junction (SHJ) solar module of three cells in series with total area of 730 cm2 . The bifaciality of the solar module has been optimized through modeling in terms of the number of cells module height and inclination. During outdoor operation in the standard monofacial configuration the system is able to produce 3.7 gr of H2 h 1 m 2 with an irradiation of 1000 W m 2 and a solar-to-hydrogen efficiency (STH) of 11.55%. The same system operating in bifacial mode gives rise to a higher H2 flux and STH efficiency reaching values of 4.2 gr of H2 h 1 m 2 and STH of 13.5%. Such a noticeable difference is achieved through the collection of albedo radiation from the ground by the bifacial PV system. The system has been tested outdoors for more than 55 h exhibiting very good endurance with no appreciable change in production and eff

This scientific article presents a developed model for optimising the scheduling of hydrogen production processes addressing the growing demand for efficient and sustainable energy sources. The study focuses on the integration of advanced scheduling techniques to improve the overall performance of the hydrogen electrolyser. The proposed model leverages constraint programming and satisfiability (CP-SAT) techniques to systematically analyse complex production schedules considering factors such as production unit capacities resource availability and energy costs. By incorporating real-world constraints such as fluctuating energy prices and the availability of renewable energy the optimisation model aims to improve overall operational efficiency and reduce production costs. The CP-SAT was applied to achieve more efficient control of the electrolysis process. The optimisation of the scheduling task was set for a 24 h time period with time resolutions of 1 h and 15 min. The performance of the proposed CP-SAT model in this study was then compared with the Monte Carlo Tree Search (MCTS)-based model (developed in our previous work). The CP-SAT was proven to perform better but has several limitations. The model response to the input parameter change has been analysed.

The synergy between hydrogen and water is crucial in moving towards a sustainable energy future. This study explores the integration of geothermal energy with desalination and hydrogen production systems to address water and clean energy demands. Two configurations one using multi-effect distillation (MED) and the other reverse osmosis (RO) were designed and compared. Both configurations utilized geothermal energy with MED directly using geothermal heat and RO converting geothermal energy into electricity to power desalination. The systems are evaluated based on various performance indicators including net power output desalinated water production hydrogen production exergy efficiency and levelized costs. Multi-objective optimization using an artificial neural network (ANN) and genetic algorithm (GA) was conducted to identify optimal operational conditions. Results highlighted that the RO-based system demonstrated higher water production efficiency achieving a broader range of optimal solutions and lower levelized costs of water (LCOW) and hydrogen production while the MED-based system offered economic advantages under specific conditions. A case study focused on Canada illustrated the potential benefits of these systems in supporting hydrogen-powered vehicles and residential water needs emphasizing the significant impact of using high-quality desalinated water to enhance the longevity and efficiency of proton exchange membrane electrolyzers (PEME). This research provides valuable insights into the optimal use of geothermal energy for sustainable water and hydrogen production.