Publications

Green hydrogen is a promising energy carrier for the decarbonization of hard-toabate sectors and supporting renewable energy integration aligning with carbon neutrality goals like the European Green Deal. Iceland’s abundant renewable energy and decarbonized electricity system position it as a strong candidate for green hydrogen production. Despite early initiatives its hydrogen economy has yet to significantly expand. This study evaluated Iceland’s hydrogen development through stakeholder interviews and a techno-economic analysis of alkaline and PEM electrolyzers. Stakeholders were driven by decarbonization goals economic opportunities and energy security but faced technological economic and governance challenges. Recommendations include building stakeholder confidence financial incentives and creating hydrogen-based chemicals to boost demand. Currently alkaline electrolyzers are more cost-effective (EUR 1.5–2.8/kg) than PEMs (EUR 2.1–3.6/kg) though the future costs for both could drop below EUR 1.5/kg. Iceland’s low electricity costs and high electrolyzer capacity provide a competitive edge. However this advantage may shrink as solar and wind costs decline globally particularly in regions like Australia. This work’s findings emphasize the need for strategic planning to sustain competitiveness and offer transferable insights for other regions introducing hydrogen into ecosystems lacking infrastructure.

A recent consensus to achieve carbon neutrality is promoting interest in the use of hydrogen and management of its production system. Among the several types of hydrogen green hydrogen is of most interest which is produced using power generated from renewable energy sources (RES). However several challenges are encountered in the stable operation of green hydrogen production systems (GHPS) owing to the inherent intermittent and variables characteristics of RES. Although the implementation of energy storage systems (ESS) can aid in compensating for this variability large-scale ESS installations can be economically infeasible. Thus this study seeks an operation strategy suitable for GHPS considering the expected variability of RES and the operational conditions of a relatively small-sized ESS. In particular as state-of-charge management is crucial for operating an ESS with limited capacity this study presents a method to conduct coordinated control between the ESS and electrolyzer. Furthermore considering the characteristics of the GHPS the expected short-term variability analyzed using the copula-based approach is utilized. The proposed method is validated based on various RES generation scenarios. By applying the developed method operational continuity to GHPS is expected to increase with efficiency.

Hydrogen is a key energy carrier in the global transition to low-carbon systems requiring scalable and secure storage solutions. While underground hydrogen storage (UHS) in salt caverns is proven its cost and limited geographic availability have led to growing interest in depleted oil and gas reservoirs. A critical factor in evaluating these reservoirs is the sealing capacity of the overlying caprock. This study presents a novel experimental protocol for assessing caprock integrity under UHS conditions using a custom-designed core-flooding apparatus integrated with a micro-capillary flow meter. This setup enables high-resolution measurements of ultra-low permeabilities (as low as 10 nano-Darcy) flow rates (down to 10 nano-liters/hour) threshold pressure and breakthrough pressure. Benchmark tests with nitrogen and methane were followed by hydrogen experiments across caprocks with a wide range of permeability and porosity. The results demonstrate clear trends between caprock properties and sealing performance providing a quantitative framework for evaluating UHS site suitability. Hydrogen showed slightly lower threshold and breakthrough pressures compared to other gases reinforcing the need for accurate site-specific caprock evaluation. The proposed method offers a robust approach for characterizing candidate storage sites in depleted reservoirs.

Industrial alkaline water electrolysis systems face challenges in maintaining hydrogenin-oxygen impurity within safe limits under fluctuating operating conditions. This study aims to characterize the dynamic response of hydrogen-in-oxygen concentration in an industrial 10 kW alkaline water electrolysis test platform (2 Nm3/h hydrogen output at 1.6 MPa and 90 ◦C) and to identify how operating parameters influence hydrogen-inoxygen behavior. We systematically varied the cell current system pressure and electrolyte flow rate while monitoring real-time hydrogen-in-oxygen levels. The results show that hydrogen-in-oxygen exhibits significant inertia and delay: during startup hydrogen-inoxygen remained below the 2% safety threshold and stabilized at 0.9% at full load whereas a step decrease to 60% load caused hydrogen-in-oxygen to rise to 1.6%. Furthermore reducing the pressure from 1.4 to 1.0 MPa lowered the hydrogen-in-oxygen concentration by up to 15% and halving the alkaline flow rate suppressed hydrogen-in-oxygen by over 20% compared to constant conditions. These findings provide new quantitative insights into hydrogen-in-oxygen dynamics and offer a basis for optimizing control strategies to keep gas purity within safe limits in industrial-scale alkaline water electrolysis systems.

This study comprehensively reviews the state-of-the-art laboratory-scale fracture mechanics testing methods to assess their suitability for investigating stress-induced critical cracks and geochemically induced subcritical cracks in caprock during underground hydrogen storage. Subcritical crack propagation is primarily examined using empirical techniques such as double torsion and constant stress-rate methods. Both methods determine stress intensity factors and crack velocities without requiring crack length measurements. Comparatively the double torsion method provides advantages such as simple sample preparation and pre-cracking process continuous data acquisition and fracture toughness measurements which makes it more reliable for caprockrelated studies. The International Society for Rock Mechanics recommends four standard methods for critical crack propagation to determine fracture toughness values. Chevron-notched specimens including the Chevron Bend specimen Short Rod specimen and Cracked Chevron Notched Brazilian Disk specimen exhibit higher uncertainty in fracture toughness data due to specimen size effects additional fixture requirements and undesirable crack formations. In contrast the Semi-Circular Bend specimen method is frequently employed due to its smaller specimen size simplified testing and well-balanced dynamic forces. Despite these advancements studies on multiple cracking behaviour in caprock under subsurface hydrogen storage conditions remain limited. The conventional methods discussed in this review are primarily designed to function at ambient conditions making it challenging to replicate subsurface geochemical interactions. Future studies should focus more on developing new laboratory techniques and enhancing existing specimen configurations by incorporating specialised apparatus such as high-pressure cells and reaction chambers to implement typical subsurface conditions observed during underground hydrogen storage. Additionally more parametric studies on caprock samples are recommended to generate a comprehensive dataset on subcritical and critical crack propagation and validate the reliability of these testing methods for underground hydrogen storage applications.

The coupling of renewable energy sources with electrolyzers under standalone conditions significantly enhances the operational efficiency and improves the costeffectiveness of electrolyzers as a technologically viable and sustainable solution for green hydrogen production. To address the configuration optimization challenge in hybrid electrolyzer systems integrating alkaline water electrolysis (AWE) and proton exchange membrane electrolysis (PEME) this study proposes an innovative methodology leveraging the morphological analysis of Pareto frontiers to determine the optimal solutions under multi-objective functions including the hydrogen production cost and efficiency. Then the complementary advantages of AWE and PEME are explored. The proposed methodology demonstrated significant performance improvements compared with the single-objective optimization function. When contrasted with the economic optimization function the hybrid system achieved a 1.00% reduction in hydrogen production costs while enhancing the utilization efficiency by 21.71%. Conversely relative to the efficiency-focused optimization function the proposed method maintained a marginal 5.22% reduction in utilization efficiency while achieving a 6.46% improvement in economic performance. These comparative results empirically validate that the proposed hybrid electrolyzer configuration through the implementation of the novel optimization framework successfully establishes an optimal balance between the economy and efficiency of hydrogen production. Additionally a discussion on the key factors affecting the rated power and mixing ratio of the hybrid electrolyzer in this research topic is provided.

In response to the surging global demand for clean energy solutions and sustainability hydrogen is increasingly recognized as a key player in the transition towards a low-carbon future necessitating efficient storage and transportation methods. The utilization of natural geological formations for underground storage solutions is gaining prominence ensuring continuous energy supply and enhancing safety measures. However this approach presents challenges in understanding gas-rock interactions. To bridge the gap this study proposes a data-driven strategy for contact angle prediction using machine learning techniques. The research leverages a comprehensive dataset compiled from diverse literature sources comprising 1045 rows and over 5200 data points. Input features such as pressure injection rate temperature salinity rock type and substrate were incorporated. Various artificial intelligence algorithms including Support Vector Machine (SVM) k-Nearest Neighbors (KNN) Feedforward Deep Neural Network (FNN) and Recurrent Deep Neural Network (RNN) were employed to predict contact angle with the FNN algorithm demonstrating superior performance accuracy compared to others. The strengths of the FNN algorithm lie in its ability to model nonlinear relationships scalability to large datasets robustness to noisy inputs generalization to unseen data parallelizable training processes and architectural flexibility. Results show that the FNN algorithm demonstrates higher accuracy (RMSE = 0.9640) than other algorithms (RMSERNN = 1.7452 RMSESVM = 1.8228 RMSEKNN = 1.0582) indicating its efficacy in predicting the contact angle testing subset within the context of underground hydrogen storage. The findings of this research highlight a low-cost and reliable approach with high accuracy for estimating contact angle of water–hydrogen–rock system. This technique also helps determine the contribution and influence of independent factors aiding in the interpretation of absorption tendencies and the ease of hydrogen gas flow through the porous rock space during underground hydrogen storage.

Deregulation in the energy sector has transformed the power systems with significant use of competition innovation and sustainability. This paper outlines a comparative study of renewable energy sources with electric vehicles (RES-EV) integration in a deregulated smart power system to highlight the learning on system efficiency effectiveness viability and the environment. This study depicts the importance of solar and wind energy in reducing carbon emissions and the challenges of integrating RES into present energy grids. It touches on the aspects of advanced energy storage systems demand-side management (DSM) and smart charging technologies for optimizing energy flows and stabilizing grids because of fluctuating demands. Findings were presented to show that based on specific pricing thresholds hybrid renewable energy systems can achieve grid parity and market competitiveness. Novel contributions included an in-depth exploration of the economic and technical feasibility of integrating EVs at the distribution level improvements in power flow control mechanisms and strategies to overcome challenges in decentralized energy systems. These insights will help policymakers and market participants make headway in the adoption of microgrids and smart grids within deregulated energy systems which is a step toward fostering a sustainable and resilient power sector.

Unlocking the potential of offshore renewables for green hydrogen (GH2) production can be a game-changer empowering economies with their visionary clean energy policies amplifying energy security and promoting economic growth. However their novelty entails uncertainty and risk necessitating a robust framework for facility deployment and infrastructure planning. To optimize offshore GH2 infrastructure placement this work proposes a novel and robust GIS-based multi-criteria decision-making (MCDM) framework. Encompassing thirtytwo techno-socio-economic-safety factors and ocean environmental impact analysis this methodology facilitates informed decision-making for sustainable and safe GH2 development. Utilizing the synergies between offshore wind and solar resources this study investigates the potential of hybrid ocean technologies to enhance space utilization and optimize efficiency. To illustrate the practical application of the proposed framework a case study examining a GH2 system in Australia's marine region and its potential nexus with nearby offshore industries has been conducted. The performed life cycle assessment (LCA) explored various configurations of GH2 production storage and transportation technologies. A Bayesian objective weight integrating technique has been introduced and contrasted statistically with the hybrid CRITIC Entropy MEREC and MARCOS-based MCDM approaches. Various locations are ranked based on the net present value of life cycle cost GH2 production capacity risk availability and environment sustainability factors illustrating their compatibility. A sensitivity analysis is conducted to confirm that a Bayesian approach improves the decision-making outcomes through identifying optimal criteria weights and alternative ranks more effectively. Empowering strategic GH2 decisions globally the proposed approach optimizes system performances cost sustainability and safety excelling in harsh environments.

Around 75% of worldwide greenhouse gas (GHG) emissions are generated by the combustion of fossil fuels (FFs) for energy production. Tackling climate change requires a global shift away from FF reliance and the decarbonization of energy systems. The energy manufacturing and construction sectors contribute a significant portion of Egypt’s total GHG emissions largely due to the reliance on fossil fuels in energy-intensive industries (EIIs). Decarbonizing these sectors is essential to achieve Egypt’s sustainable development goals improve air quality and create a resilient low-carbon economy. This paper examines practical scalable solutions to decarbonize energy-intensive industries in Egypt focusing on implementing renewable energy sources (RESs) enhancing energy efficiency and integrating new technologies such as carbon capture utilization and storage (CCUS) and green hydrogen (GH). We also explore the policy incentives and economic drivers that can facilitate these changes as the government aims to achieve net-zero GHG emissions for a sustainable transition by 2050.